WO2023149162A1 - Information processing device, inference device, machine learning device, information processing method, inference method, and machine learning method - Google Patents

Information processing device, inference device, machine learning device, information processing method, inference method, and machine learning method Download PDF

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Publication number
WO2023149162A1
WO2023149162A1 PCT/JP2023/000378 JP2023000378W WO2023149162A1 WO 2023149162 A1 WO2023149162 A1 WO 2023149162A1 JP 2023000378 W JP2023000378 W JP 2023000378W WO 2023149162 A1 WO2023149162 A1 WO 2023149162A1
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WO
WIPO (PCT)
Prior art keywords
substrate processing
fluid supply
processing fluid
information
substrate
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PCT/JP2023/000378
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French (fr)
Japanese (ja)
Inventor
充 宮▲崎▼
大地 近藤
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株式会社荏原製作所
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Publication of WO2023149162A1 publication Critical patent/WO2023149162A1/en

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B24—GRINDING; POLISHING
    • B24B—MACHINES, DEVICES, OR PROCESSES FOR GRINDING OR POLISHING; DRESSING OR CONDITIONING OF ABRADING SURFACES; FEEDING OF GRINDING, POLISHING, OR LAPPING AGENTS
    • B24B37/00—Lapping machines or devices; Accessories
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B24—GRINDING; POLISHING
    • B24B—MACHINES, DEVICES, OR PROCESSES FOR GRINDING OR POLISHING; DRESSING OR CONDITIONING OF ABRADING SURFACES; FEEDING OF GRINDING, POLISHING, OR LAPPING AGENTS
    • B24B49/00—Measuring or gauging equipment for controlling the feed movement of the grinding tool or work; Arrangements of indicating or measuring equipment, e.g. for indicating the start of the grinding operation
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
    • H01L21/00—Processes or apparatus adapted for the manufacture or treatment of semiconductor or solid state devices or of parts thereof
    • H01L21/02—Manufacture or treatment of semiconductor devices or of parts thereof
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
    • H01L21/00—Processes or apparatus adapted for the manufacture or treatment of semiconductor or solid state devices or of parts thereof
    • H01L21/02—Manufacture or treatment of semiconductor devices or of parts thereof
    • H01L21/04—Manufacture or treatment of semiconductor devices or of parts thereof the devices having potential barriers, e.g. a PN junction, depletion layer or carrier concentration layer
    • H01L21/18—Manufacture or treatment of semiconductor devices or of parts thereof the devices having potential barriers, e.g. a PN junction, depletion layer or carrier concentration layer the devices having semiconductor bodies comprising elements of Group IV of the Periodic Table or AIIIBV compounds with or without impurities, e.g. doping materials
    • H01L21/30—Treatment of semiconductor bodies using processes or apparatus not provided for in groups H01L21/20 - H01L21/26
    • H01L21/302—Treatment of semiconductor bodies using processes or apparatus not provided for in groups H01L21/20 - H01L21/26 to change their surface-physical characteristics or shape, e.g. etching, polishing, cutting
    • H01L21/304—Mechanical treatment, e.g. grinding, polishing, cutting

Definitions

  • the present invention relates to an information processing device, an inference device, a machine learning device, an information processing method, an inference method, and a machine learning method.
  • a substrate processing apparatus that performs chemical mechanical polishing (CMP) processing is known as one of substrate processing apparatuses that perform various types of processing on substrates such as semiconductor wafers.
  • CMP chemical mechanical polishing
  • a substrate processing apparatus for example, while a polishing table having a polishing pad is rotated, a polishing liquid (slurry) is supplied to the polishing pad from a liquid supply nozzle, and a polishing head called a top ring presses the substrate against the polishing pad. , the substrate is chemically and mechanically polished. Then, in order to remove foreign matter such as polishing dust adhering to the substrate after polishing, the substrate after polishing is scrub-cleaned by bringing a cleaning tool into contact with the substrate while supplying a substrate-cleaning fluid, and then the substrate is dried. , the processing of the next substrate is started.
  • Patent Document 1 adjusts the supply position of the polishing slurry by appropriately moving the tip of the supply nozzle according to the amount of supply of the polishing slurry, the position of the wafer, and the like.
  • the operating conditions such as the fluid supply flow rate, the fluid supply pressure, the opening degree of the fluid supply valve, the pressure on the primary side of the fluid supply valve, etc.
  • Positional influencing factors are complex and interact with substrate processing fluid application position. Therefore, it is difficult to accurately analyze how each operating state affects the supply position of the substrate processing fluid.
  • the present invention provides an information processing apparatus, an inference apparatus, a machine learning apparatus, an information processing method, an inference apparatus, and an apparatus capable of supplying a substrate processing fluid to an appropriate position according to the supply state of the substrate processing fluid. It aims to provide a method and a machine learning method.
  • an information processing device includes: Substrate processing showing a supply state of a substrate processing fluid supplied from the substrate processing fluid supply unit in the substrate processing performed by the substrate processing apparatus having one or more substrate processing fluid supply units for supplying the processing fluid to the substrate an information acquisition unit for acquiring substrate processing fluid supply information including fluid supply state information; learning by machine learning a correlation between the substrate processing fluid supply information and substrate processing fluid supply position information indicating a supply position of the fluid supplied by the substrate processing fluid supply unit when the substrate processing apparatus is operated; a state prediction unit that predicts the substrate processing fluid supply position information with respect to the substrate processing fluid supply information by inputting the substrate processing fluid supply information acquired by the information acquisition unit into a model; Prepare.
  • the substrate processing fluid supply information including the substrate processing fluid supply state information is input to the learning model, whereby the substrate processing fluid supply position information corresponding to the substrate processing fluid supply information is obtained. is predicted, the substrate processing fluid supply position can be appropriately predicted according to the substrate processing fluid supply state of the substrate processing apparatus.
  • FIG. 1 is an overall configuration diagram showing an example of a substrate processing system 1;
  • FIG. 1 is a plan view showing an example of a substrate processing apparatus 2;
  • FIG. 4 is a perspective view showing an example of first to fourth polishing portions 22A to 22D;
  • FIG. 4 is a perspective view showing an example of first and second roll sponge cleaning units 24A and 24B;
  • FIG. 3 is a perspective view showing an example of first and second pen sponge cleaning units 24C and 24D.
  • FIG. 3 is a perspective view showing an example of first and second drying sections 24E and 24F;
  • FIG. 4 is a diagram showing the arrangement of substrate processing fluid supply valves in a substrate processing fluid supply system;
  • 2 is a block diagram showing an example of a substrate processing apparatus 2;
  • FIG. 3 is a hardware configuration diagram showing an example of a computer 900;
  • FIG. 3 is a data configuration diagram showing an example of production history information 30 managed by a database device 3;
  • FIG. 3 is a data configuration diagram showing an example of finishing test information 31 managed by the database device 3.
  • FIG. 1 is a block diagram showing an example of a machine learning device 4 according to a first embodiment;
  • FIG. It is a figure which shows an example of 10 A of 1st learning models, and 11 A of data for 1st learning.
  • 4 is a flowchart showing an example of a machine learning method by the machine learning device 4;
  • 1 is a block diagram showing an example of an information processing device 5 according to a first embodiment;
  • FIG. 5 is a flowchart showing an example of an information processing method by the information processing device 5; It is a block diagram which shows an example of the machine-learning apparatus 4a based on 2nd Embodiment. It is a figure which shows an example of the 2nd learning model 10B and the 2nd data for learning 11B.
  • FIG. 5 is a block diagram showing an example of an information processing device 5a functioning as an information processing device 5a according to a second embodiment;
  • FIG. 5 is a functional explanatory diagram showing an example of an information processing device 5a according to a second embodiment;
  • FIG. 1 is an overall configuration diagram showing an example of a substrate processing system 1.
  • the substrate processing system 1 performs a chemical mechanical polishing process (hereinafter referred to as "polishing") for flatly polishing the surface of the wafer W by pressing the substrate (hereinafter referred to as "wafer") W such as a semiconductor wafer against a polishing pad.
  • a series of substrate processing including a cleaning process of cleaning the surface of the wafer W by bringing the polished wafer W into contact with a cleaning tool, and a drying process of drying the cleaned surface of the wafer W using a drying tool. function as a system to manage Note that the cleaning treatment and the drying treatment constitute finishing treatment.
  • the substrate processing system 1 includes a substrate processing device 2, a database device 3, a machine learning device 4, an information processing device 5, and a user terminal device 6 as its main components.
  • Each of the devices 2 to 6 is configured by, for example, a general-purpose or dedicated computer (see FIG. 8 described later), and is connected to a wired or wireless network 7 to store various data (partial data in FIG. 1). (shown by dashed arrows) can be mutually transmitted and received.
  • the number of devices 2 to 6 and the connection configuration of the network 7 are not limited to the example shown in FIG. 1, and may be changed as appropriate.
  • the substrate processing apparatus 2 is composed of a plurality of units, and performs a series of substrate processing on one or a plurality of wafers W, such as loading, polishing, cleaning, drying, film thickness measurement, and unloading. It is a device that performs each. At this time, the substrate processing apparatus 2 refers to apparatus setting information 265 consisting of a plurality of apparatus parameters respectively set for each unit, and substrate recipe information 266 that defines the operation states of the polishing process, the cleaning process, the drying process, and the like. while controlling the operation of each unit.
  • the substrate processing apparatus 2 transmits various reports R to the database device 3, the user terminal device 6, etc. according to the operation of each unit.
  • the various reports R include, for example, process information specifying the target wafer W when substrate processing was performed, apparatus status information indicating the status of each unit when each process was performed, substrate processing apparatus 2 event information detected in , operation information of a user (operator, production manager, maintenance manager, etc.) for the substrate processing apparatus 2, and the like.
  • the database device 3 stores production history information 30 relating to the history of substrate processing performed using the substrate processing fluid supply unit for actual production, and test substrate processing fluid supply using the test substrate processing fluid supply unit. It is a device for managing substrate processing fluid supply test information 31 relating to the history of the execution of the substrate processing fluid supply test (hereinafter referred to as "substrate processing fluid supply test").
  • the database device 3 may store device setting information 265 and substrate recipe information 266. In that case, the substrate processing device 2 may refer to these information. good.
  • the substrate processing fluid includes at least one of a polishing fluid in polishing processing, a cleaning fluid in cleaning processing, and a drying fluid in drying processing. Therefore, the substrate processing fluid supply test includes at least one of a polishing process test, a cleaning process test, and a drying process test.
  • the database device 3 receives various reports R from the substrate processing apparatus 2 as needed and registers them in the production history information 30 when the substrate processing apparatus 2 performs substrate processing using the substrate processing fluid supply unit for production. As a result, the production history information 30 accumulates reports R regarding substrate processing.
  • the database device 3 receives various reports R (including at least device status information) from the substrate processing apparatus 2 when the substrate processing apparatus 2 performs a substrate processing fluid supply test using the test substrate processing fluid supply unit. It is received as needed and registered in the substrate processing fluid supply test information 31, and the test results of the substrate processing fluid supply test are registered in association with each other. Reports R and test results are accumulated.
  • the substrate processing fluid supply test may be performed by the substrate processing apparatus 2 for production, or by a test substrate processing fluid supply test apparatus (not applicable) that can reproduce the same substrate processing fluid supply as the substrate processing apparatus 2. shown).
  • the condition of the substrate processing fluid supply unit is, for example, the flow rate of the substrate processing fluid supplied from the substrate processing fluid supply unit, the flow rate of the substrate processing fluid supplied from the substrate processing fluid supply unit, for measuring the pressure of the supplied substrate processing fluid, the state of the substrate processing fluid supply valve that regulates the flow rate of the substrate processing fluid, and the pressure on the primary side of the substrate processing fluid supply valve that regulates the flow rate of the substrate processing fluid;
  • Various substrate processing fluid supply state measuring devices (not shown) are provided, and the measured values of the substrate processing fluid supply state measuring devices are registered in the substrate processing fluid supply test information 31 as test results.
  • the machine learning device 4 operates as a main part of the learning phase of machine learning, for example, acquires part of the substrate processing fluid supply test information 31 from the database device 3 as first learning data 11A, and stores it in the information processing device 5.
  • Machine learning generates a first learning model 10A used for The trained first learning model 10A is provided to the information processing device 5 via the network 7, a recording medium, or the like.
  • the information processing device 5 operates as the subject of the inference phase of machine learning, and uses the first learning model 10A generated by the machine learning device 4 to determine whether the substrate processing fluid supplied by the substrate processing device 2 is suitable for production.
  • the substrate processing fluid supply position is predicted, and substrate processing fluid supply position information, which is the predicted result, is transmitted to the database device 3, the user terminal device 6, and the like.
  • the timing at which the information processing apparatus 5 predicts the substrate processing fluid supply position information may be after the substrate processing fluid is supplied (post-prediction processing) or while the substrate processing fluid is being supplied ( real-time prediction processing) or before the substrate processing fluid is supplied (advance prediction processing).
  • the user terminal device 6 is a terminal device used by the user, and may be a stationary device or a portable device.
  • the user terminal device 6 receives various input operations via the display screen of, for example, an application program or a web browser, and various information via the display screen (e.g., event notification, substrate processing fluid supply position information, production history information 30, substrate processing fluid supply test information 31, etc.).
  • FIG. 2 is a plan view showing an example of the substrate processing apparatus 2.
  • the substrate processing apparatus 2 includes a load/unload unit 21, a polishing unit 22, a substrate transfer unit 23, a finishing unit 24, a film thickness measurement unit 25, and a housing 20 which is substantially rectangular in plan view. and a control unit 26 .
  • a first partition wall 200A separates the load/unload unit 21 from the polishing unit 22, the substrate transfer unit 23 and the finishing unit 24, and the substrate transfer unit 23 and the finishing unit 24 are separated from each other by a second separation wall 200A. It is partitioned by a partition wall 200B.
  • the loading/unloading unit 21 includes first to fourth front loading sections 210A to 210D on which wafer cassettes (FOUPs, etc.) capable of vertically accommodating a large number of wafers W are placed, and A transfer robot 211 capable of moving up and down along the storage direction (vertical direction) of the wafer W, and a transfer robot 211 along the direction in which the first to fourth front load sections 210A to 210D are arranged (transverse direction of the housing 20). and a horizontal movement mechanism 212 for moving the .
  • wafer cassettes FOUPs, etc.
  • the transfer robot 211 carries wafer cassettes placed on each of the first to fourth front load sections 210A to 210D, the substrate transfer unit 23 (specifically, a lifter 232 to be described later), and the finishing unit 24 (specifically, First and second drying units 24E and 24F, which will be described later), and the film thickness measurement unit 25, are configured to be accessible, and upper and lower two-stage hands (not shown) for transferring the wafer W between them ).
  • the lower hand is used when transferring wafers W before processing, and the upper hand is used when transferring wafers W after processing.
  • a shutter (not shown) provided on the first partition 200A is opened and closed.
  • the polishing unit 22 includes first to fourth polishing sections 22A to 22D for polishing (flattening) the wafer W, respectively.
  • the first to fourth polishing parts 22A to 22D are arranged side by side along the longitudinal direction of the housing 20. As shown in FIG.
  • FIG. 3 is a perspective view showing an example of the first to fourth polishing units 22A to 22D.
  • the basic configurations and functions of the first to fourth polishing units 22A to 22D are common.
  • Each of the first to fourth polishing units 22A to 22D includes a polishing table 220 that rotatably supports a polishing pad 2200 having a polishing surface, a wafer W that holds the wafer W, and a polishing pad on the polishing table 220 that holds the wafer W.
  • a dresser 223 that contacts the polishing surface of 2200 to dress the polishing pad 2200 and an atomizer 224 that sprays cleaning fluid onto the polishing pad 2200 are provided.
  • the polishing table 220 is supported by a polishing table shaft 220a and includes a rotational movement mechanism 220b that rotates the polishing table 220 about its axis, and a temperature control mechanism 220c that adjusts the surface temperature of the polishing pad 2200. .
  • the top ring 221 is supported by a top ring shaft 221a that can move vertically.
  • a rotation movement mechanism 221c rotates the top ring 221 about its axis, and a vertical movement mechanism moves the top ring 221 vertically. It includes a mechanism portion 221d and a rocking movement mechanism portion 221e for rotating (swinging) the top ring 221 around the support shaft 221b.
  • the polishing fluid supply nozzle 222 is supported by a support shaft 222a.
  • a rocking movement mechanism 222b rotates and moves the polishing fluid supply nozzle 222 around the support shaft 222a, and a flow control unit adjusts the flow rate of the polishing fluid.
  • 222c and a temperature control mechanism 222d for adjusting the temperature of the polishing fluid.
  • the polishing fluid is a polishing liquid (slurry) or pure water, and may further contain a chemical liquid, or may be a polishing liquid to which a dispersant is added.
  • the polishing fluid supply nozzle 222 constitutes a substrate processing fluid supply section.
  • the dresser 223 is supported by a vertically movable dresser shaft 223a.
  • the dresser 223 is supported by a rotational movement mechanism 223c that drives the dresser 223 to rotate about its axis, and a vertical movement mechanism 223d that vertically moves the dresser 223. , and a swing movement mechanism portion 223e for swinging and moving the dresser 223 around the support shaft 223b.
  • the atomizer 224 is supported by a support shaft 224a and includes a swing movement mechanism section 224b that swings and moves the atomizer 224 around the support shaft 224a, and a flow rate adjustment section 224c that adjusts the flow rate of the cleaning fluid.
  • the cleaning fluid is a mixed fluid of liquid (eg, pure water) and gas (eg, nitrogen gas) or liquid (eg, pure water).
  • the wafer W is held by suction on the lower surface of the top ring 221 and moved to a predetermined polishing position on the polishing table 220 , the wafer W is applied to the polishing surface of the polishing pad 2200 to which the polishing fluid is supplied from the polishing fluid supply nozzle 222 . It is polished by being pressed by the top ring 221 .
  • the substrate transfer unit 23 is, as shown in FIG. 2, first and second linear transporters horizontally movable along the direction in which the first to fourth polishing units 22A to 22D are arranged (the longitudinal direction of the housing 20). 230A, 230B, a swing transporter 231 disposed between the first and second linear transporters 230A, 230B, a lifter 232 disposed on the loading/unloading unit 21 side, and a finishing unit 24 side. and a temporary placing table 233 for the wafer W which has been processed.
  • the first linear transporter 230A is arranged adjacent to the first and second polishing units 22A and 22B and has four transport positions (first to fourth transport positions in order from the load/unload unit 21 side). TP1 to TP4) for transporting the wafer W.
  • the second transfer position TP2 is the position at which the wafer W is transferred to the first polishing section 22A
  • the third transfer position TP3 is the position at which the wafer W is transferred to the second polishing section 22B. be.
  • the second linear transporter 230B is arranged adjacent to the third and fourth polishing units 22C and 22D and has three transport positions (fifth to seventh transport positions in order from the load/unload unit 21 side). TP5 to TP7) for transporting the wafer W.
  • the sixth transfer position TP6 is a position for transferring the wafer W to the third polishing section 22C
  • the seventh transfer position TP7 is a position for transferring the wafer W to the fourth polishing section 22D.
  • the swing transporter 231 is arranged adjacent to the fourth and fifth transport positions TP4 and TP5 and has a hand that can move between the fourth and fifth transport positions TP4 and TP5.
  • the swing transporter 231 is a mechanism that transfers the wafer W between the first and second linear transporters 230A and 230B and temporarily places the wafer W on the temporary placement table 233 .
  • the lifter 232 is a mechanism arranged adjacent to the first transfer position TP1 to transfer the wafer W to and from the transfer robot 211 of the load/unload unit 21 .
  • a shutter (not shown) provided on the first partition 200A is opened and closed.
  • the finishing unit 24 as shown in FIG.
  • First and second pen sponge cleaning units 24C and 24D which are arranged in two upper and lower stages, serve as substrate cleaning devices
  • first and second pen sponge cleaning units 24C, 24D which are arranged in two upper and lower stages, serve as substrate drying devices for drying the wafers W after cleaning. and second drying sections 24E and 24F, and first and second transfer sections 24G and 24H for transferring the wafer W.
  • the number and arrangement of the roll sponge cleaning units 24A and 24B, the pen sponge cleaning units 24C and 24D, the drying units 24E and 24F, and the transport units 24G and 24H are not limited to the example shown in FIG. good.
  • the roll sponge cleaning units 24A and 24B and the pen sponge cleaning units 24C and 24D constitute a cleaning unit
  • the drying units 24E and 24F constitute a drying unit.
  • Each section 24A to 24H of the finishing unit 24 is divided along the first and second linear transporters 230A and 230B, for example, the first and second roll sponge cleaning sections 24A and 24B, the second 1 conveying section 24G, first and second pen sponge washing sections 24C, 24D, second conveying section 24H, and first and second drying sections 24E, 24F in this order (from the load/unload unit 21 farthest order).
  • the finishing unit 24 subjects the wafer W after the polishing process to primary cleaning processing by either the first and second roll sponge cleaning units 24A and 24B, and the first and second pen sponge cleaning units 24C and 24D. A secondary cleaning process by one of them and a drying process by one of the first and second drying units 24E and 24F are performed in this order.
  • the roll sponge 2400 and pen sponge 2401 are made of synthetic resin such as PVA and nylon, and have a porous structure.
  • the roll sponge 2400 and the pen sponge 2401 function as cleaning tools for scrub cleaning the wafer W, and are the first and second roll sponge cleaning units 24A and 24B and the first and second pen sponge cleaning units 24C. , 24D, respectively.
  • the first transport section 24G includes a first transport robot 246A that can move vertically.
  • the first transport robot 246A operates on the temporary table 233 of the substrate transport unit 23, the first and second roll sponge cleaning units 24A and 24B, and the first and second pen sponge cleaning units 24C and 24D. It is configured to be accessible and has upper and lower two-stage hands for transferring wafers W therebetween. For example, the lower hand is used when transferring wafers W before cleaning, and the upper hand is used when transferring wafers W after cleaning.
  • a shutter (not shown) provided on the second partition 200B is opened and closed.
  • the second transport section 24H includes a second transport robot 246B that can move vertically.
  • the second transfer robot 246B is configured to be able to access the first and second pen sponge cleaning units 24C, 24D and the first and second drying units 24E, 24F, between which the wafer W is transferred. Equipped with a hand for passing
  • FIG. 4 is a perspective view showing an example of the first and second roll sponge cleaning parts 24A, 24B.
  • the basic configurations and functions of the first and second roll sponge cleaning units 24A and 24B are common.
  • the first and second roll sponge cleaning units 24A and 24B have a pair of roll sponges 2400 arranged vertically so as to sandwich the surfaces to be cleaned (front and back surfaces) of the wafer W.
  • Each of the first and second roll sponge cleaning units 24A and 24B can rotate a substrate holding unit 241 that holds the wafer W, a cleaning fluid supply unit 242 that supplies substrate cleaning fluid to the wafer W, and a roll sponge 2400.
  • a substrate cleaning unit 240 that supports the substrate and cleans the wafer W by bringing the roll sponge 2400 into contact with the wafer W;
  • a cleaning tool cleaning unit 243 that cleans (self-cleans) the roll sponge 2400 with a cleaning tool cleaning fluid; and an environment sensor 244 that measures the condition of the internal space of the housing 20 where the operation is performed.
  • the substrate holding unit 241 includes a substrate holding mechanism unit 241a that holds a plurality of locations on the side edge of the wafer W, and a substrate rotation mechanism unit that rotates the wafer W around a third rotation axis perpendicular to the surface to be cleaned of the wafer W. 241b.
  • the substrate holding mechanism part 241a is two driven rollers, and at least one driven roller is configured to be movable with respect to the side edge of the wafer W in the holding direction or separation direction.
  • the substrate rotation mechanism part 241b is two drive rollers.
  • the substrate holding section 241 may be a substrate holding mechanism section 241a composed of a plurality of driven rollers and a substrate rotation mechanism section 241b composed of at least one driving roller.
  • the cleaning fluid supply unit 242 includes a cleaning fluid supply nozzle 242a that supplies the substrate cleaning fluid to the surface to be cleaned of the wafer W, a swing movement mechanism 242b that swivels the cleaning fluid supply nozzle 242a, and the cleaning fluid supply nozzle 242a. It includes a vertical movement mechanism 242c for vertical movement, a flow control unit 242d for adjusting the flow rate and pressure of the substrate cleaning fluid, and a temperature control mechanism 242e for adjusting the temperature of the substrate cleaning fluid.
  • the cleaning fluid supply nozzle 242a constitutes a substrate processing fluid supply section.
  • the substrate cleaning fluid may be either pure water (rinse liquid) or chemical solution, and the cleaning fluid supply nozzle 242a is provided with separate nozzles for pure water and chemical solutions, as shown in FIG. may Also, the substrate cleaning fluid may be a liquid, a two-fluid mixture of a liquid and a gas, or may contain a solid such as dry ice.
  • the substrate cleaning section 240 includes a cleaning tool rotation mechanism section 240a that rotates the roll sponge 2400 around a first rotation axis parallel to the surface to be cleaned of the wafer W, and the height of the pair of roll sponges 2400 and the separation distance between the two.
  • a vertical movement mechanism 240b for vertically moving at least one of the pair of roll sponges 2400 and a linear movement mechanism 240c for linearly moving the pair of roll sponges 2400 in the horizontal direction are provided.
  • the vertical movement mechanism portion 240b and the linear movement mechanism portion 240c function as a cleaning tool movement mechanism portion that moves the relative positions of the roll sponge 2400 and the surface of the wafer W to be cleaned.
  • the cleaning tool cleaning part 243 is arranged at a position not interfering with the wafer W, and accommodated in the cleaning tool cleaning tank 243a capable of storing and discharging the cleaning tool cleaning fluid and the cleaning tool cleaning tank 243a.
  • a flow control unit 243d is provided to control the flow rate and pressure of the cleaning tool cleaning fluid discharged to the outside.
  • the cleaning tool cleaning fluid may be pure water (rinse liquid) or chemical solution.
  • the environment sensor 244 includes, for example, a temperature sensor 244a and a humidity sensor 244b.
  • a camera image sensor capable of photographing the surface of the wafer W, the roll sponge 2400, etc. during the cleaning process or before and after the cleaning process may be provided.
  • the wafer W is rotated by the substrate rotating mechanism 241b while being held by the substrate holding mechanism 241a. Then, in a state in which the substrate cleaning fluid is supplied to the surface to be cleaned of the wafer W from the cleaning fluid supply nozzle 242a, the roll sponge 2400 rotated around the axis by the cleaning tool rotation mechanism 240a is applied to the surface to be cleaned of the wafer W. The wafer W is cleaned by the sliding contact.
  • the substrate cleaning unit 240 moves the roll sponge 2400 to the cleaning tool cleaning tank 243a, for example, rotates the roll sponge 2400, presses it against the cleaning tool cleaning plate 243b, or controls the cleaning tool cleaning fluid by the flow control unit 243d. is supplied to the roll sponge 2400, the roll sponge 2400 is cleaned.
  • FIG. 5 is a perspective view showing an example of the first and second pen sponge cleaning units 24C and 24D.
  • the basic configurations and functions of the first and second pen sponge cleaning units 24C and 24D are common.
  • Each of the first and second pen sponge cleaning units 24C and 24D can rotate a substrate holding unit 241 that holds the wafer W, a cleaning fluid supply unit 242 that supplies substrate cleaning fluid to the wafer W, and a pen sponge 2401.
  • a substrate cleaning unit 240 that supports the substrate and cleans the wafer W by bringing the pen sponge 2401 into contact with the wafer W, a cleaning tool cleaning unit 243 that cleans (self-cleans) the pen sponge 2401 with cleaning fluid, and a cleaning process and an environment sensor 244 that measures the condition of the internal space of the housing 20 where the operation is performed.
  • the pen sponge cleaning units 24C and 24D will be described below, focusing on the differences from the roll sponge cleaning units 24A and 24B.
  • the substrate holding part 241 includes a substrate holding mechanism part 241c that holds a plurality of positions on the side edge of the wafer W, and a substrate rotation mechanism part that rotates the wafer W around a third rotation axis perpendicular to the surface to be cleaned of the wafer W. 241d.
  • the substrate holding mechanism part 241c is two driven rollers, and at least one driven roller is configured to be movable in the holding direction or the separation direction with respect to the side edge of the wafer W, thereby rotating the substrate.
  • the mechanism part 241d is two drive rollers.
  • the substrate holding section 241 may be a substrate holding mechanism section 241c composed of a plurality of driven rollers and a substrate rotation mechanism section 241d composed of at least one driving roller.
  • the cleaning fluid supply unit 242 is configured in the same manner as in FIG. 4, and includes a cleaning fluid supply nozzle 242a, a rocking movement mechanism unit 242b, a vertical movement mechanism unit 242c, a flow control unit 242d, and a temperature control mechanism unit 242e. .
  • the cleaning fluid supply nozzle 242a constitutes a substrate processing fluid supply section.
  • the substrate cleaning section 240 includes a cleaning tool rotation mechanism section 240d that rotates the pen sponge 2401 around a second rotation axis perpendicular to the surface to be cleaned of the wafer W, and a vertical movement mechanism section 240e that vertically moves the pen sponge 2401. and a rocking movement mechanism 240f for rotating and moving the pen sponge 2401 in the horizontal direction.
  • the vertical movement mechanism portion 240e and the swing movement mechanism portion 240f function as a cleaning tool movement mechanism portion that moves the relative positions of the pen sponge 2401 and the surface of the wafer W to be cleaned.
  • the cleaning tool cleaning part 243 is arranged at a position not interfering with the wafer W, and accommodated in the cleaning tool cleaning tank 243e capable of storing and discharging the cleaning tool cleaning fluid, and the cleaning tool cleaning tank 243e.
  • a flow control unit 243h is provided to control the flow rate and pressure of the cleaning tool cleaning fluid discharged to the outside.
  • the environment sensor 244 includes, for example, a temperature sensor 244a and a humidity sensor 244b.
  • a camera image sensor capable of photographing the surface of the wafer W, the pen sponge 2401, etc. during the cleaning process or before and after the cleaning process may be provided.
  • the wafer W is rotated by the substrate rotating mechanism 241d while being held by the substrate holding mechanism 241c. Then, while the substrate cleaning fluid is being supplied from the cleaning fluid supply nozzle 242a to the surface to be cleaned of the wafer W, the pen sponge 2401 rotated around the axis by the cleaning tool rotation mechanism 240d is applied to the surface to be cleaned of the wafer W. The wafer W is cleaned by the sliding contact. After that, the substrate cleaning unit 240 moves the pen sponge 2401 to the cleaning tool cleaning tank 243e, for example, rotates the pen sponge 2401, presses it against the cleaning tool cleaning plate 243f, or controls the cleaning tool cleaning fluid by the flow control unit 243h. is supplied to the pen sponge 2401 to clean the pen sponge 2401 .
  • FIG. 6 is a perspective view showing an example of the first and second drying sections 24E, 24F.
  • the basic configurations and functions of the first and second drying sections 24E and 24F are common.
  • Each of the first and second drying sections 24E and 24F includes a substrate holding section 241 that holds the wafer W, a drying fluid supply section 245 that supplies the substrate drying fluid to the wafer W, and the housing 20 where the drying process is performed. and an environment sensor 244 that measures the state of the interior space.
  • the substrate holding unit 241 includes a substrate holding mechanism unit 241e that holds a plurality of positions on the side edge of the wafer W, and a substrate rotation mechanism unit that rotates the wafer W around a third rotation axis perpendicular to the surface to be cleaned of the wafer W. 241g.
  • the substrate holding mechanism part 241e is installed such that one end thereof rotates about a horizontal axis with respect to the vertical movement mechanism part 241f that moves in the vertical direction, and the other end can be brought into contact with and separated from the peripheral edge of the wafer W. It is formed in a gripping part such as a chuck.
  • the substrate holding mechanism part 241e constitutes an umbrella mechanism in which the gripping part moves in contact with the wafer W or in the separation direction as the vertical movement mechanism 241f moves in the vertical direction. Note that the gripping portion may be configured by a roller.
  • the dry fluid supply unit 245 includes a dry fluid supply nozzle 245a that supplies the substrate dry fluid to the surface to be cleaned of the wafer W, a vertical movement mechanism unit 245b that vertically moves the dry fluid supply nozzle 245a, and the dry fluid supply nozzle 245a. , a flow control unit 245d for adjusting the flow rate and pressure of the substrate drying fluid, and a temperature control mechanism unit 245e for adjusting the temperature of the substrate drying fluid.
  • the dry fluid supply nozzle 245a constitutes a substrate processing fluid supply section.
  • the vertical movement mechanism portion 245b and the rocking movement mechanism portion 245c function as a drying fluid supply nozzle movement mechanism portion that moves the relative positions of the drying fluid supply nozzle 245a and the surface of the wafer W to be cleaned.
  • the substrate drying fluid is, for example, IPA vapor and pure water (rinse liquid), and as shown in FIG. may have been Also, the substrate drying fluid may be a liquid, a two-fluid mixture of a liquid and a gas, or a solid such as dry ice.
  • the environment sensor 244 includes a temperature sensor 244a and a humidity sensor 244b.
  • a camera image sensor capable of photographing the surface of the wafer W, etc. during the drying process or before and after the drying process may be provided.
  • the wafer W is rotated by the substrate rotating mechanism 241g while being held by the substrate holding mechanism 241e. Then, the drying fluid supply nozzle 245a is moved toward the side edge of the wafer W (outside in the radial direction) while the substrate drying fluid is being supplied from the drying fluid supply nozzle 245a to the surface of the wafer W to be cleaned. After that, the wafer W is dried by being rotated at high speed by the substrate rotation mechanism section 241e.
  • modules for generating driving force such as motors and air cylinders, linear guides, ball It is configured by appropriately combining driving force transmission mechanisms such as screws, gears, belts, couplings, and bearings, and sensors such as linear sensors, encoder sensors, limit sensors, and torque sensors.
  • 4 to 6 omit specific configurations of the flow control units 243c, 243d, 243g, 243h, and 245d. It is configured by appropriately combining sensors such as a sensor, a pressure sensor, and a liquid level sensor. 4 to 6 omit the specific configuration of the temperature control mechanism units 242d and 245e, but for example, temperature control (contact or non-contact) modules such as heaters and heat exchangers, It is configured by appropriately combining sensors such as a temperature sensor and a current sensor.
  • the film thickness measurement unit 25 is a measuring device for measuring the film thickness of the wafer W before or after polishing, and is composed of, for example, an optical film thickness measuring device, an eddy current film thickness measuring device, or the like. Transfer of the wafer W to each film thickness measurement module is performed by the transfer robot 211 .
  • FIG. 7 is a diagram showing the arrangement of substrate processing fluid supply valves in the substrate processing fluid supply system. Note that FIG. 7 omits tanks, pumps, motors, and the like.
  • the polishing fluid supply system 27 supplies polishing fluid from a polishing fluid supply source 270 to the polishing fluid supply nozzle 222 .
  • one first polishing fluid supply valve 271 is arranged upstream of all the substrate processing apparatuses 2 downstream of one polishing fluid supply source 270, and one second polishing fluid supply valve 272 is arranged for one substrate.
  • One third polishing fluid supply valve 272 is arranged upstream of all polishing units 22 downstream of the processing apparatus 2, and one third polishing fluid supply valve 272 is arranged upstream of all polishing fluid supply nozzles 222 downstream of one polishing unit 22. .
  • polishing fluid is supplied from a polishing fluid supply source 270 through a first polishing fluid supply valve 271 to each of the one or more substrate processing apparatuses 2 , and then through a second polishing fluid supply valve 272 .
  • the polishing fluid is then supplied to one or more polishing units 22 , passes through the third polishing fluid supply valve 273 , is supplied to one or more polishing fluid nozzles 222 , and is discharged from the polishing fluid nozzles 222 .
  • the cleaning fluid supply system 28 supplies cleaning fluid from a cleaning fluid supply source 280 to the cleaning fluid supply nozzles 222 .
  • one first cleaning fluid supply valve 281 is arranged upstream of all the substrate processing apparatuses 2 downstream of one cleaning fluid supply source 280, and one second cleaning fluid supply valve 282 is arranged for one substrate.
  • a third cleaning fluid supply valve 282 is arranged one upstream of all cleaning units 24A-24D downstream of the processing apparatus 2, and one third cleaning fluid supply valve 282 is located one upstream of all cleaning fluid supply nozzles 242a downstream of one cleaning unit 24A-24D. are placed.
  • cleaning fluid is supplied from a cleaning fluid supply source 280 through a first cleaning fluid supply valve 281 to each of the one or more substrate processing apparatuses 2 and then through a second cleaning fluid supply valve 282 . Then, it is supplied to one or more cleaning units 22, passes through the third cleaning fluid supply valve 283, is supplied to one or more cleaning fluid nozzles 242a, and is discharged from the cleaning fluid nozzles 242a.
  • the dry fluid supply system 29 supplies dry fluid from the dry fluid supply source 290 to the dry fluid supply nozzle 222 .
  • one first drying fluid supply valve 291 is arranged upstream of all the substrate processing apparatuses 2 downstream of one drying fluid supply source 290, and one second drying fluid supply valve 292 is arranged for one substrate.
  • a third drying fluid supply valve 292 is arranged upstream of all the drying units 24E, 24F downstream of the processing apparatus 2, and a third drying fluid supply valve 292 is positioned upstream of all drying fluid supply nozzles 245a downstream of one drying unit 24E, 24F. are placed.
  • the drying fluid is supplied from the drying fluid supply source 290 through the first drying fluid supply valve 291 to each of the one or more substrate processing apparatuses 2 and then through the second drying fluid supply valve 292 . Then, it is supplied to one or more drying units 24E, 24F, passes through the third drying fluid supply valve 293, is supplied to one or more drying fluid nozzles 245a, and is discharged from the drying fluid nozzles 245a.
  • FIG. 8 is a block diagram showing an example of the substrate processing apparatus 2. As shown in FIG. The control unit 26 is electrically connected to each of the units 21 to 25 and functions as a control section that controls the units 21 to 25 in an integrated manner.
  • the control system (modules, sensors, sequencers) of the finishing unit 24 will be described below as an example, but since the other units 21 to 23 and 25 have the same basic configuration and functions, their description will be omitted.
  • the finishing unit 24 includes subunits provided in the finishing unit 24 (for example, first and second roll sponge cleaning units 24A and 24B, first and second pen sponge cleaning units 24C and 24D, first and second Drying units 24E, 24F, first and second conveying units 24G, 24H, etc.), and a plurality of modules 2471 to 247r to be controlled, and a plurality of modules 2471 to 247r, respectively.
  • a plurality of sensors 2481 to 248s for detecting data (detection values) necessary for controlling the modules 2471 to 247r, and a sequencer 249 for controlling the operations of the modules 2471 to 247r based on the detection values of the sensors 2481 to 248s. Prepare.
  • the control unit 26 includes a control section 260 , a communication section 261 , an input section 262 , an output section 263 and a storage section 264 .
  • the control unit 26 is configured by, for example, a general-purpose or dedicated computer (see FIG. 9 described later).
  • the communication unit 261 is connected to the network 7 and functions as a communication interface for transmitting and receiving various data.
  • the input unit 262 receives various input operations, and the output unit 263 functions as a user interface by outputting various information via the display screen, signal tower lighting, and buzzer sound.
  • the storage unit 264 stores various programs (operating system (OS), application programs, web browsers, etc.) and data (apparatus setting information 265, substrate recipe information 266, etc.) used in the operation of the substrate processing apparatus 2 .
  • the equipment setting information 265 and substrate recipe information 266 are data that can be edited by the user via the display screen.
  • the control unit 260 controls a plurality of sensors 2181 to 218q, 2281 to 228s, 2381 to 238u, 2481 to 248w, 2581 through a plurality of sequencers 219, 229, 239, 249, and 259 (hereinafter referred to as "sequencer group”).
  • 258y hereinafter referred to as “sensor group”
  • module group a plurality of modules 2171-217p, 2271-227r, 2371-237t, 2471-247v, and 2571-257x.
  • a series of substrate processing such as loading, polishing, cleaning, drying, film thickness measurement, and unloading are performed by operating in conjunction with each other.
  • FIG. 9 is a hardware configuration diagram showing an example of a computer 900. As shown in FIG.
  • Each of the control unit 26 of the substrate processing apparatus 2, the database device 3, the machine learning device 4, the information processing device 5, and the user terminal device 6 is configured by a general-purpose or dedicated computer 900.
  • the computer 900 includes, as its main components, a bus 910, a processor 912, a memory 914, an input device 916, an output device 917, a display device 918, a storage device 920, a communication I/F (interface). It has a section 922 , an external equipment I/F section 924 , an I/O (input/output) device I/F section 926 and a media input/output section 928 . Note that the above components may be omitted as appropriate depending on the application for which the computer 900 is used.
  • the processor 912 is composed of one or more arithmetic processing units (CPU (Central Processing Unit), MPU (Micro-processing unit), DSP (digital signal processor), GPU (Graphics Processing Unit), etc.), and the entire computer 900 It operates as a control unit that supervises the
  • the memory 914 stores various data and programs 930, and is composed of, for example, a volatile memory (DRAM, SRAM, etc.) functioning as a main memory, a non-volatile memory (ROM), a flash memory, and the like.
  • the input device 916 is composed of, for example, a keyboard, mouse, numeric keypad, electronic pen, etc., and functions as an input unit.
  • the output device 917 is configured by, for example, a sound (voice) output device, a vibration device, or the like, and functions as an output unit.
  • a display device 918 is configured by, for example, a liquid crystal display, an organic EL display, electronic paper, a projector, or the like, and functions as an output unit.
  • the input device 916 and the display device 918 may be configured integrally like a touch panel display.
  • the storage device 920 is composed of, for example, an HDD, SSD (Solid State Drive), etc., and functions as a storage unit.
  • the storage device 920 stores various data necessary for executing the operating system and programs 930 .
  • the communication I/F unit 922 is connected to a network 940 (which may be the same as the network 7 in FIG. 1) such as the Internet or an intranet by wire or wirelessly, and exchanges data with other computers according to a predetermined communication standard. functions as a communication unit that transmits and receives.
  • the external device I/F unit 924 is connected to the external device 950 such as a camera, printer, scanner, reader/writer, etc. by wire or wirelessly, and serves as a communication unit that transmits and receives data to and from the external device 950 according to a predetermined communication standard. Function.
  • the I/O device I/F unit 926 is connected to I/O devices 960 such as various sensors and actuators, and exchanges with the I/O devices 960, for example, detection signals from sensors and control signals to actuators. functions as a communication unit that transmits and receives various signals and data.
  • the media input/output unit 928 is composed of, for example, a drive device such as a DVD drive and a CD drive, and reads and writes data from/to media (non-temporary storage media) 970 such as DVDs and CDs.
  • the processor 912 calls the program 930 stored in the storage device 920 to the memory 914 and executes it, and controls each part of the computer 900 via the bus 910 .
  • the program 930 may be stored in the memory 914 instead of the storage device 920 .
  • the program 930 may be recorded on the media 970 in an installable file format or executable file format and provided to the computer 900 via the media input/output unit 928 .
  • Program 930 may be provided to computer 900 by downloading via network 940 via communication I/F section 922 .
  • the computer 900 may implement various functions realized by the processor 912 executing the program 930 by hardware such as FPGA and ASIC, for example.
  • the computer 900 is, for example, a stationary computer or a portable computer, and is an arbitrary form of electronic equipment.
  • the computer 900 may be a client-type computer, a server-type computer, or a cloud-type computer.
  • the computer 900 may be applied to devices other than the devices 2-6.
  • FIG. 10 is a data configuration diagram showing an example of production history information 30 managed by the database device 3.
  • the production history information 30 includes, for example, a wafer history table 300 for each wafer W, polishing processing and finishing processing as a table in which reports R obtained when substrate processing for main production is performed are classified and registered. and a substrate processing fluid supply history table 301 relating to apparatus status information in substrate processing fluid supply, including It should be noted that the substrate processing fluid supply history table 301 includes a substrate processing fluid supply history table relating to apparatus status information in substrate processing fluid supply.
  • the production history information 30 includes an event history table related to event information and an operation history table related to operation information, etc., but detailed description thereof will be omitted.
  • Each record of the wafer history table 300 registers, for example, a wafer ID, cassette number, slot number, start time and end time of each process, used unit ID, and the like.
  • FIG. 10 exemplifies the polishing process, the cleaning process, and the drying process, other processes are similarly registered.
  • Each record of the substrate processing fluid supply history table 301 includes, for example, a wafer ID, supply flow rate information of the substrate processing fluid supplied from the substrate processing fluid supply units 222, 242a, and 245a, substrate processing fluid supply units 222, 242a, and 245a. supply pressure information of the substrate processing fluid supplied from the substrate processing fluid supply valves 271 to 273, 281 to 283, and 291 to 293 for adjusting the flow rate of the substrate processing fluid; Information such as the pressure on the primary side of the substrate processing fluid supply valves 271 to 273, 281 to 283, and 291 to 293 for adjusting the flow rate is registered.
  • the substrate processing fluid supply flow rate information is information indicating the flow rate of the substrate processing fluid supplied from the substrate processing fluid supply units 222, 242a, and 245a in the fluid supply processing.
  • the substrate processing fluid supply flow rate information is the substrate processing fluid supplied to the wafer W from the polishing fluid supply nozzle 222 in the polishing process, the cleaning fluid supply nozzle 242a in the cleaning process, or the drying process drying fluid supply nozzle 245a in the drying process. It is a detection value of a sensor that measures the flow rate, or the like.
  • the substrate processing fluid supply pressure information is information indicating the pressure of the substrate processing fluid supplied from the substrate processing fluid supply units 222, 242a, and 245a in the fluid supply processing.
  • the substrate processing fluid supply pressure information is the substrate processing fluid supplied to the wafer W from the polishing fluid supply nozzle 222 in the polishing process, the cleaning fluid supply nozzle 242a in the cleaning process, or the drying process drying fluid supply nozzle 245a in the drying process. It is a detection value of a sensor that measures pressure, or the like.
  • the substrate processing fluid supply valve state information is information indicating the state of the substrate processing fluid supply valves 271 to 273, 281 to 283, and 291 to 293 that adjust the flow rate of the substrate processing fluid.
  • the substrate processing fluid supply valve state information is stored in the substrate processing fluid supply system that supplies the fluid to the polishing fluid supply nozzle 222, the cleaning fluid supply nozzle 242a, or the drying fluid supply nozzle 245a.
  • the states of the polishing fluid supply valves 271 to 273, the cleaning fluid supply valves 281 to 283, or the drying fluid supply valves 291 to 293 that are connected upstream of the drying fluid supply nozzle 245a and adjust the flow rate of the substrate processing fluid are measured. It is the detection value of the sensor that does.
  • the substrate processing fluid supply valve state information includes, for example, substrate processing fluid supply valve opening state information indicating opening degrees of the substrate processing fluid supply valves 271 to 273, 281 to 283, and 291 to 293, and substrate processing fluid supply valve 271. 273, 281-283, and 291-293.
  • the substrate processing fluid supply valve primary side pressure information is information indicating the primary side pressure of the substrate processing fluid supply valves 271 to 273, 281 to 283, and 291 to 293 that adjust the flow rate of the substrate processing fluid.
  • the information on the primary side pressure of the substrate processing fluid supply valve is used in the substrate processing fluid supply system for supplying the fluid to the polishing fluid supply nozzle 222, the cleaning fluid supply nozzle 242a, or the drying fluid supply nozzle 245a.
  • time-series data of each sensor is obtained as the state of the substrate processing apparatus 2 when the substrate processing fluid is supplied to the wafer W specified by the wafer ID. (or time-series data of each module) can be extracted.
  • FIG. 11 is a data configuration diagram showing an example of the substrate processing fluid supply test information 31 managed by the database device 3.
  • the substrate processing fluid supply test information 31 is a report R obtained when the substrate processing fluid supply test is performed using the test substrate processing fluid supply units 222, 242a, and 245a and the substrate processing fluid supply test apparatus, and the test results.
  • a substrate processing fluid supply test table 310 is provided in which the results are sorted and registered.
  • Each record of the substrate processing fluid supply test table 310 includes, for example, a test ID, substrate processing fluid supply flow rate information, substrate processing fluid supply pressure information, substrate processing fluid supply valve state information, substrate processing fluid supply valve primary side pressure information, Test result information and the like are registered.
  • the substrate processing fluid supply flow rate information, the substrate processing fluid supply pressure information, the substrate processing fluid supply valve state information, and the substrate processing fluid supply valve primary side pressure information in the substrate processing fluid supply test table 310 are used for each part in the substrate processing fluid supply test. , and its data structure is the same as that of the substrate processing fluid supply history table 301, so detailed description thereof will be omitted.
  • the test result information is information indicating the substrate processing fluid supply position when the substrate processing fluid is supplied in the substrate processing fluid supply test.
  • the test result information is measured values sampled at predetermined time intervals by a substrate processing fluid supply position measuring device using a substrate processing fluid supply unit for testing or a substrate processing fluid supply testing device.
  • the test result information shown in FIG. 11 indicates that the supply of the substrate processing fluid at each time t1, t2, . . . , tm, . It contains the position measurement TR1.
  • the substrate processing fluid supply position can be measured, for example, by supplying the fluid from a test substrate processing fluid supply unit to a dummy polishing table or dummy wafer whose coordinates are set in advance, and measuring the dropping position.
  • a reference position may be determined in advance, and the amount of change from the reference position may be measured.
  • the substrate processing fluid supply unit is a vertical dropping type in which the substrate processing fluid drops vertically, a horizontal injection type in which the substrate processing fluid is ejected horizontally, and an angle adjustment injection type in which the substrate processing fluid is ejected by adjusting the angle.
  • the test result information may be a measured value obtained by a substrate processing fluid supply position measuring device as described above, or may be a substrate processing fluid supplied by a camera mounted on an optical microscope or a scanning electron microscope (SEM). It may be based on the results of image processing in which positions are photographed at predetermined time intervals and image processing is performed on each of the photographed images, or the results of experimental analysis conducted by an experimenter.
  • the test result information may be collected in one substrate processing fluid supply test in which the supply of the substrate processing fluid is continuously performed from the start to the end of the substrate processing fluid supply. By repeating the substrate processing fluid supply test from the start until reaching the predetermined time while gradually lengthening the predetermined time, the substrate processing fluid supply test may be collected a plurality of times.
  • the substrate processing fluid supply when the fluid supply processing is performed using the test substrate processing fluid supply unit in the substrate processing fluid supply test specified by the test ID can be extracted.
  • FIG. 12 is a block diagram showing an example of the machine learning device 4 according to the first embodiment.
  • the machine learning device 4 includes a control unit 40 , a communication unit 41 , a learning data storage unit 42 and a trained model storage unit 43 .
  • the control unit 40 functions as a learning data acquisition unit 400 and a machine learning unit 401.
  • the communication unit 41 is connected to external devices (for example, the substrate processing device 2, the database device 3, the information processing device 5, the user terminal device 6, the substrate processing fluid supply test device (not shown), etc.) via the network 7. and functions as a communication interface for sending and receiving various data.
  • the learning data acquisition unit 400 is connected to an external device via the communication unit 41 and the network 7, and is composed of substrate processing fluid supply information as input data and substrate processing fluid supply position information as output data. 1 of learning data 11A is obtained.
  • the first learning data 11A is data used as teacher data (training data), verification data, and test data in supervised learning. Further, the substrate processing fluid supply position information is data used as a correct label in supervised learning.
  • the learning data storage unit 42 is a database that stores a plurality of sets of the first learning data 11A acquired by the learning data acquisition unit 400. Note that the specific configuration of the database that constitutes the learning data storage unit 42 may be appropriately designed.
  • the machine learning unit 401 performs machine learning using multiple sets of first learning data 11A stored in the learning data storage unit 42 . That is, the machine learning unit 401 inputs a plurality of sets of first learning data 11A to the first learning model 10A, and determines the substrate processing fluid supply information and the substrate processing fluid supply position state included in the first learning data 11A. By having the first learning model 10A learn the correlation with the information, the learned first learning model 10A is generated.
  • the trained model storage unit 43 is a database that stores the trained first learning model 10A (specifically, the adjusted weight parameter group) generated by the machine learning unit 401.
  • the learned first learning model 10A stored in the learned model storage unit 43 is provided to the actual system (for example, the information processing device 5) via the network 7, a recording medium, or the like.
  • the learning data storage unit 42 and the trained model storage unit 43 are shown as separate storage units in FIG. 12, they may be configured as a single storage unit.
  • the number of first learning models 10A stored in the learned model storage unit 43 is not limited to one.
  • a plurality of learning models with different conditions such as differences in the mechanisms of the fluid supply units 222, 242a, and 245a, types of data included in the substrate processing fluid supply information, and types of data included in the substrate processing fluid supply position information. may be stored.
  • the learning data storage unit 42 may store a plurality of types of learning data having data configurations respectively corresponding to a plurality of learning models with different conditions.
  • FIG. 13 is a diagram showing an example of the first learning model 10A and the first learning data 11A.
  • the first learning data 11A used for machine learning of the first learning model 10A is composed of substrate processing fluid supply information and substrate processing fluid supply position information.
  • the first learning model 10A and the first learning data 11A correspond to the roll sponge cleaning units 24A and 24B using the roll sponge 2400 and the pen sponge cleaning unit using the pen sponge 2401. At least three types, one corresponding to 24C and 24D and one corresponding to drying units 24E and 24F, are prepared.
  • the substrate processing fluid supply information constituting the first learning data 11A includes substrate processing fluid supply flow rate information indicating the flow rate of the substrate processing fluid supplied from the substrate processing fluid supply units 222, 242a, and 245a, and substrate processing fluid supply information. It includes substrate processing fluid supply pressure information indicating the pressure of the substrate processing fluid supplied from the supply units 222, 242a, and 245a.
  • the substrate processing fluid supply flow rate information included in the substrate processing fluid supply information is information indicating the flow rate of the substrate processing fluid supplied from the substrate processing fluid supply units 222, 242a, and 245a in supplying the substrate processing fluid.
  • the substrate processing fluid supply flow rate information is the substrate processing fluid supplied to the wafer W from the polishing fluid supply nozzle 222 in the polishing process, the cleaning fluid supply nozzle 242a in the cleaning process, or the drying process drying fluid supply nozzle 245a in the drying process. Flow rate is fine.
  • the substrate processing fluid supply pressure information included in the substrate processing fluid supply information is information indicating the pressure of the substrate processing fluid supplied from the substrate processing fluid supply units 222, 242a, and 245a in supplying the substrate processing fluid.
  • the substrate processing fluid supply pressure information is the substrate processing fluid supplied to the wafer W from the polishing fluid supply nozzle 222 in the polishing process, the cleaning fluid supply nozzle 242a in the cleaning process, or the drying process drying fluid supply nozzle 245a in the drying process. pressure is fine.
  • the substrate processing fluid supply valve state information included in the substrate processing fluid supply information is information indicating the states of the substrate processing fluid supply valves 271 to 273, 281 to 283, and 291 to 293 that adjust the flow rate of the substrate processing fluid.
  • the substrate processing fluid supply valve state information is stored in the substrate processing fluid supply system that supplies the fluid to the polishing fluid supply nozzle 222, the cleaning fluid supply nozzle 242a, or the drying fluid supply nozzle 245a.
  • the polishing fluid supply valves 271 to 273, the cleaning fluid supply valves 281 to 283, or the drying fluid supply valves 291 to 293, which are connected upstream of the drying fluid supply nozzle 245a and adjust the flow rate of the substrate processing fluid may be used. .
  • the substrate processing fluid supply valve state information includes, for example, substrate processing fluid supply valve opening state information indicating opening degrees of the substrate processing fluid supply valves 271 to 273, 281 to 283, and 291 to 293, and substrate processing fluid supply valve state information. at least one of substrate processing supply valve on-off state information indicating the on-off state of the valves 271-273, 281-283, 291-293.
  • the substrate processing fluid supply valve primary side pressure information included in the substrate processing fluid supply information indicates the pressure on the primary side of the substrate processing fluid supply valves 271 to 273, 281 to 283, and 291 to 293 that adjust the flow rate of the substrate processing fluid. Information.
  • the substrate processing fluid supply valve primary side pressure information is connected upstream of the cleaning fluid supply nozzle 242a or the drying fluid supply nozzle 245a in the substrate processing fluid supply system that supplies fluid to the cleaning fluid supply nozzle 242a or the drying fluid supply nozzle 245a. It may be the pressure on the primary side of the cleaning fluid supply valves 281-283 or the drying fluid supply valves 291-293 that regulate the flow rate of the processing fluid.
  • the substrate processing fluid supply information may further include apparatus internal environment information indicating the environment of the space where the substrate processing fluid is supplied. At least one of temperature and humidity of the formed internal space is included. Further, the substrate processing fluid supply information may further include processing performance information indicating the substrate processing fluid supply performance. At least one of the cumulative number of used wafers W and the cumulative usage time when the substrate processing fluid supply units 222, 242a, and 245a are used to supply the substrate processing fluid after the replacement of the 242a and 245a. include.
  • the substrate processing fluid supply position information constituting the first learning data 11A is supplied from the substrate processing fluid supply units 222, 242a, and 245a when the substrate processing apparatus 2 operates in the operating state indicated by the substrate processing fluid supply information. This is information indicating the supply position of the fluid to be applied.
  • the substrate processing fluid supply position information includes:
  • the learning data acquisition unit 400 acquires the first learning data 11A by referring to the substrate processing fluid supply test information 31 and accepting user input operations through the user terminal device 6 as necessary.
  • the learning data acquisition unit 400 refers to the substrate processing fluid supply test table 310 of the substrate processing fluid supply test information 31 to obtain substrate processing data when the substrate processing fluid supply test specified by the test ID is performed.
  • Fluid supply flow rate information, substrate processing fluid supply pressure information, substrate processing fluid supply valve state information, and substrate processing fluid supply valve primary side pressure information are acquired as substrate processing fluid supply information.
  • the substrate processing fluid supply information is obtained as time-series data of the sensor group as shown in FIG. It may be changed as appropriate.
  • a command value to the module may be used, a parameter converted from the detected value of the sensor or the command value to the module may be used, or the detected value of a plurality of sensors may be used. You may use the parameter calculated based on.
  • the substrate processing fluid supply information may be acquired as time-series data for the entire supply period of the substrate processing fluid, or may be acquired as time-series data for a target period that is part of the supply period for the substrate processing fluid. Alternatively, it may be obtained as point-in-time data at a specific target point in time.
  • the data configuration of the input data in the first learning model 10A and the first learning data 11A may be changed as appropriate.
  • the learning data acquisition unit 400 refers to the substrate processing fluid supply test table 310 of the substrate processing fluid supply test information 31 to determine whether the substrate processing fluid supply test specified by the same test ID is performed.
  • Test result information time series data of the substrate processing fluid supply position measuring device (FIG. 11)
  • the substrate processing fluid supply position measuring device is a measuring device capable of planar measurement with respect to the substrate processing fluid supply units 222, 242a, and 245a
  • the learning data acquisition unit 400 obtains planar measurement values. is acquired as substrate processing fluid supply position information.
  • the substrate processing fluid supply position information is as shown in FIG. 13 . It may also include the position provided. Further, the substrate processing fluid supply position information may be calculated by substituting the measured value of the substrate processing fluid supply position measuring device into a predetermined calculation formula. Furthermore, when the substrate processing fluid supply information is acquired as, for example, time-series data of the entire substrate processing fluid supply period or time-series data of a target period that is a part of the substrate processing fluid supply period, the substrate processing fluid The supply position information may be acquired as time-series data for the entire substrate processing fluid supply period or time-series data for the target period, or may be acquired as point-in-time data at the end of supply of the substrate-processing fluid or point-in-time data at the target point.
  • the substrate processing fluid supply position information may be acquired as point-in-time data at the specific target point in time.
  • the data structure of the output data in the first learning model 10A and the first learning data 11A may be changed as appropriate.
  • the first learning model 10A employs, for example, a neural network structure, and includes an input layer 100, an intermediate layer 101, and an output layer 102.
  • a synapse (not shown) connecting each neuron is provided between each layer, and a weight is associated with each synapse.
  • a set of weight parameters consisting of the weight of each synapse is adjusted by machine learning.
  • the input layer 100 has a number of neurons corresponding to the substrate processing fluid supply information as input data, and each value of the substrate processing fluid supply information is input to each neuron.
  • the output layer 102 has a number of neurons corresponding to the substrate processing fluid supply position information as output data, and the prediction result (inference result) of the substrate processing fluid supply position information for the substrate processing fluid supply information is output as output data. be done.
  • the value output to each neuron in the output layer as the inference result is compared with the teacher data value corresponding to each output data included in the learning data to obtain the error, and the error is minimized. Then, a process (back promotion) is performed to adjust the weight associated with each synapse.
  • a predetermined learning end condition such as repeating the above series of steps a predetermined number of times, or the error is smaller than the allowable value
  • the machine learning is terminated and the learned neural It is generated as a network model (all weights associated with each of the synapses).
  • FIG. 14 is a flow chart showing an example of a machine learning method by the machine learning device 4. As shown in FIG.
  • step S100 the learning data acquisition unit 400 acquires a desired number of first learning data 11A from the substrate processing fluid supply test information 31 or the like as preparation for starting machine learning.
  • the acquired first learning data 11A is stored in the learning data storage unit 42 .
  • the number of first learning data 11A prepared here may be set in consideration of the inference accuracy required for the finally obtained first learning model 10A.
  • step S110 the machine learning unit 401 prepares the first learning model 10A before learning to start machine learning.
  • the first learning model 10A before learning prepared here is composed of a neural network model, and the weight of each synapse is set to an initial value.
  • step S120 the machine learning unit 401, for example, randomly selects one set of first learning data 11A from the plurality of sets of first learning data 11A stored in the learning data storage unit 42. get.
  • step S130 the machine learning unit 401 converts the substrate processing fluid supply information (input data) included in the set of first learning data 11A into the prepared first pre-learning (or during learning) pre-learning data. input to the input layer 100 of the learning model 10A.
  • substrate processing fluid supply position information (output data) is output as an inference result from the output layer 102 of the first learning model 10A. It is generated by model 10A. Therefore, in the state before (or during) learning, the output data output as the inference result indicates information different from the substrate processing fluid supply position information (correct label) included in the first learning data 11A.
  • step S140 the machine learning unit 401 extracts the substrate processing fluid supply position information (correct label) included in the set of first learning data 11A acquired in step S120, and from the output layer in step S130.
  • Machine learning is performed by comparing substrate processing fluid supply position information (output data) output as a result of inference and adjusting the weight of each synapse (back promotion).
  • the machine learning unit 401 causes the first learning model 10A to learn the correlation between the substrate processing fluid supply information and the substrate processing fluid supply position information.
  • step S150 the machine learning unit 401 determines whether or not a predetermined learning end condition is satisfied, for example, the substrate processing fluid supply position information (correct label) included in the first learning data 11A, Determination based on the evaluation value of the error function based on the state information (output data) output as the inference result and the remaining number of unlearned first learning data 11A stored in the learning data storage unit 42 do.
  • a predetermined learning end condition for example, the substrate processing fluid supply position information (correct label) included in the first learning data 11A, Determination based on the evaluation value of the error function based on the state information (output data) output as the inference result and the remaining number of unlearned first learning data 11A stored in the learning data storage unit 42 do.
  • step S150 when the machine learning unit 401 determines that the learning end condition is not satisfied and continues the machine learning (No in step S150), the process returns to step S120, and the first learning model 10A under learning In contrast, steps S120 to S140 are performed multiple times using the unlearned first learning data 11A.
  • step S150 when the machine learning unit 401 determines in step S150 that the learning end condition is satisfied and machine learning ends (Yes in step S150), the process proceeds to step S160.
  • step S160 the machine learning unit 401 stores the learned first learning model 10A (adjusted weight parameter group) generated by adjusting the weight associated with each synapse as a learned model. It is stored in the unit 43, and the series of machine learning methods shown in FIG. 14 is finished.
  • step S100 corresponds to a learning data storage step
  • steps S110 to S150 correspond to a machine learning step
  • step S160 corresponds to a learned model storage step.
  • substrate processing fluid supply flow rate information As described above, according to the machine learning device 4 and the machine learning method according to the present embodiment, substrate processing fluid supply flow rate information, substrate processing fluid supply pressure information, substrate processing fluid supply valve state information, and substrate processing fluid supply It is possible to provide a first learning model 10A capable of predicting (inferring) substrate processing fluid supply position information indicating the substrate processing fluid supply position from substrate processing fluid supply information including valve primary side pressure information. can.
  • FIG. 15 is a block diagram showing an example of the information processing device 5 according to the first embodiment.
  • FIG. 16 is a functional explanatory diagram showing an example of the information processing device 5 according to the first embodiment.
  • the information processing device 5 includes a control unit 50 , a communication unit 51 and a trained model storage unit 52 .
  • the control unit 50 functions as an information acquisition unit 500 , a state prediction unit 501 and an output processing unit 502 .
  • the communication unit 51 is connected to an external device (for example, the substrate processing device 2, the database device 3, the machine learning device 4, the user terminal device 6, etc.) via the network 7, and serves as a communication interface for transmitting and receiving various data. Function.
  • the information acquisition unit 500 is connected to an external device via the communication unit 51 and the network 7, and obtains substrate processing fluid supply flow rate information, substrate processing fluid supply pressure information, substrate processing fluid supply valve state information, and substrate processing fluid supply valve.
  • substrate processing fluid supply information including primary side pressure information
  • the information acquiring unit 500 acquires the substrate processing fluid supply position of the production history information 30 .
  • the history table 301 substrate processing fluid supply flow rate information, substrate processing fluid supply pressure information, substrate processing fluid supply valve state information, and substrate processing fluid supply valve state information when the substrate processing fluid is supplied to the wafer W.
  • Substrate processing fluid supply valve primary side pressure information is acquired as substrate processing fluid supply information.
  • the information acquisition unit 500 supplies the substrate processing fluid.
  • substrate processing fluid supply flow rate information and substrate processing fluid supply pressure information are acquired as substrate processing fluid supply information at any time.
  • the information acquisition unit 500 selects the substrate processing apparatus to which the substrate processing fluid is to be supplied. 2, and by simulating the apparatus state information when the substrate processing apparatus 2 operates according to the substrate recipe conditions 266, the substrate processing fluid is supplied to the wafer W.
  • Substrate processing fluid supply flow rate information, substrate processing fluid supply pressure information, substrate processing fluid supply valve state information, and substrate processing fluid supply valve primary side pressure information are acquired as substrate processing fluid supply information.
  • the state prediction unit 501 predicts the state indicated by the substrate processing fluid supply information. Then, substrate processing fluid supply position information indicating the states of the substrate processing fluid supply units 222, 242a, and 245a when the substrate processing apparatus 2 operates is predicted.
  • the learned model storage unit 52 is a database that stores the learned first learning model 10A used in the state prediction unit 501. Note that the number of first learning models 10A stored in the learned model storage unit 52 is not limited to one. A plurality of learned models with different conditions, such as differences in the mechanisms of the fluid supply units 222, 242a, and 245a, the types of data included in the substrate processing fluid supply information, and the types of data included in the substrate processing fluid supply position information. may be stored and selectively available.
  • the trained model storage unit 52 may be replaced by a storage unit of an external computer (for example, a server computer or a cloud computer), in which case the state prediction unit 501 may access the external computer. .
  • the output processing unit 502 performs output processing for outputting the substrate processing fluid supply position information generated by the state prediction unit 501 .
  • the output processing unit 502 may transmit the substrate processing fluid supply position information to the user terminal device 6 so that a display screen based on the substrate processing fluid supply position information may be displayed on the user terminal device 6,
  • the substrate processing fluid supply position information may be registered in the production history information 30 by transmitting the substrate processing fluid supply position information to the database device 3 .
  • FIG. 17 is a flowchart showing an example of an information processing method by the information processing device 5. As shown in FIG. An operation example in which the user operates the user terminal device 6 to perform "post-prediction processing" of substrate processing fluid supply position information for a specific wafer W will be described below.
  • step S200 when the user performs an input operation for inputting a wafer ID specifying a wafer W to be predicted to the user terminal device 6, the user terminal device 6 sends the wafer ID to the information processing device 5. Send to
  • step S210 the information acquisition unit 500 of the information processing device 5 receives the wafer ID transmitted in step S200.
  • the information acquisition unit 500 refers to the fluid supply history table 301 of the production history information 30 using the wafer ID received in step S210, thereby supplying the fluid to the wafer W specified by the wafer ID.
  • Substrate processing fluid supply information is obtained when processing is performed.
  • step S220 the state prediction unit 501 inputs the substrate processing fluid supply information acquired in step S211 to the first learning model 10A as input data, thereby performing substrate processing with respect to the substrate processing fluid supply information.
  • Fluid supply position information is generated as output data to predict the substrate processing fluid supply position.
  • step S230 the output processing unit 502 transmits the substrate processing fluid supply position information to the user terminal device 6 as output processing for outputting the substrate processing fluid supply position information generated in step S220.
  • the destination of the substrate processing fluid supply position information may be the database device 3 in addition to or instead of the user terminal device 6 .
  • step S240 upon receiving the substrate processing fluid supply position information transmitted in step S230 as a response to the transmission processing in step S200, the user terminal device 6 displays based on the substrate processing fluid supply position information. By displaying the screen, the user can visually recognize the substrate processing fluid supply position information.
  • steps S210 and S211 correspond to the information acquisition step
  • step S220 corresponds to the state prediction step
  • step S230 corresponds to the output processing step.
  • substrate processing fluid supply flow rate information, substrate processing fluid supply pressure information, substrate processing fluid supply valve state information, and substrate processing fluid supply valve state information in the fluid supply process are predicted. Accordingly, the processing fluid supply position can be appropriately predicted.
  • the second embodiment is different from the first embodiment in that the substrate processing fluid supply position information is substrate processing fluid supply portion position/direction information indicating the fluid ejection positions and fluid ejection directions of the substrate processing fluid supply portions 222, 242a, and 245a. It differs from the embodiment.
  • the machine learning device 4a and the information processing device 5a according to the second embodiment will be described, focusing on the differences from the first embodiment.
  • FIG. 18 is a block diagram showing an example of a machine learning device 4a according to the second embodiment.
  • FIG. 19 is a diagram showing an example of the second learning model 10B and the second learning data 11B.
  • the second learning data 11B is used for machine learning of the second learning model 10B.
  • the substrate processing fluid supply position information constituting the second learning data 11B is substrate processing fluid supply portion position/direction information indicating the positions and directions of the substrate processing fluid supply portions 222, 242a, and 245a.
  • the positions and directions of the substrate processing fluid supply portions 222, 242a, 245a are determined, for example, by the three-dimensional positions and three-dimensional directions of the substrate processing fluid supply portions 222, 242a, 245a.
  • the substrate processing fluid supply information forming the second learning data 11B is the same as in the first embodiment, so the description is omitted.
  • Measurement of the supply position and supply direction of the substrate processing fluid is performed, for example, by supplying the fluid from a substrate processing fluid supply unit such as a test nozzle in a dummy space in which three-dimensional coordinates are set in advance, and determining the optimum value of the dummy polishing table or dummy wafer. It is only necessary to measure the supply position and the supply direction when the liquid is dropped at a specific position.
  • the ejection position and ejection direction of the fluid may be measured.
  • the direction of the center line of the ejection port may be represented by a three-dimensional angle or the like.
  • the position where the cross section of the ejection port and the center line intersect may be set as the reference position, and the direction of the center line of the ejection port may be set as the reference direction, and the amount of change in the three-dimensional direction from the reference position and the reference direction may be measured. .
  • the substrate processing fluid supply unit is a vertical dropping type in which the substrate processing fluid drops vertically, a horizontal injection type in which the substrate processing fluid is ejected horizontally, and an angle adjustment injection type in which the substrate processing fluid is ejected by adjusting the angle.
  • the learning data acquisition unit 400 acquires the second learning data 11B by referring to the substrate processing fluid supply test information 31 and accepting user input operations through the user terminal device 6 as necessary.
  • the substrate processing fluid supply test information 31 includes, for example, the substrate processing fluid supply unit 222 , the substrate processing fluid supply unit 222 , the substrate processing fluid supply unit 222 , the substrate processing fluid supply unit 222 , the substrate processing fluid supply unit 222 , the substrate processing fluid supply unit 222 , the substrate processing fluid supply unit 222 , the substrate processing fluid supply unit 222 , the substrate processing fluid supply unit 222 , the substrate processing fluid supply unit 222 , The ejection positions and ejection directions of the ejection ports 242a and 245a are registered as test result information. Then, the learning data acquisition unit 400 acquires test result information when the substrate processing fluid supply test specified by the test ID is performed from the finishing substrate processing fluid supply test table 310 of the substrate processing fluid supply test information 31. Thus, substrate processing fluid supply position information is obtained.
  • the machine learning unit 401 inputs a plurality of sets of second learning data 11B to the second learning model 10B, and compares substrate processing fluid supply information and substrate processing fluid supply position information included in the second learning data 11B. By making the second learning model 10B learn the correlation, the learned second learning model 10B is generated.
  • FIG. 20 is a block diagram showing an example of an information processing device 5a functioning as the information processing device 5a according to the second embodiment.
  • FIG. 21 is a functional explanatory diagram showing an example of the information processing device 5a according to the second embodiment.
  • the information acquisition unit 500 includes substrate processing fluid supply flow rate information, substrate processing fluid supply pressure information, substrate processing fluid supply valve state information, and substrate processing fluid supply valve primary side pressure information. Obtain substrate processing fluid supply information.
  • the state prediction unit 501 predicts the operating state indicated by the substrate processing fluid supply information.
  • the three-dimensional positions and three-dimensional directions of the substrate processing fluid supply units 222, 242a, and 245a when the substrate processing apparatus 2 operates are predicted as substrate processing fluid supply position direction information.
  • the substrate processing fluid supply information including the substrate processing fluid supply valve primary side pressure information is input to the second learning model 10B, whereby the substrate processing fluid supply position direction information for the substrate processing fluid supply information is predicted. Therefore, the positions and directions of the ejection ports of the substrate processing fluid supply units 222, 242a, and 245a can be appropriately predicted according to the supply state of the substrate processing apparatus 2.
  • the database device 3, the machine learning device 4, and the information processing device 5 are described as being composed of separate devices, but these three devices may be composed of a single device. However, any two of the three devices may be configured as a single device. At least one of the machine learning device 4 and the information processing device 5 may be incorporated in the control unit 26 of the substrate processing apparatus 2 or the user terminal device 6 .
  • the substrate processing apparatus 2 has been described as having the respective units 21 to 25, but the substrate processing apparatus 2 has a function of supplying polishing processing fluid to the wafer W when the polishing unit 22 performs polishing processing. , a function of supplying the cleaning fluid to the wafer W when performing the cleaning process of the finishing unit 24, and a function of supplying the processing fluid to the wafer W when performing the drying process of the finishing unit 24. other units may be omitted.
  • machine learning models include, for example, tree types such as decision trees and regression trees, ensemble learning such as bagging and boosting, recurrent neural networks, convolutional neural networks, and neural network types such as LSTM (including deep learning ), hierarchical clustering, non-hierarchical clustering, k-nearest neighbor method, k-means method and other clustering types, principal component analysis, factor analysis, logistic regression and other multivariate analyzes, and support vector machines.
  • the test result information is information indicating the substrate processing fluid supply position when the substrate processing fluid is supplied in the substrate processing fluid supply test using the dummy polishing table or the dummy wafer in the test apparatus.
  • the continuously acquired test result information is continuously learned by the machine learning device 4 .
  • test result information may be continuously obtained in the polishing unit 22 and the finishing unit 24 in which no sensor is installed, by manually determining the substrate processing fluid supply position and labeling the data.
  • information continuously acquired using the actual polishing unit 22 and finishing unit 24 may be uploaded to the cloud, machine-learned in the cloud, and then the learned model may be deployed to the substrate processing apparatus 2.
  • the processing method may be learned within the substrate processing apparatus 2 without uploading to the cloud.
  • the present invention is provided in the form of a program (machine learning program) that causes the computer 900 to function as each part of the machine learning device 4, and a program (machine learning program) that causes the computer 900 to execute each step of the machine learning method.
  • a program information processing program
  • the present invention provides a program (information processing program) for causing the computer 900 to function as each unit provided in the information processing apparatus 5, and a program for causing the computer 900 to execute each step provided in the information processing method according to the above embodiment. It can also be provided in the form of (information processing program).
  • the present invention can be applied not only to the aspect of the information processing apparatus 5 (information processing method or information processing program) according to the above-described embodiment, but also to an inference apparatus (inference method or inference method) used for inferring substrate processing fluid supply position information. program).
  • the inference device may include a memory and a processor, and the processor of these may execute a series of processes.
  • the series of processes includes information acquisition processing (information acquisition step) for acquiring substrate processing fluid supply information, and substrate processing fluid indicated by the substrate processing fluid supply information acquired in the information acquisition processing.
  • an inference device inference method or inference program
  • it can be applied to various devices more easily than when the information processing device 5 is implemented.
  • the inference device inference method or inference program
  • the machine learning device 4 and the learned model generated by the machine learning method according to the above embodiment are used to generate a state prediction unit
  • the reasoning techniques implemented by 501 may also be applied.
  • the present invention can be used for information processing devices, inference devices, machine learning devices, information processing methods, inference methods, and machine learning methods.
  • SYMBOLS 1 Substrate processing system, 2... Substrate processing apparatus, 3... Database apparatus, 4, 4a... machine learning device, 5, 5a... information processing device, 6... User terminal device, 7... Network, 10A... first learning model, 10B... second learning model, 11A... First learning data, 11B... Second learning data, 20... housing, 21... load/unload unit, 22... Polishing unit, 22A to 22D... Polishing part, 23... Substrate transfer unit, 24... Finishing unit, 24A, 24B... Roll sponge cleaning part, 24C, 24D... pen sponge washing section, 24E, 24F... drying section, 24G, 24H... transport unit, 25... film thickness measurement unit, 26...
  • control unit 30...Production history information, 31...Finishing test information, 40... control unit, 41... communication unit, 42... learning data storage unit, 43 ... learned model storage unit, 50... Control unit, 51... Communication unit, 52... Learned model storage unit, 220... polishing table, 221... top ring, 222: Polishing fluid supply nozzle (substrate processing fluid supply unit), 223...dresser, 224...atomizer, 240... Substrate cleaning part, 241... Substrate holding part, 242... Cleaning fluid supply unit (substrate processing fluid supply unit), 243...Cleaning tool cleaning unit, 244...Environmental sensor, 245 ... dry fluid supply unit (substrate processing fluid supply unit), 260... control unit, 21...

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  • Mechanical Engineering (AREA)
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Abstract

An information processing device (5) comprises: an information acquisition unit (500) that acquires substrate processing fluid supply information including substrate processing fluid supply state information which indicates the state of supply of a substrate processing fluid that is supplied from a substrate processing fluid supply unit (222, 242a, 245a), in processing of a substrate (W) which is performed by a substrate processing device (2); and a state prediction unit (501) that predicts substrate processing fluid supply position information corresponding to the substrate processing fluid supply information by inputting the substrate processing fluid supply information to a learning model which has learned, by machine learning, correlations between substrate processing fluid supply information and substrate processing fluid supply position information, said substrate processing fluid supply position information indicating the supply position of the fluid that is supplied by the substrate processing fluid supply unit when the substrate processing device operates.

Description

情報処理装置、推論装置、機械学習装置、情報処理方法、推論方法、及び、機械学習方法Information processing device, reasoning device, machine learning device, information processing method, reasoning method, and machine learning method
　本発明は、情報処理装置、推論装置、機械学習装置、情報処理方法、推論方法、及び、機械学習方法に関する。 The present invention relates to an information processing device, an inference device, a machine learning device, an information processing method, an inference method, and a machine learning method.
　半導体ウェハ等の基板に対して各種の処理を行う基板処理装置の１つとして、化学機械研磨（ＣＭＰ：Ｃｈｅｍｉｃａｌ　Ｍｅｃｈａｎｉｃａｌ　Ｐｏｌｉｓｈｉｎｇ）処理を行う基板処理装置が知られている。基板処理装置では、例えば、研磨パッドを有する研磨テーブルを回転させつつ、液体供給ノズルから研磨パッドに研磨液（スラリー）を供給した状態で、トップリングと呼ばれる研磨ヘッドにより基板を研磨パッドに押し付けることで、基板は化学的かつ機械的に研磨される。そして、研磨後の基板に付着した研磨屑等の異物を除去するため、研磨後の基板に基板洗浄流体を供給しながら洗浄具を接触させてスクラブ洗浄し、さらに基板を乾燥することで、一連の処理が終了し、次の基板の処理に移行する。 A substrate processing apparatus that performs chemical mechanical polishing (CMP) processing is known as one of substrate processing apparatuses that perform various types of processing on substrates such as semiconductor wafers. In a substrate processing apparatus, for example, while a polishing table having a polishing pad is rotated, a polishing liquid (slurry) is supplied to the polishing pad from a liquid supply nozzle, and a polishing head called a top ring presses the substrate against the polishing pad. , the substrate is chemically and mechanically polished. Then, in order to remove foreign matter such as polishing dust adhering to the substrate after polishing, the substrate after polishing is scrub-cleaned by bringing a cleaning tool into contact with the substrate while supplying a substrate-cleaning fluid, and then the substrate is dried. , the processing of the next substrate is started.
　上記のような一連の処理が繰り返し行われると、基板に流体を噴射するノズルの移動位置にずれが生じるようになり、流体の供給位置にもずれが生じ、結果として、基板の処理に必要な液体を最適な位置に供給することが困難となることがあった。従来、供給ノズルの先端位置を研磨パッドに対して相対的に調整することで、研磨スラリーをウェハに対して適切に供給する技術が開示されている。（例えば、特許文献１参照）。 When the series of processes described above is repeated, the movement position of the nozzle that injects the fluid onto the substrate is shifted, and the position of supplying the fluid is also shifted. It was sometimes difficult to supply the liquid to the optimum position. Conventionally, there has been disclosed a technique for appropriately supplying polishing slurry to a wafer by adjusting the tip position of a supply nozzle relative to a polishing pad. (See Patent Document 1, for example).
特開２００７－０５９９３８号公報JP 2007-059938 A
　特許文献１に記載された技術は、供給ノズルの先端を研磨スラリーの供給量やウェハの位置等に応じて適宜移動して研磨スラリーの供給位置を調整する。 The technique described in Patent Document 1 adjusts the supply position of the polishing slurry by appropriately moving the tip of the supply nozzle according to the amount of supply of the polishing slurry, the position of the wafer, and the like.
　一方、基板処理流体を適切な位置に供給するにあたり、流体の供給流量、流体の供給圧力、流体供給弁の開度、流体供給弁の一次側の圧力等の動作状態は、基板処理流体の供給位置に影響を与える要素であるが、基板処理流体の供給位置に対して複雑かつ相互に作用する。そのため、各動作状態が、基板処理流体の供給位置にどのような影響を与えるのかを的確に解析することは困難である。 On the other hand, in supplying the substrate processing fluid to an appropriate position, the operating conditions such as the fluid supply flow rate, the fluid supply pressure, the opening degree of the fluid supply valve, the pressure on the primary side of the fluid supply valve, etc. Positional influencing factors are complex and interact with substrate processing fluid application position. Therefore, it is difficult to accurately analyze how each operating state affects the supply position of the substrate processing fluid.
　本発明は、上記の課題に鑑み、基板処理流体の供給状態に応じて基板処理流体を適切な位置に供給することを可能とする情報処理装置、推論装置、機械学習装置、情報処理方法、推論方法、及び、機械学習方法を提供することを目的とする。 In view of the above problems, the present invention provides an information processing apparatus, an inference apparatus, a machine learning apparatus, an information processing method, an inference apparatus, and an apparatus capable of supplying a substrate processing fluid to an appropriate position according to the supply state of the substrate processing fluid. It aims to provide a method and a machine learning method.
　上記目的を達成するために、本発明の一態様に係る情報処理装置は、
　基板に処理流体を供給する一又は複数の基板処理流体供給部を備える基板処理装置により行われる前記基板の処理における、前記基板処理流体供給部から供給される基板処理流体の供給状態を示す基板処理流体供給状態情報、を含む基板処理流体供給情報を取得する情報取得部と、
　前記基板処理流体供給情報と、前記基板処理装置が動作したときの前記基板処理流体供給部が供給する流体の供給位置を示す基板処理流体供給位置情報との相関関係を機械学習により学習させた学習モデルに、前記情報取得部により取得された前記基板処理流体供給情報を入力することで、当該基板処理流体供給情報に対する前記基板処理流体供給位置情報を予測する状態予測部と、
を備える。 In order to achieve the above object, an information processing device according to an aspect of the present invention includes:
Substrate processing showing a supply state of a substrate processing fluid supplied from the substrate processing fluid supply unit in the substrate processing performed by the substrate processing apparatus having one or more substrate processing fluid supply units for supplying the processing fluid to the substrate an information acquisition unit for acquiring substrate processing fluid supply information including fluid supply state information;
learning by machine learning a correlation between the substrate processing fluid supply information and substrate processing fluid supply position information indicating a supply position of the fluid supplied by the substrate processing fluid supply unit when the substrate processing apparatus is operated; a state prediction unit that predicts the substrate processing fluid supply position information with respect to the substrate processing fluid supply information by inputting the substrate processing fluid supply information acquired by the information acquisition unit into a model;
Prepare.
　本発明の一態様に係る情報処理装置によれば、基板処理流体供給状態情報を含む基板処理流体供給情報が学習モデルに入力されることで、当該基板処理流体供給情報に対する基板処理流体供給位置情報が予測されるので、基板処理装置の基板処理流体供給状態に応じて基板処理流体供給位置を適切に予測することができる。 According to the information processing apparatus according to the aspect of the present invention, the substrate processing fluid supply information including the substrate processing fluid supply state information is input to the learning model, whereby the substrate processing fluid supply position information corresponding to the substrate processing fluid supply information is obtained. is predicted, the substrate processing fluid supply position can be appropriately predicted according to the substrate processing fluid supply state of the substrate processing apparatus.
　上記以外の課題、構成及び効果は、後述する発明を実施するための形態にて明らかにされる。 Problems, configurations, and effects other than the above will be clarified in the mode for carrying out the invention described later.
基板処理システム１の一例を示す全体構成図である。1 is an overall configuration diagram showing an example of a substrate processing system 1; FIG. 基板処理装置２の一例を示す平面図である。1 is a plan view showing an example of a substrate processing apparatus 2; FIG. 第１乃至第４の研磨部２２Ａ～２２Ｄの一例を示す斜視図である。FIG. 4 is a perspective view showing an example of first to fourth polishing portions 22A to 22D; 第１及び第２のロールスポンジ洗浄部２４Ａ、２４Ｂの一例を示す斜視図である。FIG. 4 is a perspective view showing an example of first and second roll sponge cleaning units 24A and 24B; 第１及び第２のペンスポンジ洗浄部２４Ｃ、２４Ｄの一例を示す斜視図である。FIG. 3 is a perspective view showing an example of first and second pen sponge cleaning units 24C and 24D. 第１及び第２の乾燥部２４Ｅ、２４Ｆの一例を示す斜視図である。FIG. 3 is a perspective view showing an example of first and second drying sections 24E and 24F; 基板処理流体供給系統における基板処理流体供給弁の配置を示す図である。FIG. 4 is a diagram showing the arrangement of substrate processing fluid supply valves in a substrate processing fluid supply system; 基板処理装置２の一例を示すブロック図である。2 is a block diagram showing an example of a substrate processing apparatus 2; FIG. コンピュータ９００の一例を示すハードウエア構成図である。3 is a hardware configuration diagram showing an example of a computer 900; FIG. データベース装置３により管理される生産履歴情報３０の一例を示すデータ構成図である。3 is a data configuration diagram showing an example of production history information 30 managed by a database device 3; FIG. データベース装置３により管理される仕上げ試験情報３１の一例を示すデータ構成図である。3 is a data configuration diagram showing an example of finishing test information 31 managed by the database device 3. FIG. 第１の実施形態に係る機械学習装置４の一例を示すブロック図である。1 is a block diagram showing an example of a machine learning device 4 according to a first embodiment; FIG. 第１の学習モデル１０Ａ及び第１の学習用データ１１Ａの一例を示す図である。It is a figure which shows an example of 10 A of 1st learning models, and 11 A of data for 1st learning. 機械学習装置４による機械学習方法の一例を示すフローチャートである。4 is a flowchart showing an example of a machine learning method by the machine learning device 4; 第１の実施形態に係る情報処理装置５の一例を示すブロック図である。1 is a block diagram showing an example of an information processing device 5 according to a first embodiment; FIG. 第１の実施形態に係る情報処理装置５の一例を示す機能説明図である。1 is a function explanatory diagram showing an example of an information processing device 5 according to a first embodiment; FIG. 情報処理装置５による情報処理方法の一例を示すフローチャートである。5 is a flowchart showing an example of an information processing method by the information processing device 5; 第２の実施形態に係る機械学習装置４ａの一例を示すブロック図である。It is a block diagram which shows an example of the machine-learning apparatus 4a based on 2nd Embodiment. 第２の学習モデル１０Ｂ及び第２の学習用データ１１Ｂの一例を示す図である。It is a figure which shows an example of the 2nd learning model 10B and the 2nd data for learning 11B. 第２の実施形態に係る情報処理装置５ａとして機能する情報処理装置５ａの一例を示すブロック図である。FIG. 5 is a block diagram showing an example of an information processing device 5a functioning as an information processing device 5a according to a second embodiment; 第２の実施形態に係る情報処理装置５ａの一例を示す機能説明図である。FIG. 5 is a functional explanatory diagram showing an example of an information processing device 5a according to a second embodiment;
　以下、図面を参照して本発明を実施するための実施形態について説明する。以下では、本発明の目的を達成するための説明に必要な範囲を模式的に示し、本発明の該当部分の説明に必要な範囲を主に説明することとし、説明を省略する箇所については公知技術によるものとする。 Hereinafter, embodiments for carrying out the present invention will be described with reference to the drawings. In the following, the range necessary for the description to achieve the object of the present invention is schematically shown, and the range necessary for the description of the relevant part of the present invention is mainly described. It shall be by technology.
（第１の実施形態）
　図１は、基板処理システム１の一例を示す全体構成図である。本実施形態に係る基板処理システム１は、半導体ウェハ等の基板（以下、「ウェハ」という）Ｗを研磨パッドに押し付けることでウェハＷの表面を平坦に研磨する化学機械研磨処理（以下、「研磨処理」という）、研磨処理後のウェハＷを洗浄具に接触させることでウェハＷの表面を洗浄する洗浄処理、洗浄したウェハＷの表面を乾燥具により乾燥する乾燥処理等を含む一連の基板処理を管理するシステムとして機能する。なお、洗浄処理、及び、乾燥処理は、仕上げ処理を構成する。 (First embodiment)
FIG. 1 is an overall configuration diagram showing an example of a substrate processing system 1. As shown in FIG. The substrate processing system 1 according to the present embodiment performs a chemical mechanical polishing process (hereinafter referred to as "polishing") for flatly polishing the surface of the wafer W by pressing the substrate (hereinafter referred to as "wafer") W such as a semiconductor wafer against a polishing pad. A series of substrate processing including a cleaning process of cleaning the surface of the wafer W by bringing the polished wafer W into contact with a cleaning tool, and a drying process of drying the cleaned surface of the wafer W using a drying tool. function as a system to manage Note that the cleaning treatment and the drying treatment constitute finishing treatment.
　基板処理システム１は、その主要な構成として、基板処理装置２と、データベース装置３と、機械学習装置４と、情報処理装置５と、ユーザ端末装置６とを備える。各装置２～６は、例えば、汎用又は専用のコンピュータ（後述の図８参照）で構成されるとともに、有線又は無線のネットワーク７に接続されて、各種のデータ（図１には一部のデータの送受信を破線の矢印にて図示）を相互に送受信可能に構成される。なお、各装置２～６の数やネットワーク７の接続構成は、図１の例に限られず、適宜変更してもよい。 The substrate processing system 1 includes a substrate processing device 2, a database device 3, a machine learning device 4, an information processing device 5, and a user terminal device 6 as its main components. Each of the devices 2 to 6 is configured by, for example, a general-purpose or dedicated computer (see FIG. 8 described later), and is connected to a wired or wireless network 7 to store various data (partial data in FIG. 1). (shown by dashed arrows) can be mutually transmitted and received. The number of devices 2 to 6 and the connection configuration of the network 7 are not limited to the example shown in FIG. 1, and may be changed as appropriate.
　基板処理装置２は、複数のユニットで構成されて、１又は複数のウェハＷに対する一連の基板処理として、例えば、ロ―ド、研磨、洗浄、乾燥、膜厚測定、アンロード等の各処理をそれぞれ行う装置である。その際、基板処理装置２は、各ユニットにそれぞれ設定された複数の装置パラメータからなる装置設定情報２６５と、研磨処理、洗浄処理、乾燥処理の動作状態等を定める基板レシピ情報２６６とを参照しつつ、各ユニットの動作を制御する。 The substrate processing apparatus 2 is composed of a plurality of units, and performs a series of substrate processing on one or a plurality of wafers W, such as loading, polishing, cleaning, drying, film thickness measurement, and unloading. It is a device that performs each. At this time, the substrate processing apparatus 2 refers to apparatus setting information 265 consisting of a plurality of apparatus parameters respectively set for each unit, and substrate recipe information 266 that defines the operation states of the polishing process, the cleaning process, the drying process, and the like. while controlling the operation of each unit.
　基板処理装置２は、各ユニットの動作に応じて、各種のレポートＲをデータベース装置３、ユーザ端末装置６等に送信する。各種のレポートＲには、例えば、基板処理が行われたときの対象となるウェハＷを特定する工程情報、各処理が行われたときの各ユニットの状態を示す装置状態情報、基板処理装置２にて検出されたイベント情報、基板処理装置２に対するユーザ（オペレータ、生産管理者、保守管理者等）の操作情報等が含まれる。 The substrate processing apparatus 2 transmits various reports R to the database device 3, the user terminal device 6, etc. according to the operation of each unit. The various reports R include, for example, process information specifying the target wafer W when substrate processing was performed, apparatus status information indicating the status of each unit when each process was performed, substrate processing apparatus 2 event information detected in , operation information of a user (operator, production manager, maintenance manager, etc.) for the substrate processing apparatus 2, and the like.
　データベース装置３は、本生産用の基板処理流体供給部を用いて基板処理が行われたときの履歴に関する生産履歴情報３０と、試験用の基板処理流体供給部を用いて基板処理流体供給の試験（以下、「基板処理流体供給試験」という）が行われたときの履歴に関する基板処理流体供給試験情報３１とを管理する装置である。なお、データベース装置３には、上記の他に、装置設定情報２６５や基板レシピ情報２６６が記憶されていてもよく、その場合には、基板処理装置２がこれらの情報を参照するようにしてもよい。なお、基板処理流体は、研磨処理における研磨流体、洗浄処理における洗浄流体、及び乾燥処理における乾燥流体の少なくとも１つを含む。したがって、基板処理流体供給試験は、研磨処理の試験、洗浄処理の試験、及び、乾燥処理の試験の少なくとも１つを含む。 The database device 3 stores production history information 30 relating to the history of substrate processing performed using the substrate processing fluid supply unit for actual production, and test substrate processing fluid supply using the test substrate processing fluid supply unit. It is a device for managing substrate processing fluid supply test information 31 relating to the history of the execution of the substrate processing fluid supply test (hereinafter referred to as "substrate processing fluid supply test"). In addition to the above, the database device 3 may store device setting information 265 and substrate recipe information 266. In that case, the substrate processing device 2 may refer to these information. good. Note that the substrate processing fluid includes at least one of a polishing fluid in polishing processing, a cleaning fluid in cleaning processing, and a drying fluid in drying processing. Therefore, the substrate processing fluid supply test includes at least one of a polishing process test, a cleaning process test, and a drying process test.
　データベース装置３は、基板処理装置２が本生産用の基板処理流体供給部を用いて基板処理を行ったときに、基板処理装置２から各種のレポートＲを随時受信し、生産履歴情報３０に登録することで、生産履歴情報３０には、基板処理に関するレポートＲが蓄積される。 The database device 3 receives various reports R from the substrate processing apparatus 2 as needed and registers them in the production history information 30 when the substrate processing apparatus 2 performs substrate processing using the substrate processing fluid supply unit for production. As a result, the production history information 30 accumulates reports R regarding substrate processing.
　データベース装置３は、基板処理装置２が試験用の基板処理流体供給部を用いて基板処理流体供給試験を行ったときに、基板処理装置２から各種のレポートＲ（装置状態情報を少なくとも含む）を随時受信し、基板処理流体供給試験情報３１に登録するとともに、その基板処理流体供給試験の試験結果を対応付けて登録することで、基板処理流体供給試験情報３１には、基板処理流体供給試験に関するレポートＲ及び試験結果が蓄積される。基板処理流体供給試験は、本生産用の基板処理装置２で行われてもよいし、基板処理装置２と同様の基板処理流体の供給を再現可能な試験用の基板処理流体供給試験装置（不図示）で行われてもよい。 The database device 3 receives various reports R (including at least device status information) from the substrate processing apparatus 2 when the substrate processing apparatus 2 performs a substrate processing fluid supply test using the test substrate processing fluid supply unit. It is received as needed and registered in the substrate processing fluid supply test information 31, and the test results of the substrate processing fluid supply test are registered in association with each other. Reports R and test results are accumulated. The substrate processing fluid supply test may be performed by the substrate processing apparatus 2 for production, or by a test substrate processing fluid supply test apparatus (not applicable) that can reproduce the same substrate processing fluid supply as the substrate processing apparatus 2. shown).
　試験用の基板処理流体供給部や基板処理流体供給試験装置には、基板処理流体供給部のコンディションとして、例えば、基板処理流体供給部から供給される基板処理流体の流量、基板処理流体供給部から供給される基板処理流体の圧力、基板処理流体の流量を調整する基板処理流体供給弁の状態、及び、基板処理流体の流量を調整する基板処理流体供給弁の一次側の圧力を測定するための各種の基板処理流体供給状態測定機器（不図示）が設けられ、基板処理流体供給状態測定機器の測定値が、試験結果として基板処理流体供給試験情報３１に登録される。 In the substrate processing fluid supply unit for testing and the substrate processing fluid supply testing device, the condition of the substrate processing fluid supply unit is, for example, the flow rate of the substrate processing fluid supplied from the substrate processing fluid supply unit, the flow rate of the substrate processing fluid supplied from the substrate processing fluid supply unit, for measuring the pressure of the supplied substrate processing fluid, the state of the substrate processing fluid supply valve that regulates the flow rate of the substrate processing fluid, and the pressure on the primary side of the substrate processing fluid supply valve that regulates the flow rate of the substrate processing fluid; Various substrate processing fluid supply state measuring devices (not shown) are provided, and the measured values of the substrate processing fluid supply state measuring devices are registered in the substrate processing fluid supply test information 31 as test results.
　機械学習装置４は、機械学習の学習フェーズの主体として動作し、例えば、データベース装置３から基板処理流体供給試験情報３１の一部を第１の学習用データ１１Ａとして取得し、情報処理装置５にて用いられる第１の学習モデル１０Ａを機械学習により生成する。学習済みの第１の学習モデル１０Ａは、ネットワーク７や記録媒体等を介して情報処理装置５に提供される。 The machine learning device 4 operates as a main part of the learning phase of machine learning, for example, acquires part of the substrate processing fluid supply test information 31 from the database device 3 as first learning data 11A, and stores it in the information processing device 5. Machine learning generates a first learning model 10A used for The trained first learning model 10A is provided to the information processing device 5 via the network 7, a recording medium, or the like.
　情報処理装置５は、機械学習の推論フェーズの主体として動作し、機械学習装置４により生成された第１の学習モデル１０Ａを用いて、基板処理装置２による基板処理流体の供給が本生産用の基板処理流体供給部を用いて行われたときに、その基板処理流体供給位置を予測し、その予測した結果である基板処理流体供給位置情報をデータベース装置３、ユーザ端末装置６等に送信する。情報処理装置５が基板処理流体供給位置情報を予測するタイミングとしては、基板処理流体の供給が行われた後（事後予測処理）でもよいし、基板処理流体の供給が行われている最中（リアルタイム予測処理）でもよいし、基板処理流体の供給が行われる前（事前予測処理）でもよい。 The information processing device 5 operates as the subject of the inference phase of machine learning, and uses the first learning model 10A generated by the machine learning device 4 to determine whether the substrate processing fluid supplied by the substrate processing device 2 is suitable for production. When the substrate processing fluid supply unit is used, the substrate processing fluid supply position is predicted, and substrate processing fluid supply position information, which is the predicted result, is transmitted to the database device 3, the user terminal device 6, and the like. The timing at which the information processing apparatus 5 predicts the substrate processing fluid supply position information may be after the substrate processing fluid is supplied (post-prediction processing) or while the substrate processing fluid is being supplied ( real-time prediction processing) or before the substrate processing fluid is supplied (advance prediction processing).
　ユーザ端末装置６は、ユーザが使用する端末装置であり、据置型の装置でもよいし、携帯型の装置でもよい。ユーザ端末装置６は、例えば、アプリケーションプログラム、ウェブブラウザ等の表示画面を介して各種の入力操作を受け付けるとともに、表示画面を介して各種の情報（例えば、イベントの通知、基板処理流体供給位置情報、生産履歴情報３０、基板処理流体供給試験情報３１等）を表示する。 The user terminal device 6 is a terminal device used by the user, and may be a stationary device or a portable device. The user terminal device 6 receives various input operations via the display screen of, for example, an application program or a web browser, and various information via the display screen (e.g., event notification, substrate processing fluid supply position information, production history information 30, substrate processing fluid supply test information 31, etc.).
（基板処理装置２）
　図２は、基板処理装置２の一例を示す平面図である。基板処理装置２は、平面視で略矩形状のハウジング２０の内部に、ロード／アンロードユニット２１と、研磨ユニット２２と、基板搬送ユニット２３と、仕上げユニット２４と、膜厚測定ユニット２５と、制御ユニット２６とを備えて構成される。ロード／アンロードユニット２１と、研磨ユニット２２、基板搬送ユニット２３及び仕上げユニット２４との間は、第１の隔壁２００Ａにより区画され、基板搬送ユニット２３と仕上げユニット２４との間は、第２の隔壁２００Ｂにより区画されている。 (Substrate processing apparatus 2)
FIG. 2 is a plan view showing an example of the substrate processing apparatus 2. As shown in FIG. The substrate processing apparatus 2 includes a load/unload unit 21, a polishing unit 22, a substrate transfer unit 23, a finishing unit 24, a film thickness measurement unit 25, and a housing 20 which is substantially rectangular in plan view. and a control unit 26 . A first partition wall 200A separates the load/unload unit 21 from the polishing unit 22, the substrate transfer unit 23 and the finishing unit 24, and the substrate transfer unit 23 and the finishing unit 24 are separated from each other by a second separation wall 200A. It is partitioned by a partition wall 200B.
（ロード／アンロードユニット）
　ロード／アンロードユニット２１は、多数のウェハＷを上下方向に収納可能なウェハカセット（ＦＯＵＰ等）が載置される第１乃至第４のフロントロード部２１０Ａ～２１０Ｄと、ウェハカセットに収納されたウェハＷの収納方向（上下方向）に沿って上下移動可能な搬送ロボット２１１と、第１乃至第４のフロントロード部２１０Ａ～２１０Ｄの並び方向（ハウジング２０の短手方向）に沿って搬送ロボット２１１を移動させる水平移動機構部２１２とを備える。 (load/unload unit)
The loading/unloading unit 21 includes first to fourth front loading sections 210A to 210D on which wafer cassettes (FOUPs, etc.) capable of vertically accommodating a large number of wafers W are placed, and A transfer robot 211 capable of moving up and down along the storage direction (vertical direction) of the wafer W, and a transfer robot 211 along the direction in which the first to fourth front load sections 210A to 210D are arranged (transverse direction of the housing 20). and a horizontal movement mechanism 212 for moving the .
　搬送ロボット２１１は、第１乃至第４のフロントロード部２１０Ａ～２１０Ｄの各々に載置されたウェハカセット、基板搬送ユニット２３（具体的に、後述のリフタ２３２）、仕上げユニット２４（具体的に、後述の第１及び第２の乾燥部２４Ｅ、２４Ｆ）、及び、膜厚測定ユニット２５に対してアクセス可能に構成され、それらの間でウェハＷを受け渡すための上下二段のハンド（不図示）を備える。下側ハンドは、処理前のウェハＷを受け渡すときに使用され、上側ハンドは、処理後のウェハＷを受け渡すときに使用される。基板搬送ユニット２３や仕上げユニット２４に対するウェハＷの受け渡しの際には、第１の隔壁２００Ａに設けられたシャッタ（不図示）が開閉される。 The transfer robot 211 carries wafer cassettes placed on each of the first to fourth front load sections 210A to 210D, the substrate transfer unit 23 (specifically, a lifter 232 to be described later), and the finishing unit 24 (specifically, First and second drying units 24E and 24F, which will be described later), and the film thickness measurement unit 25, are configured to be accessible, and upper and lower two-stage hands (not shown) for transferring the wafer W between them ). The lower hand is used when transferring wafers W before processing, and the upper hand is used when transferring wafers W after processing. When the wafer W is transferred to the substrate transfer unit 23 or the finishing unit 24, a shutter (not shown) provided on the first partition 200A is opened and closed.
（研磨ユニット）
　研磨ユニット２２は、ウェハＷの研磨処理（平坦化）をそれぞれ行う第１乃至第４の研磨部２２Ａ～２２Ｄを備える。第１乃至第４の研磨部２２Ａ～２２Ｄは、ハウジング２０の長手方向に沿って並べられて配置される。 (polishing unit)
The polishing unit 22 includes first to fourth polishing sections 22A to 22D for polishing (flattening) the wafer W, respectively. The first to fourth polishing parts 22A to 22D are arranged side by side along the longitudinal direction of the housing 20. As shown in FIG.
　図３は、第１乃至第４の研磨部２２Ａ～２２Ｄの一例を示す斜視図である。第１乃至第４の研磨部２２Ａ～２２Ｄの基本的な構成や機能は共通する。 FIG. 3 is a perspective view showing an example of the first to fourth polishing units 22A to 22D. The basic configurations and functions of the first to fourth polishing units 22A to 22D are common.
　第１乃至第４の研磨部２２Ａ～２２Ｄの各々は、研磨面を有する研磨パッド２２００を回転可能に支持する研磨テーブル２２０と、ウェハＷを保持し、かつウェハＷを研磨テーブル２２０上の研磨パッド２２００に押圧しながら研磨するためのトップリング（研磨ヘッド）２２１と、研磨パッド２２００に研磨流体を供給する研磨流体供給ノズル２２２と、ドレッサディスク２２３０を回転可能に支持するとともにドレッサディスク２２３０を研磨パッド２２００の研磨面に接触させて研磨パッド２２００をドレッシングするドレッサ２２３と、研磨パッド２２００に洗浄流体を噴射するアトマイザ２２４とを備える。 Each of the first to fourth polishing units 22A to 22D includes a polishing table 220 that rotatably supports a polishing pad 2200 having a polishing surface, a wafer W that holds the wafer W, and a polishing pad on the polishing table 220 that holds the wafer W. A top ring (polishing head) 221 for polishing while pressing against 2200, a polishing fluid supply nozzle 222 for supplying polishing fluid to the polishing pad 2200, and a dresser disk 2230 rotatably supporting the dresser disk 2230 on the polishing pad 2200. A dresser 223 that contacts the polishing surface of 2200 to dress the polishing pad 2200 and an atomizer 224 that sprays cleaning fluid onto the polishing pad 2200 are provided.
　研磨テーブル２２０は、研磨テーブルシャフト２２０ａにより支持されて、その軸心周りに研磨テーブル２２０を回転駆動させる回転移動機構部２２０ｂと、研磨パッド２２００の表面温度を調節する温調機構部２２０ｃとを備える。 The polishing table 220 is supported by a polishing table shaft 220a and includes a rotational movement mechanism 220b that rotates the polishing table 220 about its axis, and a temperature control mechanism 220c that adjusts the surface temperature of the polishing pad 2200. .
　トップリング２２１は、上下方向に移動可能なトップリングシャフト２２１ａに支持されて、その軸心周りにトップリング２２１を回転駆動させる回転移動機構部２２１ｃと、トップリング２２１を上下方向に移動させる上下移動機構部２２１ｄと、支持シャフト２２１ｂを旋回中心にしてトップリング２２１を旋回（揺動）移動させる揺動移動機構部２２１ｅとを備える。 The top ring 221 is supported by a top ring shaft 221a that can move vertically. A rotation movement mechanism 221c rotates the top ring 221 about its axis, and a vertical movement mechanism moves the top ring 221 vertically. It includes a mechanism portion 221d and a rocking movement mechanism portion 221e for rotating (swinging) the top ring 221 around the support shaft 221b.
　研磨流体供給ノズル２２２は、支持シャフト２２２ａに支持されて、支持シャフト２２２ａを旋回中心にして研磨流体供給ノズル２２２を旋回移動させる揺動移動機構部２２２ｂと、研磨流体の流量を調節する流量調節部２２２ｃと、研磨流体の温度を調節する温調機構部２２２ｄとを備える。研磨流体は、研磨液（スラリー）又は純水であり、さらに、薬液を含むものでもよいし、研磨液に分散剤を添加したものでもよい。研磨流体供給ノズル２２２は、基板処理流体供給部を構成する。 The polishing fluid supply nozzle 222 is supported by a support shaft 222a. A rocking movement mechanism 222b rotates and moves the polishing fluid supply nozzle 222 around the support shaft 222a, and a flow control unit adjusts the flow rate of the polishing fluid. 222c and a temperature control mechanism 222d for adjusting the temperature of the polishing fluid. The polishing fluid is a polishing liquid (slurry) or pure water, and may further contain a chemical liquid, or may be a polishing liquid to which a dispersant is added. The polishing fluid supply nozzle 222 constitutes a substrate processing fluid supply section.
　ドレッサ２２３は、上下方向に移動可能なドレッサシャフト２２３ａに支持されて、その軸心周りにドレッサ２２３を回転駆動させる回転移動機構部２２３ｃと、ドレッサ２２３を上下方向に移動させる上下移動機構部２２３ｄと、支持シャフト２２３ｂを旋回中心にしてドレッサ２２３を旋回移動させる揺動移動機構部２２３ｅとを備える。 The dresser 223 is supported by a vertically movable dresser shaft 223a. The dresser 223 is supported by a rotational movement mechanism 223c that drives the dresser 223 to rotate about its axis, and a vertical movement mechanism 223d that vertically moves the dresser 223. , and a swing movement mechanism portion 223e for swinging and moving the dresser 223 around the support shaft 223b.
　アトマイザ２２４は、支持シャフト２２４ａに支持されて、支持シャフト２２４ａを旋回中心にしてアトマイザ２２４を旋回移動させる揺動移動機構部２２４ｂと、洗浄流体の流量を調節する流量調節部２２４ｃとを備える。洗浄流体は、液体（例えば、純水）と気体（例えば、窒素ガス）の混合流体又は液体（例えば、純水）である。 The atomizer 224 is supported by a support shaft 224a and includes a swing movement mechanism section 224b that swings and moves the atomizer 224 around the support shaft 224a, and a flow rate adjustment section 224c that adjusts the flow rate of the cleaning fluid. The cleaning fluid is a mixed fluid of liquid (eg, pure water) and gas (eg, nitrogen gas) or liquid (eg, pure water).
　ウェハＷは、トップリング２２１の下面に吸着保持されて、研磨テーブル２２０上の所定の研磨位置に移動された後、研磨流体供給ノズル２２２から研磨流体が供給された研磨パッド２２００の研磨面に対してトップリング２２１により押圧されることで研磨される。 After the wafer W is held by suction on the lower surface of the top ring 221 and moved to a predetermined polishing position on the polishing table 220 , the wafer W is applied to the polishing surface of the polishing pad 2200 to which the polishing fluid is supplied from the polishing fluid supply nozzle 222 . It is polished by being pressed by the top ring 221 .
（基板搬送ユニット）
　基板搬送ユニット２３は、図２に示すように、第１乃至第４の研磨部２２Ａ～２２Ｄの並び方向（ハウジング２０の長手方向）に沿って水平移動可能な第１及び第２のリニアトランスポータ２３０Ａ、２３０Ｂと、第１及び第２のリニアトランスポータ２３０Ａ、２３０Ｂの間に配置されたスイングトランスポータ２３１と、ロード／アンロードユニット２１側に配置されたリフタ２３２と、仕上げユニット２４側に配置されたウェハＷの仮置き台２３３とを備える。 (substrate transfer unit)
The substrate transfer unit 23 is, as shown in FIG. 2, first and second linear transporters horizontally movable along the direction in which the first to fourth polishing units 22A to 22D are arranged (the longitudinal direction of the housing 20). 230A, 230B, a swing transporter 231 disposed between the first and second linear transporters 230A, 230B, a lifter 232 disposed on the loading/unloading unit 21 side, and a finishing unit 24 side. and a temporary placing table 233 for the wafer W which has been processed.
　第１のリニアトランスポータ２３０Ａは、第１及び第２の研磨部２２Ａ、２２Ｂに隣接して配置されて、４つの搬送位置（ロード／アンロードユニット２１側から順に第１乃至第４の搬送位置ＴＰ１～ＴＰ４とする）の間でウェハＷを搬送する機構である。第２の搬送位置ＴＰ２は、第１の研磨部２２Ａに対してウェハＷを受け渡す位置であり、第３の搬送位置ＴＰ３は、第２の研磨部２２Ｂに対してウェハＷを受け渡す位置である。 The first linear transporter 230A is arranged adjacent to the first and second polishing units 22A and 22B and has four transport positions (first to fourth transport positions in order from the load/unload unit 21 side). TP1 to TP4) for transporting the wafer W. The second transfer position TP2 is the position at which the wafer W is transferred to the first polishing section 22A, and the third transfer position TP3 is the position at which the wafer W is transferred to the second polishing section 22B. be.
　第２のリニアトランスポータ２３０Ｂは、第３及び第４の研磨部２２Ｃ、２２Ｄに隣接して配置されて、３つの搬送位置（ロード／アンロードユニット２１側から順に第５乃至第７の搬送位置ＴＰ５～ＴＰ７とする）の間でウェハＷを搬送する機構である。第６の搬送位置ＴＰ６は、第３の研磨部２２Ｃに対してウェハＷを受け渡す位置であり、第７の搬送位置ＴＰ７は、第４の研磨部２２Ｄに対してウェハＷを受け渡す位置である。 The second linear transporter 230B is arranged adjacent to the third and fourth polishing units 22C and 22D and has three transport positions (fifth to seventh transport positions in order from the load/unload unit 21 side). TP5 to TP7) for transporting the wafer W. The sixth transfer position TP6 is a position for transferring the wafer W to the third polishing section 22C, and the seventh transfer position TP7 is a position for transferring the wafer W to the fourth polishing section 22D. be.
　スイングトランスポータ２３１は、第４及び第５の搬送位置ＴＰ４、ＴＰ５に隣接して配置されるとともに、第４及び第５の搬送位置ＴＰ４、ＴＰ５の間を移動可能なハンドを有する。スイングトランスポータ２３１は、第１及び第２のリニアトランスポータ２３０Ａ、２３０Ｂの間でウェハＷを受け渡すとともに、仮置き台２３３にウェハＷを仮置きする機構である。リフタ２３２は、第１の搬送位置ＴＰ１に隣接して配置されて、ロード／アンロードユニット２１の搬送ロボット２１１との間でウェハＷを受け渡す機構である。ウェハＷの受け渡しの際、第１の隔壁２００Ａに設けられたシャッタ（不図示）が開閉される。 The swing transporter 231 is arranged adjacent to the fourth and fifth transport positions TP4 and TP5 and has a hand that can move between the fourth and fifth transport positions TP4 and TP5. The swing transporter 231 is a mechanism that transfers the wafer W between the first and second linear transporters 230A and 230B and temporarily places the wafer W on the temporary placement table 233 . The lifter 232 is a mechanism arranged adjacent to the first transfer position TP1 to transfer the wafer W to and from the transfer robot 211 of the load/unload unit 21 . When the wafer W is transferred, a shutter (not shown) provided on the first partition 200A is opened and closed.
（仕上げユニット）
　仕上げユニット２４は、図２に示すように、ロールスポンジ２４００を用いた基板洗浄装置として、上下二段に配置された第１及び第２のロールスポンジ洗浄部２４Ａ、２４Ｂと、ペンスポンジ２４０１を用いた基板洗浄装置として、上下二段に配置された第１及び第２のペンスポンジ洗浄部２４Ｃ、２４Ｄと、洗浄後のウェハＷを乾燥させる基板乾燥装置として、上下二段に配置された第１及び第２の乾燥部２４Ｅ、２４Ｆと、ウェハＷを搬送する第１及び第２の搬送部２４Ｇ、２４Ｈとを備える。なお、ロールスポンジ洗浄部２４Ａ、２４Ｂ、ペンスポンジ洗浄部２４Ｃ、２４Ｄ、乾燥部２４Ｅ、２４Ｆ、及び、搬送部２４Ｇ、２４Ｈの数や配置は、図２の例に限られず、適宜変更してもよい。なお、ロールスポンジ洗浄部２４Ａ、２４Ｂ、ペンスポンジ洗浄部２４Ｃ、２４Ｄは洗浄ユニットを構成し、乾燥部２４Ｅ、２４Ｆは乾燥ユニットを構成する。 (finishing unit)
The finishing unit 24, as shown in FIG. First and second pen sponge cleaning units 24C and 24D, which are arranged in two upper and lower stages, serve as substrate cleaning devices, and first and second pen sponge cleaning units 24C, 24D, which are arranged in two upper and lower stages, serve as substrate drying devices for drying the wafers W after cleaning. and second drying sections 24E and 24F, and first and second transfer sections 24G and 24H for transferring the wafer W. As shown in FIG. The number and arrangement of the roll sponge cleaning units 24A and 24B, the pen sponge cleaning units 24C and 24D, the drying units 24E and 24F, and the transport units 24G and 24H are not limited to the example shown in FIG. good. The roll sponge cleaning units 24A and 24B and the pen sponge cleaning units 24C and 24D constitute a cleaning unit, and the drying units 24E and 24F constitute a drying unit.
　仕上げユニット２４の各部２４Ａ～２４Ｈは、それぞれが区画された状態で第１及び第２のリニアトランスポータ２３０Ａ、２３０Ｂに沿って、例えば、第１及び第２のロールスポンジ洗浄部２４Ａ、２４Ｂ、第１の搬送部２４Ｇ、第１及び第２のペンスポンジ洗浄部２４Ｃ、２４Ｄ、第２の搬送部２４Ｈ、及び、第１及び第２の乾燥部２４Ｅ、２４Ｆの順（ロード／アンロードユニット２１から遠い順）に配置される。仕上げユニット２４は、研磨処理後のウェハＷに対して、第１及び第２のロールスポンジ洗浄部２４Ａ、２４Ｂのいずれかによる一次洗浄処理、第１及び第２のペンスポンジ洗浄部２４Ｃ、２４Ｄのいずれかによる二次洗浄処理、及び、第１及び第２の乾燥部２４Ｅ、２４Ｆのいずれかによる乾燥処理を順に行う。 Each section 24A to 24H of the finishing unit 24 is divided along the first and second linear transporters 230A and 230B, for example, the first and second roll sponge cleaning sections 24A and 24B, the second 1 conveying section 24G, first and second pen sponge washing sections 24C, 24D, second conveying section 24H, and first and second drying sections 24E, 24F in this order (from the load/unload unit 21 farthest order). The finishing unit 24 subjects the wafer W after the polishing process to primary cleaning processing by either the first and second roll sponge cleaning units 24A and 24B, and the first and second pen sponge cleaning units 24C and 24D. A secondary cleaning process by one of them and a drying process by one of the first and second drying units 24E and 24F are performed in this order.
　ロールスポンジ２４００及びペンスポンジ２４０１は、ＰＶＡ、ナイロン等の合成樹脂で形成され、多孔質構造を有する。ロールスポンジ２４００及びペンスポンジ２４０１は、ウェハＷをスクラブ洗浄するための洗浄具として機能し、第１及び第２のロールスポンジ洗浄部２４Ａ、２４Ｂ、並びに、第１及び第２のペンスポンジ洗浄部２４Ｃ、２４Ｄに交換可能にそれぞれ取り付けられる。 The roll sponge 2400 and pen sponge 2401 are made of synthetic resin such as PVA and nylon, and have a porous structure. The roll sponge 2400 and the pen sponge 2401 function as cleaning tools for scrub cleaning the wafer W, and are the first and second roll sponge cleaning units 24A and 24B and the first and second pen sponge cleaning units 24C. , 24D, respectively.
　第１の搬送部２４Ｇは、上下方向に移動可能な第１の搬送ロボット２４６Ａを備える。第１の搬送ロボット２４６Ａは、基板搬送ユニット２３の仮置き台２３３、第１及び第２のロールスポンジ洗浄部２４Ａ、２４Ｂ、並びに、第１及び第２のペンスポンジ洗浄部２４Ｃ、２４Ｄに対してアクセス可能に構成され、それらの間でウェハＷを受け渡すための上下二段のハンドを備える。例えば、下側ハンドは、洗浄前のウェハＷを受け渡すときに使用され、上側ハンドは、洗浄後のウェハＷを受け渡すときに使用される。仮置き台２３３に対するウェハＷの受け渡しの際には、第２の隔壁２００Ｂに設けられたシャッタ（不図示）が開閉される。 The first transport section 24G includes a first transport robot 246A that can move vertically. The first transport robot 246A operates on the temporary table 233 of the substrate transport unit 23, the first and second roll sponge cleaning units 24A and 24B, and the first and second pen sponge cleaning units 24C and 24D. It is configured to be accessible and has upper and lower two-stage hands for transferring wafers W therebetween. For example, the lower hand is used when transferring wafers W before cleaning, and the upper hand is used when transferring wafers W after cleaning. When the wafer W is transferred to the temporary table 233, a shutter (not shown) provided on the second partition 200B is opened and closed.
　第２の搬送部２４Ｈは、上下方向に移動可能な第２の搬送ロボット２４６Ｂを備える。第２の搬送ロボット２４６Ｂは、第１及び第２のペンスポンジ洗浄部２４Ｃ、２４Ｄ、並びに、第１及び第２の乾燥部２４Ｅ、２４Ｆに対してアクセス可能に構成され、それらの間でウェハＷを受け渡すためのハンドを備える。 The second transport section 24H includes a second transport robot 246B that can move vertically. The second transfer robot 246B is configured to be able to access the first and second pen sponge cleaning units 24C, 24D and the first and second drying units 24E, 24F, between which the wafer W is transferred. Equipped with a hand for passing
　図４は、第１及び第２のロールスポンジ洗浄部２４Ａ、２４Ｂの一例を示す斜視図である。第１及び第２のロールスポンジ洗浄部２４Ａ、２４Ｂの基本的な構成や機能は共通する。図４の例では、第１及び第２のロールスポンジ洗浄部２４Ａ、２４Ｂは、ウェハＷの被洗浄面（表面及び裏面）を挟み込むように、上下に配置された一対のロールスポンジ２４００を有する。 FIG. 4 is a perspective view showing an example of the first and second roll sponge cleaning parts 24A, 24B. The basic configurations and functions of the first and second roll sponge cleaning units 24A and 24B are common. In the example of FIG. 4, the first and second roll sponge cleaning units 24A and 24B have a pair of roll sponges 2400 arranged vertically so as to sandwich the surfaces to be cleaned (front and back surfaces) of the wafer W.
　第１及び第２のロールスポンジ洗浄部２４Ａ、２４Ｂの各々は、ウェハＷを保持する基板保持部２４１と、ウェハＷに基板洗浄流体を供給する洗浄流体供給部２４２と、ロールスポンジ２４００を回転可能に支持するとともにロールスポンジ２４００をウェハＷに接触させてウェハＷを洗浄する基板洗浄部２４０と、ロールスポンジ２４００を洗浄具洗浄流体にて洗浄（セルフクリーニング）する洗浄具洗浄部２４３と、洗浄処理が行われるハウジング２０の内部空間の状態を測定する環境センサ２４４とを備える。 Each of the first and second roll sponge cleaning units 24A and 24B can rotate a substrate holding unit 241 that holds the wafer W, a cleaning fluid supply unit 242 that supplies substrate cleaning fluid to the wafer W, and a roll sponge 2400. a substrate cleaning unit 240 that supports the substrate and cleans the wafer W by bringing the roll sponge 2400 into contact with the wafer W; a cleaning tool cleaning unit 243 that cleans (self-cleans) the roll sponge 2400 with a cleaning tool cleaning fluid; and an environment sensor 244 that measures the condition of the internal space of the housing 20 where the operation is performed.
　基板保持部２４１は、ウェハＷの側縁部の複数個所を保持する基板保持機構部２４１ａと、ウェハＷの被洗浄面に垂直な第３の回転軸周りにウェハＷを回転させる基板回転機構部２４１ｂとを備える。図４の例では、基板保持機構部２４１ａは、２つの従動ローラであり、少なくとも１つの従動ローラは、ウェハＷの側縁部に対して保持方向又は離間方向に移動可能に構成される。基板回転機構部２４１ｂは、２つの駆動ローラである。なお、基板保持部２４１は、複数の従動ローラで構成される基板保持機構部２４１ａと、少なくとも１つの駆動ローラで構成される基板回転機構部２４１ｂでよい。 The substrate holding unit 241 includes a substrate holding mechanism unit 241a that holds a plurality of locations on the side edge of the wafer W, and a substrate rotation mechanism unit that rotates the wafer W around a third rotation axis perpendicular to the surface to be cleaned of the wafer W. 241b. In the example of FIG. 4, the substrate holding mechanism part 241a is two driven rollers, and at least one driven roller is configured to be movable with respect to the side edge of the wafer W in the holding direction or separation direction. The substrate rotation mechanism part 241b is two drive rollers. The substrate holding section 241 may be a substrate holding mechanism section 241a composed of a plurality of driven rollers and a substrate rotation mechanism section 241b composed of at least one driving roller.
　洗浄流体供給部２４２は、ウェハＷの被洗浄面に基板洗浄流体を供給する洗浄流体供給ノズル２４２ａと、洗浄流体供給ノズル２４２ａを旋回移動させる揺動移動機構部２４２ｂと、洗浄流体供給ノズル２４２ａを上下移動させる上下移動機構部２４２ｃと、基板洗浄流体の流量及び圧力を調節する流量調節部２４２ｄと、基板洗浄流体の温度を調節する温調機構部２４２ｅとを備える。洗浄流体供給ノズル２４２ａは、基板処理流体供給部を構成する。基板洗浄流体は、純水（リンス液）及び薬液のいずれでもよく、洗浄流体供給ノズル２４２ａは、図４に示すように、純水用のノズルと、薬液用のノズルとが別々に設けられていてもよい。また、基板洗浄流体は、液体でもよいし、液体及び気体を混合させた二流体でもよいし、ドライアイスのような固体を含むものでもよい。 The cleaning fluid supply unit 242 includes a cleaning fluid supply nozzle 242a that supplies the substrate cleaning fluid to the surface to be cleaned of the wafer W, a swing movement mechanism 242b that swivels the cleaning fluid supply nozzle 242a, and the cleaning fluid supply nozzle 242a. It includes a vertical movement mechanism 242c for vertical movement, a flow control unit 242d for adjusting the flow rate and pressure of the substrate cleaning fluid, and a temperature control mechanism 242e for adjusting the temperature of the substrate cleaning fluid. The cleaning fluid supply nozzle 242a constitutes a substrate processing fluid supply section. The substrate cleaning fluid may be either pure water (rinse liquid) or chemical solution, and the cleaning fluid supply nozzle 242a is provided with separate nozzles for pure water and chemical solutions, as shown in FIG. may Also, the substrate cleaning fluid may be a liquid, a two-fluid mixture of a liquid and a gas, or may contain a solid such as dry ice.
　基板洗浄部２４０は、ウェハＷの被洗浄面に平行な第１の回転軸周りにロールスポンジ２４００を回転させる洗浄具回転機構部２４０ａと、一対のロールスポンジ２４００の高さ及び両者の離間距離を変更するため、一対のロールスポンジ２４００の少なくとも一方を上下方向に移動させる上下移動機構部２４０ｂと、一対のロールスポンジ２４００を水平方向に直線移動させる直線移動機構部２４０ｃとを備える。上下移動機構部２４０ｂ及び直線移動機構部２４０ｃは、ロールスポンジ２４００とウェハＷの被洗浄面との相対位置を移動させる洗浄具移動機構部として機能する。 The substrate cleaning section 240 includes a cleaning tool rotation mechanism section 240a that rotates the roll sponge 2400 around a first rotation axis parallel to the surface to be cleaned of the wafer W, and the height of the pair of roll sponges 2400 and the separation distance between the two. For change, a vertical movement mechanism 240b for vertically moving at least one of the pair of roll sponges 2400 and a linear movement mechanism 240c for linearly moving the pair of roll sponges 2400 in the horizontal direction are provided. The vertical movement mechanism portion 240b and the linear movement mechanism portion 240c function as a cleaning tool movement mechanism portion that moves the relative positions of the roll sponge 2400 and the surface of the wafer W to be cleaned.
　洗浄具洗浄部２４３は、ウェハＷと干渉しない位置に配置されて、洗浄具洗浄流体を貯留及び排出可能な洗浄具洗浄槽２４３ａと、洗浄具洗浄槽２４３ａに収容されて、ロールスポンジ２４００が押し付けられる洗浄具洗浄板２４３ｂと、洗浄具洗浄槽２４３ａに供給される洗浄具洗浄流体の流量及び圧力を調節する流量調節部２４３ｃと、ロールスポンジ２４００の内側を流通し、ロールスポンジ２４００の外周面から外部に排出される洗浄具洗浄流体の流量及び圧力を調節する流量調節部２４３ｄとを備える。洗浄具洗浄流体は、純水（リンス液）及び薬液のいずれでもよい。 The cleaning tool cleaning part 243 is arranged at a position not interfering with the wafer W, and accommodated in the cleaning tool cleaning tank 243a capable of storing and discharging the cleaning tool cleaning fluid and the cleaning tool cleaning tank 243a. a cleaning tool cleaning plate 243b, a flow control unit 243c for adjusting the flow rate and pressure of the cleaning tool cleaning fluid supplied to the cleaning tool cleaning tank 243a, and a flow control unit 243c for regulating the flow rate and pressure of the cleaning tool cleaning fluid supplied to the cleaning tool cleaning tank 243a; A flow control unit 243d is provided to control the flow rate and pressure of the cleaning tool cleaning fluid discharged to the outside. The cleaning tool cleaning fluid may be pure water (rinse liquid) or chemical solution.
　環境センサ２４４は、例えば、温度センサ２４４ａと、湿度センサ２４４ｂとを備える。なお、環境センサ２４４として、洗浄処理中や洗浄処理の前後に、ウェハＷやロールスポンジ２４００の表面等を撮影可能なカメラ（イメージセンサ）を備えていてもよい。 The environment sensor 244 includes, for example, a temperature sensor 244a and a humidity sensor 244b. As the environment sensor 244, a camera (image sensor) capable of photographing the surface of the wafer W, the roll sponge 2400, etc. during the cleaning process or before and after the cleaning process may be provided.
　第１及び第２のロールスポンジ洗浄部２４Ａ、２４Ｂによる一次洗浄処理では、ウェハＷは、基板保持機構部２４１ａにより保持された状態で基板回転機構部２４１ｂにより回転される。そして、洗浄流体供給ノズル２４２ａからウェハＷの被洗浄面に基板洗浄流体が供給された状態で、洗浄具回転機構部２４０ａにより軸心周りに回転されたロールスポンジ２４００がウェハＷの被洗浄面に摺接することでウェハＷは洗浄される。その後、基板洗浄部２４０が、ロールスポンジ２４００を洗浄具洗浄槽２４３ａに移動させて、例えば、ロールスポンジ２４００を回転させたり、洗浄具洗浄板２４３ｂに押し付けたり、流量調節部２４３ｄにより洗浄具洗浄流体をロールスポンジ２４００に供給することで、ロールスポンジ２４００は洗浄される。 In the primary cleaning process by the first and second roll sponge cleaning units 24A and 24B, the wafer W is rotated by the substrate rotating mechanism 241b while being held by the substrate holding mechanism 241a. Then, in a state in which the substrate cleaning fluid is supplied to the surface to be cleaned of the wafer W from the cleaning fluid supply nozzle 242a, the roll sponge 2400 rotated around the axis by the cleaning tool rotation mechanism 240a is applied to the surface to be cleaned of the wafer W. The wafer W is cleaned by the sliding contact. After that, the substrate cleaning unit 240 moves the roll sponge 2400 to the cleaning tool cleaning tank 243a, for example, rotates the roll sponge 2400, presses it against the cleaning tool cleaning plate 243b, or controls the cleaning tool cleaning fluid by the flow control unit 243d. is supplied to the roll sponge 2400, the roll sponge 2400 is cleaned.
　図５は、第１及び第２のペンスポンジ洗浄部２４Ｃ、２４Ｄの一例を示す斜視図である。第１及び第２のペンスポンジ洗浄部２４Ｃ、２４Ｄの基本的な構成や機能は共通する。 FIG. 5 is a perspective view showing an example of the first and second pen sponge cleaning units 24C and 24D. The basic configurations and functions of the first and second pen sponge cleaning units 24C and 24D are common.
　第１及び第２のペンスポンジ洗浄部２４Ｃ、２４Ｄの各々は、ウェハＷを保持する基板保持部２４１と、ウェハＷに基板洗浄流体を供給する洗浄流体供給部２４２と、ペンスポンジ２４０１を回転可能に支持するとともにペンスポンジ２４０１をウェハＷに接触させてウェハＷを洗浄する基板洗浄部２４０と、ペンスポンジ２４０１を洗浄具洗浄流体にて洗浄（セルフクリーニング）する洗浄具洗浄部２４３と、洗浄処理が行われるハウジング２０の内部空間の状態を測定する環境センサ２４４とを備える。以下では、ペンスポンジ洗浄部２４Ｃ、２４Ｄについて、ロールスポンジ洗浄部２４Ａ、２４Ｂと異なる部分を中心に説明する。 Each of the first and second pen sponge cleaning units 24C and 24D can rotate a substrate holding unit 241 that holds the wafer W, a cleaning fluid supply unit 242 that supplies substrate cleaning fluid to the wafer W, and a pen sponge 2401. A substrate cleaning unit 240 that supports the substrate and cleans the wafer W by bringing the pen sponge 2401 into contact with the wafer W, a cleaning tool cleaning unit 243 that cleans (self-cleans) the pen sponge 2401 with cleaning fluid, and a cleaning process and an environment sensor 244 that measures the condition of the internal space of the housing 20 where the operation is performed. The pen sponge cleaning units 24C and 24D will be described below, focusing on the differences from the roll sponge cleaning units 24A and 24B.
　基板保持部２４１は、ウェハＷの側縁部の複数個所を保持する基板保持機構部２４１ｃと、ウェハＷの被洗浄面に垂直な第３の回転軸周りにウェハＷを回転させる基板回転機構部２４１ｄとを備える。図５の例では、基板保持機構部２４１ｃは、２つの従動ローラであり、少なくとも１つの従動ローラは、ウェハＷの側縁部に対して保持方向又は離間方向に移動可能に構成され、基板回転機構部２４１ｄは、２つの駆動ローラである。なお、基板保持部２４１は、複数の従動ローラで構成される基板保持機構部２４１ｃと、少なくとも１つの駆動ローラで構成される基板回転機構部２４１ｄでよい。 The substrate holding part 241 includes a substrate holding mechanism part 241c that holds a plurality of positions on the side edge of the wafer W, and a substrate rotation mechanism part that rotates the wafer W around a third rotation axis perpendicular to the surface to be cleaned of the wafer W. 241d. In the example of FIG. 5, the substrate holding mechanism part 241c is two driven rollers, and at least one driven roller is configured to be movable in the holding direction or the separation direction with respect to the side edge of the wafer W, thereby rotating the substrate. The mechanism part 241d is two drive rollers. The substrate holding section 241 may be a substrate holding mechanism section 241c composed of a plurality of driven rollers and a substrate rotation mechanism section 241d composed of at least one driving roller.
　洗浄流体供給部２４２は、図４と同様に構成されており、洗浄流体供給ノズル２４２ａ、揺動移動機構部２４２ｂ、上下移動機構部２４２ｃ、流量調節部２４２ｄ、及び、温調機構部２４２ｅを備える。洗浄流体供給ノズル２４２ａは、基板処理流体供給部を構成する。 The cleaning fluid supply unit 242 is configured in the same manner as in FIG. 4, and includes a cleaning fluid supply nozzle 242a, a rocking movement mechanism unit 242b, a vertical movement mechanism unit 242c, a flow control unit 242d, and a temperature control mechanism unit 242e. . The cleaning fluid supply nozzle 242a constitutes a substrate processing fluid supply section.
　基板洗浄部２４０は、ウェハＷの被洗浄面に垂直な第２の回転軸周りにペンスポンジ２４０１を回転させる洗浄具回転機構部２４０ｄと、ペンスポンジ２４０１を上下方向に移動させる上下移動機構部２４０ｅと、ペンスポンジ２４０１を水平方向に旋回移動させる揺動移動機構部２４０ｆとを備える。上下移動機構部２４０ｅ及び揺動移動機構部２４０ｆは、ペンスポンジ２４０１とウェハＷの被洗浄面との相対位置を移動させる洗浄具移動機構部として機能する。 The substrate cleaning section 240 includes a cleaning tool rotation mechanism section 240d that rotates the pen sponge 2401 around a second rotation axis perpendicular to the surface to be cleaned of the wafer W, and a vertical movement mechanism section 240e that vertically moves the pen sponge 2401. and a rocking movement mechanism 240f for rotating and moving the pen sponge 2401 in the horizontal direction. The vertical movement mechanism portion 240e and the swing movement mechanism portion 240f function as a cleaning tool movement mechanism portion that moves the relative positions of the pen sponge 2401 and the surface of the wafer W to be cleaned.
　洗浄具洗浄部２４３は、ウェハＷと干渉しない位置に配置されて、洗浄具洗浄流体を貯留及び排出可能な洗浄具洗浄槽２４３ｅと、洗浄具洗浄槽２４３ｅに収容されて、ペンスポンジ２４０１が押し付けられる洗浄具洗浄板２４３ｆと、洗浄具洗浄槽２４３ｅに供給される洗浄具洗浄流体の流量及び圧力を調節する流量調節部２４３ｇと、ペンスポンジ２４０１の内側を流通し、ペンスポンジ２４０１の外表面から外部に排出される洗浄具洗浄流体の流量及び圧力を調節する流量調節部２４３ｈとを備える。 The cleaning tool cleaning part 243 is arranged at a position not interfering with the wafer W, and accommodated in the cleaning tool cleaning tank 243e capable of storing and discharging the cleaning tool cleaning fluid, and the cleaning tool cleaning tank 243e. a cleaning tool cleaning plate 243f, a flow control unit 243g for adjusting the flow rate and pressure of the cleaning tool cleaning fluid supplied to the cleaning tool cleaning tank 243e, A flow control unit 243h is provided to control the flow rate and pressure of the cleaning tool cleaning fluid discharged to the outside.
　環境センサ２４４は、例えば、温度センサ２４４ａと、湿度センサ２４４ｂとを備える。なお、環境センサ２４４として、洗浄処理中や洗浄処理の前後に、ウェハＷやペンスポンジ２４０１の表面等を撮影可能なカメラ（イメージセンサ）を備えていてもよい。 The environment sensor 244 includes, for example, a temperature sensor 244a and a humidity sensor 244b. As the environment sensor 244, a camera (image sensor) capable of photographing the surface of the wafer W, the pen sponge 2401, etc. during the cleaning process or before and after the cleaning process may be provided.
　第１及び第２のペンスポンジ洗浄部２４Ｃ、２４Ｄによる二次洗浄処理では、ウェハＷは、基板保持機構部２４１ｃにより保持された状態で基板回転機構部２４１ｄにより回転される。そして、洗浄流体供給ノズル２４２ａからウェハＷの被洗浄面に基板洗浄流体が供給された状態で、洗浄具回転機構部２４０ｄにより軸心周りに回転されたペンスポンジ２４０１がウェハＷの被洗浄面に摺接することでウェハＷは洗浄される。その後、基板洗浄部２４０が、ペンスポンジ２４０１を洗浄具洗浄槽２４３ｅに移動させて、例えば、ペンスポンジ２４０１を回転させたり、洗浄具洗浄板２４３ｆに押し付けたり、流量調節部２４３ｈにより洗浄具洗浄流体をペンスポンジ２４０１に供給することで、ペンスポンジ２４０１は洗浄される。 In the secondary cleaning process by the first and second pen sponge cleaning units 24C and 24D, the wafer W is rotated by the substrate rotating mechanism 241d while being held by the substrate holding mechanism 241c. Then, while the substrate cleaning fluid is being supplied from the cleaning fluid supply nozzle 242a to the surface to be cleaned of the wafer W, the pen sponge 2401 rotated around the axis by the cleaning tool rotation mechanism 240d is applied to the surface to be cleaned of the wafer W. The wafer W is cleaned by the sliding contact. After that, the substrate cleaning unit 240 moves the pen sponge 2401 to the cleaning tool cleaning tank 243e, for example, rotates the pen sponge 2401, presses it against the cleaning tool cleaning plate 243f, or controls the cleaning tool cleaning fluid by the flow control unit 243h. is supplied to the pen sponge 2401 to clean the pen sponge 2401 .
　図６は、第１及び第２の乾燥部２４Ｅ、２４Ｆの一例を示す斜視図である。第１及び第２の乾燥部２４Ｅ、２４Ｆの基本的な構成や機能は共通する。 FIG. 6 is a perspective view showing an example of the first and second drying sections 24E, 24F. The basic configurations and functions of the first and second drying sections 24E and 24F are common.
　第１及び第２の乾燥部２４Ｅ、２４Ｆの各々は、ウェハＷを保持する基板保持部２４１と、ウェハＷに基板乾燥流体を供給する乾燥流体供給部２４５と、乾燥処理が行われるハウジング２０の内部空間の状態を測定する環境センサ２４４とを備える。 Each of the first and second drying sections 24E and 24F includes a substrate holding section 241 that holds the wafer W, a drying fluid supply section 245 that supplies the substrate drying fluid to the wafer W, and the housing 20 where the drying process is performed. and an environment sensor 244 that measures the state of the interior space.
　基板保持部２４１は、ウェハＷの側縁部の複数個所を保持する基板保持機構部２４１ｅと、ウェハＷの被洗浄面に垂直な第３の回転軸周りにウェハＷを回転させる基板回転機構部２４１ｇとを備える。基板保持機構部２４１ｅは、一端を上下方向に移動する上下移動機構部２４１ｆに対して水平軸を中心として回動するように設置され、他端をウェハＷの周縁部に対して接離可能なチャック等の把持部に形成される。基板保持機構部２４１ｅは、上下移動機構２４１ｆの上下方向への移動に伴い、把持部がウェハＷに対して当接又は分離方向に移動する傘機構を構成する。なお、把持部は、ローラで構成してもよい。 The substrate holding unit 241 includes a substrate holding mechanism unit 241e that holds a plurality of positions on the side edge of the wafer W, and a substrate rotation mechanism unit that rotates the wafer W around a third rotation axis perpendicular to the surface to be cleaned of the wafer W. 241g. The substrate holding mechanism part 241e is installed such that one end thereof rotates about a horizontal axis with respect to the vertical movement mechanism part 241f that moves in the vertical direction, and the other end can be brought into contact with and separated from the peripheral edge of the wafer W. It is formed in a gripping part such as a chuck. The substrate holding mechanism part 241e constitutes an umbrella mechanism in which the gripping part moves in contact with the wafer W or in the separation direction as the vertical movement mechanism 241f moves in the vertical direction. Note that the gripping portion may be configured by a roller.
　乾燥流体供給部２４５は、ウェハＷの被洗浄面に基板乾燥流体を供給する乾燥流体供給ノズル２４５ａと、乾燥流体供給ノズル２４５ａを上下方向に移動させる上下移動機構部２４５ｂと、乾燥流体供給ノズル２４５ａを水平方向に旋回移動させる揺動移動機構部２４５ｃと、基板乾燥流体の流量及び圧力を調節する流量調節部２４５ｄと、基板乾燥流体の温度を調節する温調機構部２４５ｅとを備える。乾燥流体供給ノズル２４５ａは、基板処理流体供給部を構成する。上下移動機構部２４５ｂ及び揺動移動機構部２４５ｃは、乾燥流体供給ノズル２４５ａとウェハＷの被洗浄面との相対位置を移動させる乾燥流体供給ノズル移動機構部として機能する。 The dry fluid supply unit 245 includes a dry fluid supply nozzle 245a that supplies the substrate dry fluid to the surface to be cleaned of the wafer W, a vertical movement mechanism unit 245b that vertically moves the dry fluid supply nozzle 245a, and the dry fluid supply nozzle 245a. , a flow control unit 245d for adjusting the flow rate and pressure of the substrate drying fluid, and a temperature control mechanism unit 245e for adjusting the temperature of the substrate drying fluid. The dry fluid supply nozzle 245a constitutes a substrate processing fluid supply section. The vertical movement mechanism portion 245b and the rocking movement mechanism portion 245c function as a drying fluid supply nozzle movement mechanism portion that moves the relative positions of the drying fluid supply nozzle 245a and the surface of the wafer W to be cleaned.
　基板乾燥流体は、例えば、ＩＰＡ蒸気及び純水（リンス液）であり、乾燥流体供給ノズル２４５ａは、図６に示すように、ＩＰＡ蒸気用のノズルと、純水用のノズルとが別々に設けられていてもよい。また、基板乾燥流体は、液体でもよいし、液体及び気体を混合させた二流体でもよいし、ドライアイスのような固体を含むものでもよい。 The substrate drying fluid is, for example, IPA vapor and pure water (rinse liquid), and as shown in FIG. may have been Also, the substrate drying fluid may be a liquid, a two-fluid mixture of a liquid and a gas, or a solid such as dry ice.
　環境センサ２４４は、温度センサ２４４ａと、湿度センサ２４４ｂとを備える。なお、環境センサ２４４として、乾燥処理中や乾燥処理の前後に、ウェハＷの表面等を撮影可能なカメラ（イメージセンサ）を備えていてもよい。 The environment sensor 244 includes a temperature sensor 244a and a humidity sensor 244b. As the environment sensor 244, a camera (image sensor) capable of photographing the surface of the wafer W, etc. during the drying process or before and after the drying process may be provided.
　第１及び第２の乾燥部２４Ｅ、２４Ｆによる乾燥処理では、ウェハＷは、基板保持機構部２４１ｅにより保持された状態で基板回転機構部２４１ｇにより回転される。そして、乾燥流体供給ノズル２４５ａからウェハＷの被洗浄面に基板乾燥流体が供給された状態で、乾燥流体供給ノズル２４５ａがウェハＷの側縁部側（径方向外側）に移動される。その後、ウェハＷは、基板回転機構部２４１ｅにより高速回転されることでウェハＷが乾燥される。 In the drying process by the first and second drying units 24E and 24F, the wafer W is rotated by the substrate rotating mechanism 241g while being held by the substrate holding mechanism 241e. Then, the drying fluid supply nozzle 245a is moved toward the side edge of the wafer W (outside in the radial direction) while the substrate drying fluid is being supplied from the drying fluid supply nozzle 245a to the surface of the wafer W to be cleaned. After that, the wafer W is dried by being rotated at high speed by the substrate rotation mechanism section 241e.
　なお、図４乃至図６では、基板保持機構部２４１ａ、２４１ｃ、２４１ｅ、基板回転機構部２４１ｂ、２４１ｄ、２４１ｇ、上下移動機構部２４０ｂ、２４０ｅ、２４１ｆ、２４２ｂ、２４５ｂ、直線移動機構部２４０ｃ、揺動移動機構部２４０ｆ、２４２ｃ、２４５ｃ、洗浄具回転機構部２４０ａ、２４０ｄの具体的な構成を省略しているが、例えば、モータ、エアシリンダ等の駆動力発生用のモジュールと、リニアガイド、ボールねじ、ギヤ、ベルト、カップリング、軸受等の駆動力伝達機構と、リニアセンサ、エンコーダセンサ、リミットセンサ、トルクセンサ等のセンサとを適宜組み合わせて構成される。 4 to 6, the substrate holding mechanism units 241a, 241c, and 241e, the substrate rotation mechanism units 241b, 241d, and 241g, the vertical movement mechanism units 240b, 240e, 241f, 242b, and 245b, the linear movement mechanism unit 240c, Although the specific configurations of the dynamic movement mechanisms 240f, 242c, and 245c and the cleaning tool rotation mechanisms 240a and 240d are omitted, for example, modules for generating driving force such as motors and air cylinders, linear guides, ball It is configured by appropriately combining driving force transmission mechanisms such as screws, gears, belts, couplings, and bearings, and sensors such as linear sensors, encoder sensors, limit sensors, and torque sensors.
　また、図４乃至図６では、流量調節部２４３ｃ、２４３ｄ、２４３ｇ、２４３ｈ、２４５ｄの具体的な構成を省略しているが、例えば、ポンプ、バルブ、レギュレータ等の流体調節用のモジュールと、流量センサ、圧力センサ、液面センサ等のセンサとを適宜組み合わせて構成される。図４乃至図６では、温調機構部２４２ｄ、２４５ｅの具体的な構成を省略しているが、例えば、ヒータ、熱交換器等の温度調節用（接触式又は非接触式）のモジュールと、温度センサ、電流センサ等のセンサとを適宜組み合わせて構成される。 4 to 6 omit specific configurations of the flow control units 243c, 243d, 243g, 243h, and 245d. It is configured by appropriately combining sensors such as a sensor, a pressure sensor, and a liquid level sensor. 4 to 6 omit the specific configuration of the temperature control mechanism units 242d and 245e, but for example, temperature control (contact or non-contact) modules such as heaters and heat exchangers, It is configured by appropriately combining sensors such as a temperature sensor and a current sensor.
（膜厚測定ユニット）
　膜厚測定ユニット２５は、研磨処理前又は研磨処理後のウェハＷの膜厚を測定する測定器であり、例えば、光学式膜厚測定器、渦電流式膜厚測定器等で構成される。各膜厚測定モジュールに対するウェハＷの受け渡しは、搬送ロボット２１１により行われる。 (film thickness measurement unit)
The film thickness measurement unit 25 is a measuring device for measuring the film thickness of the wafer W before or after polishing, and is composed of, for example, an optical film thickness measuring device, an eddy current film thickness measuring device, or the like. Transfer of the wafer W to each film thickness measurement module is performed by the transfer robot 211 .
（基板処理流体供給弁）
　図７は、基板処理流体供給系統における基板処理流体供給弁の配置を示す図である。なお、図７は、タンク、ポンプ、モータ等を省略している。 (substrate processing fluid supply valve)
FIG. 7 is a diagram showing the arrangement of substrate processing fluid supply valves in the substrate processing fluid supply system. Note that FIG. 7 omits tanks, pumps, motors, and the like.
　研磨流体供給系統２７は、研磨流体供給源２７０から研磨流体供給ノズル２２２へ研磨流体を供給する。研磨流体供給系統２７において、第１研磨流体供給弁２７１は１つの研磨流体供給源２７０の下流における全ての基板処理装置２の上流に１つ配置され、第２研磨流体供給弁２７２は１つの基板処理装置２の下流における全ての研磨ユニット２２の上流に１つ配置され、第３研磨流体供給弁２７２は１つの研磨ユニット２２の下流における全ての研磨流体供給ノズル２２２の上流に１つ配置される。 The polishing fluid supply system 27 supplies polishing fluid from a polishing fluid supply source 270 to the polishing fluid supply nozzle 222 . In the polishing fluid supply system 27, one first polishing fluid supply valve 271 is arranged upstream of all the substrate processing apparatuses 2 downstream of one polishing fluid supply source 270, and one second polishing fluid supply valve 272 is arranged for one substrate. One third polishing fluid supply valve 272 is arranged upstream of all polishing units 22 downstream of the processing apparatus 2, and one third polishing fluid supply valve 272 is arranged upstream of all polishing fluid supply nozzles 222 downstream of one polishing unit 22. .
　研磨流体供給系統２７において、研磨流体は、研磨流体供給源２７０から第１研磨流体供給弁２７１を通過して１又は複数の各基板処理装置２へ供給され、第２研磨流体供給弁２７２を通過して１又は複数の研磨ユニット２２へ供給され、第３研磨流体供給弁２７３を通過して１又は複数の研磨流体ノズル２２２へ供給され、研磨流体ノズル２２２から吐出される。 In the polishing fluid supply system 27 , polishing fluid is supplied from a polishing fluid supply source 270 through a first polishing fluid supply valve 271 to each of the one or more substrate processing apparatuses 2 , and then through a second polishing fluid supply valve 272 . The polishing fluid is then supplied to one or more polishing units 22 , passes through the third polishing fluid supply valve 273 , is supplied to one or more polishing fluid nozzles 222 , and is discharged from the polishing fluid nozzles 222 .
　洗浄流体供給系統２８は、洗浄流体供給源２８０から洗浄流体供給ノズル２２２へ洗浄流体を供給する。洗浄流体供給系統２８において、第１洗浄流体供給弁２８１は１つの洗浄流体供給源２８０の下流における全ての基板処理装置２の上流に１つ配置され、第２洗浄流体供給弁２８２は１つの基板処理装置２の下流における全ての洗浄ユニット２４Ａ～２４Ｄの上流に１つ配置され、第３洗浄流体供給弁２８２は１つの洗浄ユニット２４Ａ～２４Ｄの下流における全ての洗浄流体供給ノズル２４２ａの上流に１つ配置される。 The cleaning fluid supply system 28 supplies cleaning fluid from a cleaning fluid supply source 280 to the cleaning fluid supply nozzles 222 . In the cleaning fluid supply system 28, one first cleaning fluid supply valve 281 is arranged upstream of all the substrate processing apparatuses 2 downstream of one cleaning fluid supply source 280, and one second cleaning fluid supply valve 282 is arranged for one substrate. A third cleaning fluid supply valve 282 is arranged one upstream of all cleaning units 24A-24D downstream of the processing apparatus 2, and one third cleaning fluid supply valve 282 is located one upstream of all cleaning fluid supply nozzles 242a downstream of one cleaning unit 24A-24D. are placed.
　洗浄流体供給系統２８において、洗浄流体は、洗浄流体供給源２８０から第１洗浄流体供給弁２８１を通過して１又は複数の各基板処理装置２へ供給され、第２洗浄流体供給弁２８２を通過して１又は複数の洗浄ユニット２２へ供給され、第３洗浄流体供給弁２８３を通過して１又は複数の洗浄流体ノズル２４２ａへ供給され、洗浄流体ノズル２４２ａから吐出される。 In the cleaning fluid supply system 28 , cleaning fluid is supplied from a cleaning fluid supply source 280 through a first cleaning fluid supply valve 281 to each of the one or more substrate processing apparatuses 2 and then through a second cleaning fluid supply valve 282 . Then, it is supplied to one or more cleaning units 22, passes through the third cleaning fluid supply valve 283, is supplied to one or more cleaning fluid nozzles 242a, and is discharged from the cleaning fluid nozzles 242a.
　乾燥流体供給系統２９は、乾燥流体供給源２９０から乾燥流体供給ノズル２２２へ乾燥流体を供給する。乾燥流体供給系統２９において、第１乾燥流体供給弁２９１は１つの乾燥流体供給源２９０の下流における全ての基板処理装置２の上流に１つ配置され、第２乾燥流体供給弁２９２は１つの基板処理装置２の下流における全ての乾燥ユニット２４Ｅ、２４Ｆの上流に１つ配置され、第３乾燥流体供給弁２９２は１つの乾燥ユニット２４Ｅ、２４Ｆの下流における全ての乾燥流体供給ノズル２４５ａの上流に１つ配置される。 The dry fluid supply system 29 supplies dry fluid from the dry fluid supply source 290 to the dry fluid supply nozzle 222 . In the drying fluid supply system 29, one first drying fluid supply valve 291 is arranged upstream of all the substrate processing apparatuses 2 downstream of one drying fluid supply source 290, and one second drying fluid supply valve 292 is arranged for one substrate. A third drying fluid supply valve 292 is arranged upstream of all the drying units 24E, 24F downstream of the processing apparatus 2, and a third drying fluid supply valve 292 is positioned upstream of all drying fluid supply nozzles 245a downstream of one drying unit 24E, 24F. are placed.
　乾燥流体供給系統２９において、乾燥流体は、乾燥流体供給源２９０から第１乾燥流体供給弁２９１を通過して１又は複数の各基板処理装置２へ供給され、第２乾燥流体供給弁２９２を通過して１又は複数の乾燥ユニット２４Ｅ、２４Ｆへ供給され、第３乾燥流体供給弁２９３を通過して１又は複数の乾燥流体ノズル２４５ａへ供給され、乾燥流体ノズル２４５ａから吐出される。 In the drying fluid supply system 29 , the drying fluid is supplied from the drying fluid supply source 290 through the first drying fluid supply valve 291 to each of the one or more substrate processing apparatuses 2 and then through the second drying fluid supply valve 292 . Then, it is supplied to one or more drying units 24E, 24F, passes through the third drying fluid supply valve 293, is supplied to one or more drying fluid nozzles 245a, and is discharged from the drying fluid nozzles 245a.
（制御ユニット）
　図８は、基板処理装置２の一例を示すブロック図である。制御ユニット２６は、各ユニット２１～２５と電気的に接続されて、各ユニット２１～２５を統括的に制御する制御部として機能する。以下では、仕上げユニット２４の制御系（モジュール、センサ、シーケンサ）を例にして説明するが、他のユニット２１～２３、２５も基本的な構成や機能は共通するため、説明を省略する。 (Controller unit)
FIG. 8 is a block diagram showing an example of the substrate processing apparatus 2. As shown in FIG. The control unit 26 is electrically connected to each of the units 21 to 25 and functions as a control section that controls the units 21 to 25 in an integrated manner. The control system (modules, sensors, sequencers) of the finishing unit 24 will be described below as an example, but since the other units 21 to 23 and 25 have the same basic configuration and functions, their description will be omitted.
　仕上げユニット２４は、仕上げユニット２４が備える各サブユニット（例えば、第１及び第２のロールスポンジ洗浄部２４Ａ、２４Ｂ、第１及び第２のペンスポンジ洗浄部２４Ｃ、２４Ｄ、第１及び第２の乾燥部２４Ｅ、２４Ｆ、第１及び第２の搬送部２４Ｇ、２４Ｈ等）にそれぞれ配置されて、制御対象となる複数のモジュール２４７１～２４７ｒと、複数のモジュール２４７１～２４７ｒにそれぞれ配置されて、各モジュール２４７１～２４７ｒの制御に必要なデータ（検出値）を検出する複数のセンサ２４８１～２４８ｓと、各センサ２４８１～２４８ｓの検出値に基づいて各モジュール２４７１～２４７ｒの動作を制御するシーケンサ２４９とを備える。 The finishing unit 24 includes subunits provided in the finishing unit 24 (for example, first and second roll sponge cleaning units 24A and 24B, first and second pen sponge cleaning units 24C and 24D, first and second Drying units 24E, 24F, first and second conveying units 24G, 24H, etc.), and a plurality of modules 2471 to 247r to be controlled, and a plurality of modules 2471 to 247r, respectively. A plurality of sensors 2481 to 248s for detecting data (detection values) necessary for controlling the modules 2471 to 247r, and a sequencer 249 for controlling the operations of the modules 2471 to 247r based on the detection values of the sensors 2481 to 248s. Prepare.
　仕上げユニット２４のセンサ２４８１～２４８ｓには、例えば、図７に示した基板処理流体供給系統において、洗浄流体供給ノズル２４２ａ又は乾燥流体供給ノズル２４５ａからウェハＷに供給される基板処理流体の供給流量を検出するセンサ、洗浄流体供給ノズル２４２ａ又は乾燥流体供給ノズル２４５ａからウェハＷに供給される基板処理流体の供給圧力を検出するセンサ、洗浄流体供給ノズル２４２ａ又は乾燥流体供給ノズル２４５ａへ流体を供給する供給系統において洗浄流体供給ノズル２４２ａ又は乾燥流体供給ノズル２４５ａの上流に接続され基板処理流体の流量を調整する洗浄流体供給弁２８１～２８３又は乾燥流体供給弁２９１～２９３の状態を検出するセンサ、洗浄流体供給ノズル２４２ａ又は乾燥流体供給ノズル２４５ａへ流体を供給する供給系統において洗浄流体供給ノズル２４２ａ又は乾燥流体供給ノズル２４５ａの上流に接続され基板処理流体の流量を調整する洗浄流体供給弁２８１～２８３又は乾燥流体供給弁２９１～２９３の一次側の圧力を検出するセンサ等が含まれる。 The sensors 2481 to 248s of the finishing unit 24, for example, in the substrate processing fluid supply system shown in FIG. A sensor that detects the supply pressure of the substrate processing fluid supplied to the wafer W from the cleaning fluid supply nozzle 242a or the drying fluid supply nozzle 245a, a supply that supplies the fluid to the cleaning fluid supply nozzle 242a or the drying fluid supply nozzle 245a A sensor for detecting the state of the cleaning fluid supply valves 281 to 283 or the drying fluid supply valves 291 to 293 connected upstream of the cleaning fluid supply nozzle 242a or the drying fluid supply nozzle 245a in the system and adjusting the flow rate of the substrate processing fluid, cleaning fluid Cleaning fluid supply valves 281 to 283 connected upstream of the cleaning fluid supply nozzle 242a or the drying fluid supply nozzle 245a in a supply system for supplying fluid to the supply nozzle 242a or the drying fluid supply nozzle 245a for adjusting the flow rate of the substrate processing fluid or the drying fluid supply nozzle 242a or the drying fluid supply nozzle 245a. A sensor or the like for detecting the pressure on the primary side of the fluid supply valves 291-293 is included.
　制御ユニット２６は、制御部２６０、通信部２６１、入力部２６２、出力部２６３、及び、記憶部２６４を備える。制御ユニット２６は、例えば、汎用又は専用のコンピュータ（後述の図９参照）で構成される。 The control unit 26 includes a control section 260 , a communication section 261 , an input section 262 , an output section 263 and a storage section 264 . The control unit 26 is configured by, for example, a general-purpose or dedicated computer (see FIG. 9 described later).
　通信部２６１は、ネットワーク７に接続され、各種のデータを送受信する通信インターフェースとして機能する。入力部２６２は、各種の入力操作を受け付けるとともに、出力部２６３は、表示画面、シグナルタワー点灯、ブザー音を介して各種の情報を出力することで、ユーザインターフェースとして機能する。 The communication unit 261 is connected to the network 7 and functions as a communication interface for transmitting and receiving various data. The input unit 262 receives various input operations, and the output unit 263 functions as a user interface by outputting various information via the display screen, signal tower lighting, and buzzer sound.
　記憶部２６４は、基板処理装置２の動作で使用される各種のプログラム（オペレーティングシステム（ＯＳ）、アプリケーションプログラム、ウェブブラウザ等）やデータ（装置設定情報２６５、基板レシピ情報２６６等）を記憶する。装置設定情報２６５及び基板レシピ情報２６６は、表示画面を介してユーザにより編集可能なデータである。 The storage unit 264 stores various programs (operating system (OS), application programs, web browsers, etc.) and data (apparatus setting information 265, substrate recipe information 266, etc.) used in the operation of the substrate processing apparatus 2 . The equipment setting information 265 and substrate recipe information 266 are data that can be edited by the user via the display screen.
　制御部２６０は、複数のシーケンサ２１９、２２９、２３９、２４９、２５９（以下、「シーケンサ群」という）を介して複数のセンサ２１８１～２１８ｑ、２２８１～２２８ｓ、２３８１～２３８ｕ、２４８１～２４８ｗ、２５８１～２５８ｙ（以下、「センサ群」という）の検出値を取得するとともに、複数のモジュール２１７１～２１７ｐ、２２７１～２２７ｒ、２３７１～２３７ｔ、２４７１～２４７ｖ、２５７１～２５７ｘ（以下、「モジュール群」という）を連携して動作させることで、ロ―ド、研磨、洗浄、乾燥、膜厚測定、アンロード等の一連の基板処理を行う。 The control unit 260 controls a plurality of sensors 2181 to 218q, 2281 to 228s, 2381 to 238u, 2481 to 248w, 2581 through a plurality of sequencers 219, 229, 239, 249, and 259 (hereinafter referred to as "sequencer group"). 258y (hereinafter referred to as "sensor group"), and a plurality of modules 2171-217p, 2271-227r, 2371-237t, 2471-247v, and 2571-257x (hereinafter referred to as "module group"). A series of substrate processing such as loading, polishing, cleaning, drying, film thickness measurement, and unloading are performed by operating in conjunction with each other.
（各装置のハードウエア構成）
　図９は、コンピュータ９００の一例を示すハードウエア構成図である。基板処理装置２の制御ユニット２６、データベース装置３、機械学習装置４、情報処理装置５、及び、ユーザ端末装置６の各々は、汎用又は専用のコンピュータ９００により構成される。 (Hardware configuration of each device)
FIG. 9 is a hardware configuration diagram showing an example of a computer 900. As shown in FIG. Each of the control unit 26 of the substrate processing apparatus 2, the database device 3, the machine learning device 4, the information processing device 5, and the user terminal device 6 is configured by a general-purpose or dedicated computer 900. FIG.
　コンピュータ９００は、図９に示すように、その主要な構成要素として、バス９１０、プロセッサ９１２、メモリ９１４、入力デバイス９１６、出力デバイス９１７、表示デバイス９１８、ストレージ装置９２０、通信Ｉ／Ｆ（インターフェース）部９２２、外部機器Ｉ／Ｆ部９２４、Ｉ／Ｏ（入出力）デバイスＩ／Ｆ部９２６、及び、メディア入出力部９２８を備える。なお、上記の構成要素は、コンピュータ９００が使用される用途に応じて適宜省略されてもよい。 As shown in FIG. 9, the computer 900 includes, as its main components, a bus 910, a processor 912, a memory 914, an input device 916, an output device 917, a display device 918, a storage device 920, a communication I/F (interface). It has a section 922 , an external equipment I/F section 924 , an I/O (input/output) device I/F section 926 and a media input/output section 928 . Note that the above components may be omitted as appropriate depending on the application for which the computer 900 is used.
　プロセッサ９１２は、１つ又は複数の演算処理装置（ＣＰＵ（Ｃｅｎｔｒａｌ　Ｐｒｏｃｅｓｓｉｎｇ　Ｕｎｉｔ）、ＭＰＵ（Ｍｉｃｒｏ－ｐｒｏｃｅｓｓｉｎｇ　ｕｎｉｔ）、ＤＳＰ（ｄｉｇｉｔａｌ　ｓｉｇｎａｌ　ｐｒｏｃｅｓｓｏｒ）、ＧＰＵ（Ｇｒａｐｈｉｃｓ　Ｐｒｏｃｅｓｓｉｎｇ　Ｕｎｉｔ）等）で構成され、コンピュータ９００全体を統括する制御部として動作する。メモリ９１４は、各種のデータ及びプログラム９３０を記憶し、例えば、メインメモリとして機能する揮発性メモリ（ＤＲＡＭ、ＳＲＡＭ等）と、不揮発性メモリ（ＲＯＭ）、フラッシュメモリ等とで構成される。 The processor 912 is composed of one or more arithmetic processing units (CPU (Central Processing Unit), MPU (Micro-processing unit), DSP (digital signal processor), GPU (Graphics Processing Unit), etc.), and the entire computer 900 It operates as a control unit that supervises the The memory 914 stores various data and programs 930, and is composed of, for example, a volatile memory (DRAM, SRAM, etc.) functioning as a main memory, a non-volatile memory (ROM), a flash memory, and the like.
　入力デバイス９１６は、例えば、キーボード、マウス、テンキー、電子ペン等で構成され、入力部として機能する。出力デバイス９１７は、例えば、音（音声）出力装置、バイブレーション装置等で構成され、出力部として機能する。表示デバイス９１８は、例えば、液晶ディスプレイ、有機ＥＬディスプレイ、電子ペーパー、プロジェクタ等で構成され、出力部として機能する。入力デバイス９１６及び表示デバイス９１８は、タッチパネルディスプレイのように、一体的に構成されていてもよい。ストレージ装置９２０は、例えば、ＨＤＤ、ＳＳＤ（Ｓｏｌｉｄ　Ｓｔａｔｅ　Ｄｒｉｖｅ）等で構成され、記憶部として機能する。ストレージ装置９２０は、オペレーティングシステムやプログラム９３０の実行に必要な各種のデータを記憶する。 The input device 916 is composed of, for example, a keyboard, mouse, numeric keypad, electronic pen, etc., and functions as an input unit. The output device 917 is configured by, for example, a sound (voice) output device, a vibration device, or the like, and functions as an output unit. A display device 918 is configured by, for example, a liquid crystal display, an organic EL display, electronic paper, a projector, or the like, and functions as an output unit. The input device 916 and the display device 918 may be configured integrally like a touch panel display. The storage device 920 is composed of, for example, an HDD, SSD (Solid State Drive), etc., and functions as a storage unit. The storage device 920 stores various data necessary for executing the operating system and programs 930 .
　通信Ｉ／Ｆ部９２２は、インターネットやイントラネット等のネットワーク９４０（図１のネットワーク７と同じであってもよい）に有線又は無線により接続され、所定の通信規格に従って他のコンピュータとの間でデータの送受信を行う通信部として機能する。外部機器Ｉ／Ｆ部９２４は、カメラ、プリンタ、スキャナ、リーダライタ等の外部機器９５０に有線又は無線により接続され、所定の通信規格に従って外部機器９５０との間でデータの送受信を行う通信部として機能する。Ｉ／ＯデバイスＩ／Ｆ部９２６は、各種のセンサ、アクチュエータ等のＩ／Ｏデバイス９６０に接続され、Ｉ／Ｏデバイス９６０との間で、例えば、センサによる検出信号やアクチュエータへの制御信号等の各種の信号やデータの送受信を行う通信部として機能する。メディア入出力部９２８は、例えば、ＤＶＤドライブ、ＣＤドライブ等のドライブ装置で構成され、ＤＶＤ、ＣＤ等のメディア（非一時的な記憶媒体）９７０に対してデータの読み書きを行う。 The communication I/F unit 922 is connected to a network 940 (which may be the same as the network 7 in FIG. 1) such as the Internet or an intranet by wire or wirelessly, and exchanges data with other computers according to a predetermined communication standard. functions as a communication unit that transmits and receives The external device I/F unit 924 is connected to the external device 950 such as a camera, printer, scanner, reader/writer, etc. by wire or wirelessly, and serves as a communication unit that transmits and receives data to and from the external device 950 according to a predetermined communication standard. Function. The I/O device I/F unit 926 is connected to I/O devices 960 such as various sensors and actuators, and exchanges with the I/O devices 960, for example, detection signals from sensors and control signals to actuators. functions as a communication unit that transmits and receives various signals and data. The media input/output unit 928 is composed of, for example, a drive device such as a DVD drive and a CD drive, and reads and writes data from/to media (non-temporary storage media) 970 such as DVDs and CDs.
　上記構成を有するコンピュータ９００において、プロセッサ９１２は、ストレージ装置９２０に記憶されたプログラム９３０をメモリ９１４に呼び出して実行し、バス９１０を介してコンピュータ９００の各部を制御する。なお、プログラム９３０は、ストレージ装置９２０に代えて、メモリ９１４に記憶されていてもよい。プログラム９３０は、インストール可能なファイル形式又は実行可能なファイル形式でメディア９７０に記録され、メディア入出力部９２８を介してコンピュータ９００に提供されてもよい。プログラム９３０は、通信Ｉ／Ｆ部９２２を介してネットワーク９４０経由でダウンロードすることによりコンピュータ９００に提供されてもよい。また、コンピュータ９００は、プロセッサ９１２がプログラム９３０を実行することで実現する各種の機能を、例えば、ＦＰＧＡ、ＡＳＩＣ等のハードウエアで実現するものでもよい。 In the computer 900 having the above configuration, the processor 912 calls the program 930 stored in the storage device 920 to the memory 914 and executes it, and controls each part of the computer 900 via the bus 910 . Note that the program 930 may be stored in the memory 914 instead of the storage device 920 . The program 930 may be recorded on the media 970 in an installable file format or executable file format and provided to the computer 900 via the media input/output unit 928 . Program 930 may be provided to computer 900 by downloading via network 940 via communication I/F section 922 . Further, the computer 900 may implement various functions realized by the processor 912 executing the program 930 by hardware such as FPGA and ASIC, for example.
　コンピュータ９００は、例えば、据置型コンピュータや携帯型コンピュータで構成され、任意の形態の電子機器である。コンピュータ９００は、クライアント型コンピュータでもよいし、サーバ型コンピュータやクラウド型コンピュータでもよい。コンピュータ９００は、各装置２～６以外の装置にも適用されてもよい。 The computer 900 is, for example, a stationary computer or a portable computer, and is an arbitrary form of electronic equipment. The computer 900 may be a client-type computer, a server-type computer, or a cloud-type computer. The computer 900 may be applied to devices other than the devices 2-6.
（生産履歴情報３０）
　図１０は、データベース装置３により管理される生産履歴情報３０の一例を示すデータ構成図である。生産履歴情報３０は、本生産用の基板処理が行われたときに取得されたレポートＲが分類されて登録されるテーブルとして、例えば、各ウェハＷに関するウェハ履歴テーブル３００と、研磨処理及び仕上げ処理を含む基板処理流体の供給における装置状態情報に関する基板処理流体供給履歴テーブル３０１とを備える。なお、基板処理流体供給履歴テーブル３０１は、基板処理流体の供給における装置状態情報に関する基板処理流体供給履歴テーブルを含む。また、生産履歴情報３０は、上記の他に、イベント情報に関するイベント履歴テーブル及び操作情報に関する操作履歴テーブル等を備えるが、詳細な説明は省略する。 (Production history information 30)
FIG. 10 is a data configuration diagram showing an example of production history information 30 managed by the database device 3. As shown in FIG. The production history information 30 includes, for example, a wafer history table 300 for each wafer W, polishing processing and finishing processing as a table in which reports R obtained when substrate processing for main production is performed are classified and registered. and a substrate processing fluid supply history table 301 relating to apparatus status information in substrate processing fluid supply, including It should be noted that the substrate processing fluid supply history table 301 includes a substrate processing fluid supply history table relating to apparatus status information in substrate processing fluid supply. In addition to the above, the production history information 30 includes an event history table related to event information and an operation history table related to operation information, etc., but detailed description thereof will be omitted.
　ウェハ履歴テーブル３００の各レコードには、例えば、ウェハＩＤ、カセット番号、スロット番号、各工程の開始時刻、終了時刻、使用ユニットＩＤ等が登録される。なお、図１０では、研磨工程、洗浄工程、乾燥工程が例示されているが、他の工程についても同様に登録される。 Each record of the wafer history table 300 registers, for example, a wafer ID, cassette number, slot number, start time and end time of each process, used unit ID, and the like. Although FIG. 10 exemplifies the polishing process, the cleaning process, and the drying process, other processes are similarly registered.
　基板処理流体供給履歴テーブル３０１の各レコードには、例えば、ウェハＩＤ、基板処理流体供給部２２２、２４２ａ、２４５ａから供給される基板処理流体の供給流量情報、基板処理流体供給部２２２、２４２ａ、２４５ａから供給される基板処理流体の供給圧力情報、基板処理流体の流量を調整する基板処理流体供給弁２７１～２７３、２８１～２８３、２９１～２９３の開度等の状態情報、及び、基板処理流体の流量を調整する基板処理流体供給弁２７１～２７３、２８１～２８３、２９１～２９３の一次側の圧力情報等が登録される。 Each record of the substrate processing fluid supply history table 301 includes, for example, a wafer ID, supply flow rate information of the substrate processing fluid supplied from the substrate processing fluid supply units 222, 242a, and 245a, substrate processing fluid supply units 222, 242a, and 245a. supply pressure information of the substrate processing fluid supplied from the substrate processing fluid supply valves 271 to 273, 281 to 283, and 291 to 293 for adjusting the flow rate of the substrate processing fluid; Information such as the pressure on the primary side of the substrate processing fluid supply valves 271 to 273, 281 to 283, and 291 to 293 for adjusting the flow rate is registered.
　基板処理流体供給流量情報は、流体供給処理における基板処理流体供給部２２２、２４２ａ、２４５ａから供給される基板処理流体の流量を示す情報である。基板処理流体供給流量情報は、研磨処理における研磨流体供給ノズル２２２、洗浄処理における洗浄流体供給ノズル２４２ａ、又は、乾燥処理における乾燥処理乾燥流体供給ノズル２４５ａからウェハＷに供給される基板処理流体の供給流量を計測するセンサの検出値等である。 The substrate processing fluid supply flow rate information is information indicating the flow rate of the substrate processing fluid supplied from the substrate processing fluid supply units 222, 242a, and 245a in the fluid supply processing. The substrate processing fluid supply flow rate information is the substrate processing fluid supplied to the wafer W from the polishing fluid supply nozzle 222 in the polishing process, the cleaning fluid supply nozzle 242a in the cleaning process, or the drying process drying fluid supply nozzle 245a in the drying process. It is a detection value of a sensor that measures the flow rate, or the like.
　基板処理流体供給圧力情報は、流体供給処理における基板処理流体供給部２２２、２４２ａ、２４５ａから供給される基板処理流体の圧力を示す情報である。基板処理流体供給圧力情報は、研磨処理における研磨流体供給ノズル２２２、洗浄処理における洗浄流体供給ノズル２４２ａ、又は、乾燥処理における乾燥処理乾燥流体供給ノズル２４５ａからウェハＷに供給される基板処理流体の供給圧力を計測するセンサの検出値等である。 The substrate processing fluid supply pressure information is information indicating the pressure of the substrate processing fluid supplied from the substrate processing fluid supply units 222, 242a, and 245a in the fluid supply processing. The substrate processing fluid supply pressure information is the substrate processing fluid supplied to the wafer W from the polishing fluid supply nozzle 222 in the polishing process, the cleaning fluid supply nozzle 242a in the cleaning process, or the drying process drying fluid supply nozzle 245a in the drying process. It is a detection value of a sensor that measures pressure, or the like.
　基板処理流体供給弁状態情報は、基板処理流体の流量を調整する基板処理流体供給弁２７１～２７３、２８１～２８３、２９１～２９３の状態を示す情報である。基板処理流体供給弁状態情報は、研磨流体供給ノズル２２２、洗浄流体供給ノズル２４２ａ、又は、乾燥流体供給ノズル２４５ａへ流体を供給する基板処理流体供給系統において研磨流体供給ノズル２２２、洗浄流体供給ノズル２４２ａ、又は、乾燥流体供給ノズル２４５ａの上流に接続され基板処理流体の流量を調整する研磨流体供給弁２７１～２７３、洗浄流体供給弁２８１～２８３、又は、乾燥流体供給弁２９１～２９３の状態を計測するセンサの検出値等である。 The substrate processing fluid supply valve state information is information indicating the state of the substrate processing fluid supply valves 271 to 273, 281 to 283, and 291 to 293 that adjust the flow rate of the substrate processing fluid. The substrate processing fluid supply valve state information is stored in the substrate processing fluid supply system that supplies the fluid to the polishing fluid supply nozzle 222, the cleaning fluid supply nozzle 242a, or the drying fluid supply nozzle 245a. Alternatively, the states of the polishing fluid supply valves 271 to 273, the cleaning fluid supply valves 281 to 283, or the drying fluid supply valves 291 to 293 that are connected upstream of the drying fluid supply nozzle 245a and adjust the flow rate of the substrate processing fluid are measured. It is the detection value of the sensor that does.
　基板処理流体供給弁状態情報は、例えば、基板処理流体供給弁２７１～２７３、２８１～２８３、２９１～２９３の開度を示す基板処理流体供給弁開度状態情報、及び、基板処理流体供給弁２７１～２７３、２８１～２８３、２９１～２９３のon-off状態を示す基板処理供給弁on-off状態情報、の少なくとも１つを含む。 The substrate processing fluid supply valve state information includes, for example, substrate processing fluid supply valve opening state information indicating opening degrees of the substrate processing fluid supply valves 271 to 273, 281 to 283, and 291 to 293, and substrate processing fluid supply valve 271. 273, 281-283, and 291-293.
　基板処理流体供給弁一次側圧力情報は、基板処理流体の流量を調整する基板処理流体供給弁２７１～２７３、２８１～２８３、２９１～２９３の一次側の圧力を示す情報である。基板処理流体供給弁一次側圧力情報は、研磨流体供給ノズル２２２、洗浄流体供給ノズル２４２ａ又は乾燥流体供給ノズル２４５ａへ流体を供給する基板処理流体供給系統において研磨流体供給ノズル２２２、洗浄流体供給ノズル２４２ａ又は乾燥流体供給ノズル２４５ａの上流に接続され基板処理流体の流量を調整する研磨処理流体供給弁２７１～２７３、洗浄流体供給弁２８１～２８３又は乾燥流体供給弁２９１～２９３の一次側の圧力を測定するセンサの検出値等である。 The substrate processing fluid supply valve primary side pressure information is information indicating the primary side pressure of the substrate processing fluid supply valves 271 to 273, 281 to 283, and 291 to 293 that adjust the flow rate of the substrate processing fluid. The information on the primary side pressure of the substrate processing fluid supply valve is used in the substrate processing fluid supply system for supplying the fluid to the polishing fluid supply nozzle 222, the cleaning fluid supply nozzle 242a, or the drying fluid supply nozzle 245a. Alternatively, measure the pressure on the primary side of the polishing fluid supply valves 271 to 273, the cleaning fluid supply valves 281 to 283, or the drying fluid supply valves 291 to 293 that are connected upstream of the drying fluid supply nozzle 245a and adjust the flow rate of the substrate processing fluid. It is the detection value of the sensor that does.
　基板処理流体供給履歴テーブル３０１を参照することで、ウェハＩＤで特定されるウェハＷに対して基板処理流体の供給が行われたときの基板処理装置２の装置状態として、各センサの時系列データ（又は各モジュールの時系列データ）が抽出可能である。 By referring to the substrate processing fluid supply history table 301, time-series data of each sensor is obtained as the state of the substrate processing apparatus 2 when the substrate processing fluid is supplied to the wafer W specified by the wafer ID. (or time-series data of each module) can be extracted.
（基板処理流体供給試験情報３１）
　図１１は、データベース装置３により管理される基板処理流体供給試験情報３１の一例を示すデータ構成図である。基板処理流体供給試験情報３１は、試験用の基板処理流体供給部２２２、２４２ａ、２４５ａや基板処理流体供給試験装置を用いて基板処理流体供給試験が行われたときに取得されたレポートＲ及び試験結果が分類されて登録される基板処理流体供給試験テーブル３１０を備える。 (Substrate processing fluid supply test information 31)
FIG. 11 is a data configuration diagram showing an example of the substrate processing fluid supply test information 31 managed by the database device 3. As shown in FIG. The substrate processing fluid supply test information 31 is a report R obtained when the substrate processing fluid supply test is performed using the test substrate processing fluid supply units 222, 242a, and 245a and the substrate processing fluid supply test apparatus, and the test results. A substrate processing fluid supply test table 310 is provided in which the results are sorted and registered.
　基板処理流体供給試験テーブル３１０の各レコードには、例えば、試験ＩＤ、基板処理流体供給流量情報、基板処理流体供給圧力情報、基板処理流体供給弁状態情報、基板処理流体供給弁一次側圧力情報、試験結果情報等が登録される。基板処理流体供給試験テーブル３１０の基板処理流体供給流量情報、基板処理流体供給圧力情報、基板処理流体供給弁状態情報、及び、基板処理流体供給弁一次側圧力情報は、基板処理流体供給試験における各部の状態を示す情報であり、そのデータ構成は、基板処理流体供給履歴テーブル３０１と同様であるため、詳細な説明を省略する。 Each record of the substrate processing fluid supply test table 310 includes, for example, a test ID, substrate processing fluid supply flow rate information, substrate processing fluid supply pressure information, substrate processing fluid supply valve state information, substrate processing fluid supply valve primary side pressure information, Test result information and the like are registered. The substrate processing fluid supply flow rate information, the substrate processing fluid supply pressure information, the substrate processing fluid supply valve state information, and the substrate processing fluid supply valve primary side pressure information in the substrate processing fluid supply test table 310 are used for each part in the substrate processing fluid supply test. , and its data structure is the same as that of the substrate processing fluid supply history table 301, so detailed description thereof will be omitted.
　試験結果情報は、基板処理流体供給試験において基板処理流体の供給が行われたときの基板処理流体供給位置を示す情報である。試験結果情報は、試験用の基板処理流体供給部や基板処理流体供給試験装置を用いて基板処理流体供給位置測定機器により所定の時間間隔でサンプリングされた測定値である。図１１に示す試験結果情報は、基板処理流体の供給を開始してから終了するまでの基板処理流体供給期間に含まれる各時刻ｔ１，ｔ２，…，…ｔｍ，…，ｔｎにおける基板処理流体供給位置の測定値ＴＲ１を含む。 The test result information is information indicating the substrate processing fluid supply position when the substrate processing fluid is supplied in the substrate processing fluid supply test. The test result information is measured values sampled at predetermined time intervals by a substrate processing fluid supply position measuring device using a substrate processing fluid supply unit for testing or a substrate processing fluid supply testing device. The test result information shown in FIG. 11 indicates that the supply of the substrate processing fluid at each time t1, t2, . . . , tm, . It contains the position measurement TR1.
　基板処理流体供給位置の測定は、例えば、予め座標を設定したダミー研磨テーブル又はダミーウェハに、試験用の基板処理流体供給部から流体を供給し、滴下した位置を測定すればよい。また、予め基準位置を決めておき、基準位置からの変化分を測定してもよい。 The substrate processing fluid supply position can be measured, for example, by supplying the fluid from a test substrate processing fluid supply unit to a dummy polishing table or dummy wafer whose coordinates are set in advance, and measuring the dropping position. Alternatively, a reference position may be determined in advance, and the amount of change from the reference position may be measured.
　基板処理流体供給部は、基板処理流体が垂直方向に落下する垂直滴下型、基板処理流体が水平方向に射出される水平射出型、基板処理流体が角度を調整して射出される角度調整射出型のいずれかでよい。 The substrate processing fluid supply unit is a vertical dropping type in which the substrate processing fluid drops vertically, a horizontal injection type in which the substrate processing fluid is ejected horizontally, and an angle adjustment injection type in which the substrate processing fluid is ejected by adjusting the angle. Either
　なお、試験結果情報は、上記のように、基板処理流体供給位置測定機器による測定結果である測定値でもよいし、光学式顕微鏡や走査電子顕微鏡（ＳＥＭ）に搭載されたカメラにより基板処理流体供給位置を所定の時間間隔で撮影し、その撮影した各画像に対して画像処理を行った画像処理結果や実験者が解析した実験解析結果に基づくものでもよい。また、試験結果情報は、基板処理流体の供給を開始してから終了するまでを連続して行った１回の基板処理流体供給試験にて収集されたものでもよいし、基板処理流体の供給を開始してから所定の時刻に到達するまでの基板処理流体供給試験を所定の時刻を徐々に長くしながら繰り返し行うことで、複数回の基板処理流体供給試験にて収集されたものでもよい。 The test result information may be a measured value obtained by a substrate processing fluid supply position measuring device as described above, or may be a substrate processing fluid supplied by a camera mounted on an optical microscope or a scanning electron microscope (SEM). It may be based on the results of image processing in which positions are photographed at predetermined time intervals and image processing is performed on each of the photographed images, or the results of experimental analysis conducted by an experimenter. The test result information may be collected in one substrate processing fluid supply test in which the supply of the substrate processing fluid is continuously performed from the start to the end of the substrate processing fluid supply. By repeating the substrate processing fluid supply test from the start until reaching the predetermined time while gradually lengthening the predetermined time, the substrate processing fluid supply test may be collected a plurality of times.
　基板処理流体供給試験テーブル３１０を参照することで、試験ＩＤで特定される基板処理流体供給試験において、試験用の基板処理流体供給部を用いて流体供給処理が行われたときの基板処理流体供給位置を示す時系列データ（又は各モジュールの時系列データ）と、そのときの試験用の基板処理流体供給部の状態を示す時系列データとが抽出可能である。　　　 By referring to the substrate processing fluid supply test table 310, the substrate processing fluid supply when the fluid supply processing is performed using the test substrate processing fluid supply unit in the substrate processing fluid supply test specified by the test ID. Time-series data indicating the position (or time-series data of each module) and time-series data indicating the state of the substrate processing fluid supply unit for testing at that time can be extracted.　　　
（機械学習装置４）
　図１２は、第１の実施形態に係る機械学習装置４の一例を示すブロック図である。機械学習装置４は、制御部４０、通信部４１、学習用データ記憶部４２、及び、学習済みモデル記憶部４３を備える。 (Machine learning device 4)
FIG. 12 is a block diagram showing an example of the machine learning device 4 according to the first embodiment. The machine learning device 4 includes a control unit 40 , a communication unit 41 , a learning data storage unit 42 and a trained model storage unit 43 .
　制御部４０は、学習用データ取得部４００及び機械学習部４０１として機能する。通信部４１は、ネットワーク７を介して外部装置（例えば、基板処理装置２、データベース装置３、情報処理装置５、及び、ユーザ端末装置６、基板処理流体供給試験装置（不図示）等）と接続され、各種のデータを送受信する通信インターフェースとして機能する。 The control unit 40 functions as a learning data acquisition unit 400 and a machine learning unit 401. The communication unit 41 is connected to external devices (for example, the substrate processing device 2, the database device 3, the information processing device 5, the user terminal device 6, the substrate processing fluid supply test device (not shown), etc.) via the network 7. and functions as a communication interface for sending and receiving various data.
　学習用データ取得部４００は、通信部４１及びネットワーク７を介して外部装置と接続され、入力データとしての基板処理流体供給情報と、出力データとしての基板処理流体供給位置情報とで構成される第１の学習用データ１１Ａを取得する。第１の学習用データ１１Ａは、教師あり学習における教師データ（トレーニングデータ）、検証データ及びテストデータとして用いられるデータである。また、基板処理流体供給位置情報は、教師あり学習における正解ラベルとして用いられるデータである。 The learning data acquisition unit 400 is connected to an external device via the communication unit 41 and the network 7, and is composed of substrate processing fluid supply information as input data and substrate processing fluid supply position information as output data. 1 of learning data 11A is obtained. The first learning data 11A is data used as teacher data (training data), verification data, and test data in supervised learning. Further, the substrate processing fluid supply position information is data used as a correct label in supervised learning.
　学習用データ記憶部４２は、学習用データ取得部４００で取得した第１の学習用データ１１Ａを複数組記憶するデータベースである。なお、学習用データ記憶部４２を構成するデータベースの具体的な構成は適宜設計すればよい。 The learning data storage unit 42 is a database that stores a plurality of sets of the first learning data 11A acquired by the learning data acquisition unit 400. Note that the specific configuration of the database that constitutes the learning data storage unit 42 may be appropriately designed.
　機械学習部４０１は、学習用データ記憶部４２に記憶された複数組の第１の学習用データ１１Ａを用いて機械学習を実施する。すなわち、機械学習部４０１は、第１の学習モデル１０Ａに第１の学習用データ１１Ａを複数組入力し、第１の学習用データ１１Ａに含まれる基板処理流体供給情報と基板処理流体供給位置態情報との相関関係を第１の学習モデル１０Ａに学習させることで、学習済みの第１の学習モデル１０Ａを生成する。 The machine learning unit 401 performs machine learning using multiple sets of first learning data 11A stored in the learning data storage unit 42 . That is, the machine learning unit 401 inputs a plurality of sets of first learning data 11A to the first learning model 10A, and determines the substrate processing fluid supply information and the substrate processing fluid supply position state included in the first learning data 11A. By having the first learning model 10A learn the correlation with the information, the learned first learning model 10A is generated.
　学習済みモデル記憶部４３は、機械学習部４０１により生成された学習済みの第１の学習モデル１０Ａ（具体的には、調整済みの重みパラメータ群）を記憶するデータベースである。学習済みモデル記憶部４３に記憶された学習済みの第１の学習モデル１０Ａは、ネットワーク７や記録媒体等を介して実システム（例えば、情報処理装置５）に提供される。なお、図１２では、学習用データ記憶部４２と、学習済みモデル記憶部４３とが別々の記憶部として示されているが、これらは単一の記憶部で構成されてもよい。 The trained model storage unit 43 is a database that stores the trained first learning model 10A (specifically, the adjusted weight parameter group) generated by the machine learning unit 401. The learned first learning model 10A stored in the learned model storage unit 43 is provided to the actual system (for example, the information processing device 5) via the network 7, a recording medium, or the like. Although the learning data storage unit 42 and the trained model storage unit 43 are shown as separate storage units in FIG. 12, they may be configured as a single storage unit.
　なお、学習済みモデル記憶部４３に記憶される第１の学習モデル１０Ａの数は１つに限定されず、例えば、機械学習の手法、基板処理流体供給部２２２、２４２ａ、２４５ａの種類、基板処理流体供給部２２２、２４２ａ、２４５ａの機構の違い、基板処理流体供給情報に含まれるデータの種類、基板処理流体供給位置情報に含まれるデータの種類等のように、条件が異なる複数の学習モデルが記憶されてもよい。その場合には、学習用データ記憶部４２には、条件が異なる複数の学習モデルにそれぞれ対応するデータ構成を有する複数種類の学習用データが記憶されればよい。 Note that the number of first learning models 10A stored in the learned model storage unit 43 is not limited to one. A plurality of learning models with different conditions, such as differences in the mechanisms of the fluid supply units 222, 242a, and 245a, types of data included in the substrate processing fluid supply information, and types of data included in the substrate processing fluid supply position information. may be stored. In that case, the learning data storage unit 42 may store a plurality of types of learning data having data configurations respectively corresponding to a plurality of learning models with different conditions.
　図１３は、第１の学習モデル１０Ａ及び第１の学習用データ１１Ａの一例を示す図である。第１の学習モデル１０Ａの機械学習に用いられる第１の学習用データ１１Ａは、基板処理流体供給情報と基板処理流体供給位置情報とで構成される。本実施形態では、第１の学習モデル１０Ａ及び第１の学習用データ１１Ａは、ロールスポンジ２４００を用いたロールスポンジ洗浄部２４Ａ、２４Ｂに対応するものと、ペンスポンジ２４０１を用いたペンスポンジ洗浄部２４Ｃ、２４Ｄに対応するものと、乾燥部２４Ｅ、２４Ｆに対応するものとの３種類が少なくとも用意されるが、基本的なデータ構成は共通するため、以下にまとめて説明する。 FIG. 13 is a diagram showing an example of the first learning model 10A and the first learning data 11A. The first learning data 11A used for machine learning of the first learning model 10A is composed of substrate processing fluid supply information and substrate processing fluid supply position information. In this embodiment, the first learning model 10A and the first learning data 11A correspond to the roll sponge cleaning units 24A and 24B using the roll sponge 2400 and the pen sponge cleaning unit using the pen sponge 2401. At least three types, one corresponding to 24C and 24D and one corresponding to drying units 24E and 24F, are prepared.
　第１の学習用データ１１Ａを構成する基板処理流体供給情報は、基板処理流体供給部２２２、２４２ａ、２４５ａから供給される基板処理流体の流量を示す基板処理流体供給流量情報、及び、基板処理流体供給部２２２、２４２ａ、２４５ａから供給される基板処理流体の圧力を示す基板処理流体供給圧力情報を含む。 The substrate processing fluid supply information constituting the first learning data 11A includes substrate processing fluid supply flow rate information indicating the flow rate of the substrate processing fluid supplied from the substrate processing fluid supply units 222, 242a, and 245a, and substrate processing fluid supply information. It includes substrate processing fluid supply pressure information indicating the pressure of the substrate processing fluid supplied from the supply units 222, 242a, and 245a.
　基板処理流体供給情報に含まれる基板処理流体供給流量情報は、基板処理流体の供給における基板処理流体供給部２２２、２４２ａ、２４５ａから供給される基板処理流体の流量を示す情報である。基板処理流体供給流量情報は、研磨処理における研磨流体供給ノズル２２２、洗浄処理における洗浄流体供給ノズル２４２ａ、又は、乾燥処理における乾燥処理乾燥流体供給ノズル２４５ａからウェハＷに供給される基板処理流体の供給流量でよい。 The substrate processing fluid supply flow rate information included in the substrate processing fluid supply information is information indicating the flow rate of the substrate processing fluid supplied from the substrate processing fluid supply units 222, 242a, and 245a in supplying the substrate processing fluid. The substrate processing fluid supply flow rate information is the substrate processing fluid supplied to the wafer W from the polishing fluid supply nozzle 222 in the polishing process, the cleaning fluid supply nozzle 242a in the cleaning process, or the drying process drying fluid supply nozzle 245a in the drying process. Flow rate is fine.
　基板処理流体供給情報に含まれる基板処理流体供給圧力情報は、基板処理流体の供給における基板処理流体供給部２２２、２４２ａ、２４５ａから供給される基板処理流体の圧力を示す情報である。基板処理流体供給圧力情報は、研磨処理における研磨流体供給ノズル２２２、洗浄処理における洗浄流体供給ノズル２４２ａ、又は、乾燥処理における乾燥処理乾燥流体供給ノズル２４５ａからウェハＷに供給される基板処理流体の供給圧力でよい。 The substrate processing fluid supply pressure information included in the substrate processing fluid supply information is information indicating the pressure of the substrate processing fluid supplied from the substrate processing fluid supply units 222, 242a, and 245a in supplying the substrate processing fluid. The substrate processing fluid supply pressure information is the substrate processing fluid supplied to the wafer W from the polishing fluid supply nozzle 222 in the polishing process, the cleaning fluid supply nozzle 242a in the cleaning process, or the drying process drying fluid supply nozzle 245a in the drying process. pressure is fine.
　基板処理流体供給情報に含まれる基板処理流体供給弁状態情報は、基板処理流体の流量を調整する基板処理流体供給弁２７１～２７３、２８１～２８３、２９１～２９３の状態を示す情報である。基板処理流体供給弁状態情報は、研磨流体供給ノズル２２２、洗浄流体供給ノズル２４２ａ、又は、乾燥流体供給ノズル２４５ａへ流体を供給する基板処理流体供給系統において研磨流体供給ノズル２２２、洗浄流体供給ノズル２４２ａ、又は、乾燥流体供給ノズル２４５ａの上流に接続され基板処理流体の流量を調整する研磨流体供給弁２７１～２７３、洗浄流体供給弁２８１～２８３、又は、乾燥流体供給弁２９１～２９３の状態でよい。 The substrate processing fluid supply valve state information included in the substrate processing fluid supply information is information indicating the states of the substrate processing fluid supply valves 271 to 273, 281 to 283, and 291 to 293 that adjust the flow rate of the substrate processing fluid. The substrate processing fluid supply valve state information is stored in the substrate processing fluid supply system that supplies the fluid to the polishing fluid supply nozzle 222, the cleaning fluid supply nozzle 242a, or the drying fluid supply nozzle 245a. Alternatively, the polishing fluid supply valves 271 to 273, the cleaning fluid supply valves 281 to 283, or the drying fluid supply valves 291 to 293, which are connected upstream of the drying fluid supply nozzle 245a and adjust the flow rate of the substrate processing fluid, may be used. .
　なお、基板処理流体供給弁状態情報は、例えば、基板処理流体供給弁２７１～２７３、２８１～２８３、２９１～２９３の開度を示す基板処理流体供給弁開度状態情報、及び、基板処理流体供給弁２７１～２７３、２８１～２８３、２９１～２９３のon-off状態を示す基板処理供給弁on-off状態情報、の少なくとも１つでよい。 The substrate processing fluid supply valve state information includes, for example, substrate processing fluid supply valve opening state information indicating opening degrees of the substrate processing fluid supply valves 271 to 273, 281 to 283, and 291 to 293, and substrate processing fluid supply valve state information. at least one of substrate processing supply valve on-off state information indicating the on-off state of the valves 271-273, 281-283, 291-293.
　基板処理流体供給情報に含まれる基板処理流体供給弁一次側圧力情報は、基板処理流体の流量を調整する基板処理流体供給弁２７１～２７３、２８１～２８３、２９１～２９３の一次側の圧力を示す情報である。基板処理流体供給弁一次側圧力情報は、洗浄流体供給ノズル２４２ａ又は乾燥流体供給ノズル２４５ａへ流体を供給する基板処理流体供給系統において洗浄流体供給ノズル２４２ａ又は乾燥流体供給ノズル２４５ａの上流に接続され基板処理流体の流量を調整する洗浄流体供給弁２８１～２８３又は乾燥流体供給弁２９１～２９３の一次側の圧力でよい。 The substrate processing fluid supply valve primary side pressure information included in the substrate processing fluid supply information indicates the pressure on the primary side of the substrate processing fluid supply valves 271 to 273, 281 to 283, and 291 to 293 that adjust the flow rate of the substrate processing fluid. Information. The substrate processing fluid supply valve primary side pressure information is connected upstream of the cleaning fluid supply nozzle 242a or the drying fluid supply nozzle 245a in the substrate processing fluid supply system that supplies fluid to the cleaning fluid supply nozzle 242a or the drying fluid supply nozzle 245a. It may be the pressure on the primary side of the cleaning fluid supply valves 281-283 or the drying fluid supply valves 291-293 that regulate the flow rate of the processing fluid.
　なお、基板処理流体供給情報は、基板処理流体の供給が行われる空間の環境を示す装置内環境情報をさらに含むものでもよく、基板処理流体供給情報に含まれる装置内環境情報は、ハウジング２０により形成された内部空間の温度、及び、湿度の少なくとも１つを含む。また、基板処理流体供給情報は、基板処理流体の供給の実績を示す処理実績情報をさらに含むものでもよく、基板処理流体供給情報に含まれる処理実績情報は、例えば、基板処理流体供給部２２２、２４２ａ、２４５ａが交換されてからその基板処理流体供給部２２２、２４２ａ、２４５ａを用いて基板処理流体の供給が行われたときのウェハＷの累積使用枚数、及び、累積使用時間の少なくとも１つを含む。 The substrate processing fluid supply information may further include apparatus internal environment information indicating the environment of the space where the substrate processing fluid is supplied. At least one of temperature and humidity of the formed internal space is included. Further, the substrate processing fluid supply information may further include processing performance information indicating the substrate processing fluid supply performance. At least one of the cumulative number of used wafers W and the cumulative usage time when the substrate processing fluid supply units 222, 242a, and 245a are used to supply the substrate processing fluid after the replacement of the 242a and 245a. include.
　第１の学習用データ１１Ａを構成する基板処理流体供給位置情報は、基板処理流体供給情報が示す動作状態にて基板処理装置２が動作したときの基板処理流体供給部２２２、２４２ａ、２４５ａから供給される流体の供給位置を示す情報である。本実施形態では、基板処理流体供給位置情報は、を含む。 The substrate processing fluid supply position information constituting the first learning data 11A is supplied from the substrate processing fluid supply units 222, 242a, and 245a when the substrate processing apparatus 2 operates in the operating state indicated by the substrate processing fluid supply information. This is information indicating the supply position of the fluid to be applied. In this embodiment, the substrate processing fluid supply position information includes:
　学習用データ取得部４００は、基板処理流体供給試験情報３１を参照するとともに、必要に応じてユーザ端末装置６によるユーザの入力操作を受け付けることで、第１の学習用データ１１Ａを取得する。例えば、学習用データ取得部４００は、基板処理流体供給試験情報３１の基板処理流体供給試験テーブル３１０を参照することで、試験ＩＤで特定される基板処理流体供給試験が行われたときの基板処理流体供給流量情報、基板処理流体供給圧力情報、基板処理流体供給弁状態情報、及び、基板処理流体供給弁一次側圧力情報、を、基板処理流体供給情報として取得する。 The learning data acquisition unit 400 acquires the first learning data 11A by referring to the substrate processing fluid supply test information 31 and accepting user input operations through the user terminal device 6 as necessary. For example, the learning data acquisition unit 400 refers to the substrate processing fluid supply test table 310 of the substrate processing fluid supply test information 31 to obtain substrate processing data when the substrate processing fluid supply test specified by the test ID is performed. Fluid supply flow rate information, substrate processing fluid supply pressure information, substrate processing fluid supply valve state information, and substrate processing fluid supply valve primary side pressure information are acquired as substrate processing fluid supply information.
　なお、本実施形態では、基板処理流体供給情報を、図１３に示すようなセンサ群の時系列データとして取得する場合について説明するが、基板処理流体供給部２２２、２４２ａ、２４５ａの構成に応じて適宜変更してもよい。また、基板処理流体供給情報として、モジュールへの指令値を用いてもよいし、センサの検出値又はモジュールへの指令値から換算されるパラメータを用いてもよいし、複数のセンサの検出値に基づいて算出されるパラメータを用いてもよい。さらに、基板処理流体供給情報は、基板処理流体の供給期間全体の時系列データとして取得されてもよいし、基板処理流体の供給期間の一部である対象期間の時系列データとして取得されてもよいし、特定の対象時点における時点データとして取得されてもよい。上記のように、基板処理流体供給情報の定義を変更する場合には、第１の学習モデル１０Ａ及び第１の学習用データ１１Ａにおける入力データのデータ構成を適宜変更すればよい。 In this embodiment, a case will be described in which the substrate processing fluid supply information is obtained as time-series data of the sensor group as shown in FIG. It may be changed as appropriate. Also, as the substrate processing fluid supply information, a command value to the module may be used, a parameter converted from the detected value of the sensor or the command value to the module may be used, or the detected value of a plurality of sensors may be used. You may use the parameter calculated based on. Further, the substrate processing fluid supply information may be acquired as time-series data for the entire supply period of the substrate processing fluid, or may be acquired as time-series data for a target period that is part of the supply period for the substrate processing fluid. Alternatively, it may be obtained as point-in-time data at a specific target point in time. As described above, when changing the definition of the substrate processing fluid supply information, the data configuration of the input data in the first learning model 10A and the first learning data 11A may be changed as appropriate.
　また、学習用データ取得部４００は、基板処理流体供給試験情報３１の基板処理流体供給試験テーブル３１０を参照することで、同一の試験ＩＤで特定される基板処理流体供給試験が行われたときの試験結果情報（基板処理流体供給位置測定機器の時系列データ（図１１））を、上記の基板処理流体供給情報に対する基板処理流体供給位置情報として取得する。基板処理流体供給位置測定機器が、基板処理流体供給部２２２、２４２ａ、２４５ａに対して面的な測定が可能な測定機器である場合には、学習用データ取得部４００は、面的な測定値を基板処理流体供給位置情報として取得する。 In addition, the learning data acquisition unit 400 refers to the substrate processing fluid supply test table 310 of the substrate processing fluid supply test information 31 to determine whether the substrate processing fluid supply test specified by the same test ID is performed. Test result information (time series data of the substrate processing fluid supply position measuring device (FIG. 11)) is acquired as substrate processing fluid supply position information for the substrate processing fluid supply information. When the substrate processing fluid supply position measuring device is a measuring device capable of planar measurement with respect to the substrate processing fluid supply units 222, 242a, and 245a, the learning data acquisition unit 400 obtains planar measurement values. is acquired as substrate processing fluid supply position information.
　なお、本実施形態では、基板処理流体供給位置情報が、図１３に示すような場合について説明するが、予め座標を設定したダミー研磨テーブル又はダミーウェハに、試験用の基板処理流体供給部から流体が供給された位置を含むものでもよい。また、基板処理流体供給位置情報は、基板処理流体供給位置測定機器の測定値を所定の算出式に代入することで算出されてもよい。さらに、基板処理流体供給情報が、例えば、基板処理流体供給期間全体の時系列データ又は基板処理流体供給期間の一部である対象期間の時系列データとして取得されている場合には、基板処理流体供給位置情報は、基板処理流体供給期間全体の時系列データ又は対象期間の時系列データとして取得されてもよいし、基板処理流体供給終了時点の時点データ又は対象時点の時点データとして取得されてもよい。また、基板処理流体供給情報が、例えば、特定の対象時点における時点データとして取得されている場合には、基板処理流体供給位置情報は、その特定の対象時点における時点データとして取得されてもよい。上記のように、基板処理流体供給位置情報の定義を変更する場合には、第１の学習モデル１０Ａ及び第１の学習用データ１１Ａにおける出力データのデータ構成を適宜変更すればよい。 In this embodiment, the case where the substrate processing fluid supply position information is as shown in FIG. 13 will be described. It may also include the position provided. Further, the substrate processing fluid supply position information may be calculated by substituting the measured value of the substrate processing fluid supply position measuring device into a predetermined calculation formula. Furthermore, when the substrate processing fluid supply information is acquired as, for example, time-series data of the entire substrate processing fluid supply period or time-series data of a target period that is a part of the substrate processing fluid supply period, the substrate processing fluid The supply position information may be acquired as time-series data for the entire substrate processing fluid supply period or time-series data for the target period, or may be acquired as point-in-time data at the end of supply of the substrate-processing fluid or point-in-time data at the target point. good. Further, when the substrate processing fluid supply information is acquired as point-in-time data at a specific target point in time, the substrate processing fluid supply position information may be acquired as point-in-time data at the specific target point in time. As described above, when changing the definition of the substrate processing fluid supply position information, the data structure of the output data in the first learning model 10A and the first learning data 11A may be changed as appropriate.
　第１の学習モデル１０Ａは、例えば、ニューラルネットワークの構造を採用したものであり、入力層１００、中間層１０１、及び、出力層１０２を備える。各層の間には、各ニューロンをそれぞれ接続するシナプス（不図示）が張られており、各シナプスには、重みがそれぞれ対応付けられている。各シナプスの重みからなる重みパラメータ群が、機械学習により調整される。 The first learning model 10A employs, for example, a neural network structure, and includes an input layer 100, an intermediate layer 101, and an output layer 102. A synapse (not shown) connecting each neuron is provided between each layer, and a weight is associated with each synapse. A set of weight parameters consisting of the weight of each synapse is adjusted by machine learning.
　入力層１００は、入力データとしての基板処理流体供給情報に対応する数のニューロンを有し、基板処理流体供給情報の各値が各ニューロンにそれぞれ入力される。出力層１０２は、出力データとしての基板処理流体供給位置情報に対応する数のニューロンを有し、基板処理流体供給情報に対する基板処理流体供給位置情報の予測結果（推論結果）が、出力データとして出力される。
  The input layer 100 has a number of neurons corresponding to the substrate processing fluid supply information as input data, and each value of the substrate processing fluid supply information is input to each neuron. The output layer 102 has a number of neurons corresponding to the substrate processing fluid supply position information as output data, and the prediction result (inference result) of the substrate processing fluid supply position information for the substrate processing fluid supply information is output as output data. be done.
　そして、推論結果として出力層の各ニューロンに出力された値と、学習用データに含まれる出力データのそれぞれに対応する教師データの値とをそれぞれ比較して誤差を求め、その誤差が小さくなるように、各シナプスに対応付けられた重みを調整する処理（バックプロバケーション）が実施される。 Then, the value output to each neuron in the output layer as the inference result is compared with the teacher data value corresponding to each output data included in the learning data to obtain the error, and the error is minimized. Then, a process (back promotion) is performed to adjust the weight associated with each synapse.
　上記の一連の工程を所定回数反復実施すること、又は、上記の誤差が許容値より小さくなること等の所定の学習終了条件が満たされた場合には、機械学習を終了し、学習済みのニューラルネットワークモデル（シナプスのそれぞれに対応付けられた全ての重み）として生成される。 When a predetermined learning end condition is satisfied, such as repeating the above series of steps a predetermined number of times, or the error is smaller than the allowable value, the machine learning is terminated and the learned neural It is generated as a network model (all weights associated with each of the synapses).
（機械学習方法）
　図１４は、機械学習装置４による機械学習方法の一例を示すフローチャートである。 (machine learning method)
FIG. 14 is a flow chart showing an example of a machine learning method by the machine learning device 4. As shown in FIG.
　まず、ステップＳ１００において、学習用データ取得部４００は、機械学習を開始するための事前準備として、基板処理流体供給試験情報３１等から所望の数の第１の学習用データ１１Ａを取得し、その取得した第１の学習用データ１１Ａを学習用データ記憶部４２に記憶する。ここで準備する第１の学習用データ１１Ａの数については、最終的に得られる第１の学習モデル１０Ａに求められる推論精度を考慮して設定すればよい。 First, in step S100, the learning data acquisition unit 400 acquires a desired number of first learning data 11A from the substrate processing fluid supply test information 31 or the like as preparation for starting machine learning. The acquired first learning data 11A is stored in the learning data storage unit 42 . The number of first learning data 11A prepared here may be set in consideration of the inference accuracy required for the finally obtained first learning model 10A.
　次に、ステップＳ１１０において、機械学習部４０１は、機械学習を開始すべく、学習前の第１の学習モデル１０Ａを準備する。ここで準備する学習前の第１の学習モデル１０Ａは、ニューラルネットワークモデルで構成されており、各シナプスの重みが初期値に設定されている。 Next, in step S110, the machine learning unit 401 prepares the first learning model 10A before learning to start machine learning. The first learning model 10A before learning prepared here is composed of a neural network model, and the weight of each synapse is set to an initial value.
　次に、ステップＳ１２０において、機械学習部４０１は、学習用データ記憶部４２に記憶された複数組の第１の学習用データ１１Ａから、例えば、ランダムに１組の第１の学習用データ１１Ａを取得する。 Next, in step S120, the machine learning unit 401, for example, randomly selects one set of first learning data 11A from the plurality of sets of first learning data 11A stored in the learning data storage unit 42. get.
　次に、ステップＳ１３０において、機械学習部４０１は、１組の第１の学習用データ１１Ａに含まれる基板処理流体供給情報（入力データ）を、準備された学習前（又は学習中）の第１の学習モデル１０Ａの入力層１００に入力する。その結果、第１の学習モデル１０Ａの出力層１０２から推論結果として基板処理流体供給位置情報（出力データ）が出力されるが、当該出力データは、学習前（又は学習中）の第１の学習モデル１０Ａによって生成されたものである。そのため、学習前（又は学習中）の状態では、推論結果として出力された出力データは、第１の学習用データ１１Ａに含まれる基板処理流体供給位置情報（正解ラベル）とは異なる情報を示す。 Next, in step S130, the machine learning unit 401 converts the substrate processing fluid supply information (input data) included in the set of first learning data 11A into the prepared first pre-learning (or during learning) pre-learning data. input to the input layer 100 of the learning model 10A. As a result, substrate processing fluid supply position information (output data) is output as an inference result from the output layer 102 of the first learning model 10A. It is generated by model 10A. Therefore, in the state before (or during) learning, the output data output as the inference result indicates information different from the substrate processing fluid supply position information (correct label) included in the first learning data 11A.
　次に、ステップＳ１４０において、機械学習部４０１は、ステップＳ１２０において取得された１組の第１の学習用データ１１Ａに含まれる基板処理流体供給位置情報（正解ラベル）と、ステップＳ１３０において出力層から推論結果として出力された基板処理流体供給位置情報（出力データ）とを比較し、各シナプスの重みを調整する処理（バックプロバケーション）を実施することで、機械学習を実施する。これにより、機械学習部４０１は、基板処理流体供給情報と基板処理流体供給位置情報との相関関係を第１の学習モデル１０Ａに学習させる。 Next, in step S140, the machine learning unit 401 extracts the substrate processing fluid supply position information (correct label) included in the set of first learning data 11A acquired in step S120, and from the output layer in step S130. Machine learning is performed by comparing substrate processing fluid supply position information (output data) output as a result of inference and adjusting the weight of each synapse (back promotion). Thereby, the machine learning unit 401 causes the first learning model 10A to learn the correlation between the substrate processing fluid supply information and the substrate processing fluid supply position information.
　次に、ステップＳ１５０において、機械学習部４０１は、所定の学習終了条件が満たされたか否かを、例えば、第１の学習用データ１１Ａに含まれる基板処理流体供給位置情報（正解ラベル）と、推論結果として出力された状態情報（出力データ）とに基づく誤差関数の評価値や、学習用データ記憶部４２内に記憶された未学習の第１の学習用データ１１Ａの残数に基づいて判定する。 Next, in step S150, the machine learning unit 401 determines whether or not a predetermined learning end condition is satisfied, for example, the substrate processing fluid supply position information (correct label) included in the first learning data 11A, Determination based on the evaluation value of the error function based on the state information (output data) output as the inference result and the remaining number of unlearned first learning data 11A stored in the learning data storage unit 42 do.
　ステップＳ１５０において、機械学習部４０１が、学習終了条件が満たされておらず、機械学習を継続すると判定した場合（ステップＳ１５０でＮｏ）、ステップＳ１２０に戻り、学習中の第１の学習モデル１０Ａに対してステップＳ１２０～Ｓ１４０の工程を未学習の第１の学習用データ１１Ａを用いて複数回実施する。一方、ステップＳ１５０において、機械学習部４０１が、学習終了条件が満たされて、機械学習を終了すると判定した場合（ステップＳ１５０でＹｅｓ）、ステップＳ１６０に進む。 In step S150, when the machine learning unit 401 determines that the learning end condition is not satisfied and continues the machine learning (No in step S150), the process returns to step S120, and the first learning model 10A under learning In contrast, steps S120 to S140 are performed multiple times using the unlearned first learning data 11A. On the other hand, when the machine learning unit 401 determines in step S150 that the learning end condition is satisfied and machine learning ends (Yes in step S150), the process proceeds to step S160.
　そして、ステップＳ１６０において、機械学習部４０１は、各シナプスに対応付けられた重みを調整することで生成された学習済みの第１の学習モデル１０Ａ（調整済みの重みパラメータ群）を学習済みモデル記憶部４３に記憶し、図１４に示す一連の機械学習方法を終了する。機械学習方法において、ステップＳ１００が学習用データ記憶工程、ステップＳ１１０～Ｓ１５０が機械学習工程、ステップＳ１６０が学習済みモデル記憶工程に相当する。 Then, in step S160, the machine learning unit 401 stores the learned first learning model 10A (adjusted weight parameter group) generated by adjusting the weight associated with each synapse as a learned model. It is stored in the unit 43, and the series of machine learning methods shown in FIG. 14 is finished. In the machine learning method, step S100 corresponds to a learning data storage step, steps S110 to S150 correspond to a machine learning step, and step S160 corresponds to a learned model storage step.
　以上のように、本実施形態に係る機械学習装置４及び機械学習方法によれば、基板処理流体供給流量情報、基板処理流体供給圧力情報、基板処理流体供給弁状態情報、及び、基板処理流体供給弁一次側圧力情報、を含む基板処理流体供給情報から、基板処理流体の供給位置を示す基板処理流体供給位置情報を予測（推論）することが可能な第１の学習モデル１０Ａを提供することができる。 As described above, according to the machine learning device 4 and the machine learning method according to the present embodiment, substrate processing fluid supply flow rate information, substrate processing fluid supply pressure information, substrate processing fluid supply valve state information, and substrate processing fluid supply It is possible to provide a first learning model 10A capable of predicting (inferring) substrate processing fluid supply position information indicating the substrate processing fluid supply position from substrate processing fluid supply information including valve primary side pressure information. can.
（情報処理装置５）
　図１５は、第１の実施形態に係る情報処理装置５の一例を示すブロック図である。図１６は、第１の実施形態に係る情報処理装置５の一例を示す機能説明図である。情報処理装置５は、制御部５０、通信部５１、及び、学習済みモデル記憶部５２を備える。 (Information processing device 5)
FIG. 15 is a block diagram showing an example of the information processing device 5 according to the first embodiment. FIG. 16 is a functional explanatory diagram showing an example of the information processing device 5 according to the first embodiment. The information processing device 5 includes a control unit 50 , a communication unit 51 and a trained model storage unit 52 .
　制御部５０は、情報取得部５００、状態予測部５０１及び出力処理部５０２として機能する。通信部５１は、ネットワーク７を介して外部装置（例えば、基板処理装置２、データベース装置３、機械学習装置４、及び、ユーザ端末装置６等）と接続され、各種のデータを送受信する通信インターフェースとして機能する。 The control unit 50 functions as an information acquisition unit 500 , a state prediction unit 501 and an output processing unit 502 . The communication unit 51 is connected to an external device (for example, the substrate processing device 2, the database device 3, the machine learning device 4, the user terminal device 6, etc.) via the network 7, and serves as a communication interface for transmitting and receiving various data. Function.
　情報取得部５００は、通信部５１及びネットワーク７を介して外部装置と接続され、基板処理流体供給流量情報、基板処理流体供給圧力情報、基板処理流体供給弁状態情報、及び、基板処理流体供給弁一次側圧力情報、を含む基板処理流体供給情報を取得する。 The information acquisition unit 500 is connected to an external device via the communication unit 51 and the network 7, and obtains substrate processing fluid supply flow rate information, substrate processing fluid supply pressure information, substrate processing fluid supply valve state information, and substrate processing fluid supply valve. substrate processing fluid supply information including primary side pressure information;
　例えば、基板処理流体の供給がすでに行われた後のウェハＷに対する基板処理流体供給位置情報の「事後予測処理」を行う場合には、情報取得部５００は、生産履歴情報３０の基板処理流体供給履歴テーブル３０１を参照することで、そのウェハＷに対して基板処理流体の供給が行われたときの基板処理流体供給流量情報、基板処理流体供給圧力情報、基板処理流体供給弁状態情報、及び、基板処理流体供給弁一次側圧力情報、を、基板処理流体供給情報として取得する。 For example, in the case of performing the “post-prediction processing” of the substrate processing fluid supply position information for the wafer W after the substrate processing fluid has already been supplied, the information acquiring unit 500 acquires the substrate processing fluid supply position of the production history information 30 . By referring to the history table 301, substrate processing fluid supply flow rate information, substrate processing fluid supply pressure information, substrate processing fluid supply valve state information, and substrate processing fluid supply valve state information when the substrate processing fluid is supplied to the wafer W. Substrate processing fluid supply valve primary side pressure information is acquired as substrate processing fluid supply information.
　基板処理流体の供給が行われている最中のウェハＷに対する基板処理流体供給位置情報の「リアルタイム予測処理」を行う場合には、情報取得部５００は、その基板処理流体の供給を行っている基板処理装置２から装置状態情報に関するレポートＲを随時受信することで、そのウェハＷに対して基板処理流体の供給が行われている最中の基板処理流体供給流量情報、基板処理流体供給圧力情報、基板処理流体供給弁状態情報、及び、基板処理流体供給弁一次側圧力情報、を、基板処理流体供給情報として随時取得する。 When performing the "real-time prediction process" of the substrate processing fluid supply position information for the wafer W while the substrate processing fluid is being supplied, the information acquisition unit 500 supplies the substrate processing fluid. By receiving a report R regarding the apparatus status information from the substrate processing apparatus 2 at any time, substrate processing fluid supply flow rate information and substrate processing fluid supply pressure information while the substrate processing fluid is being supplied to the wafer W. , substrate processing fluid supply valve state information, and substrate processing fluid supply valve primary side pressure information are acquired as substrate processing fluid supply information at any time.
　基板処理流体の供給が行われる前のウェハＷに対する基板処理流体供給位置情報の「事前予測処理」を行う場合には、情報取得部５００は、その基板処理流体の供給を行う予定の基板処理装置２から基板レシピ情報２６６を受信し、その基板レシピ条件２６６に従って基板処理装置２が動作するときの装置状態情報をシミュレーションすることで、そのウェハＷに対して基板処理流体の供給が行われるときの基板処理流体供給流量情報、基板処理流体供給圧力情報、基板処理流体供給弁状態情報、及び、基板処理流体供給弁一次側圧力情報、を、基板処理流体供給情報として取得する。 When performing the "advance prediction process" of the substrate processing fluid supply position information for the wafer W before the substrate processing fluid is supplied, the information acquisition unit 500 selects the substrate processing apparatus to which the substrate processing fluid is to be supplied. 2, and by simulating the apparatus state information when the substrate processing apparatus 2 operates according to the substrate recipe conditions 266, the substrate processing fluid is supplied to the wafer W. Substrate processing fluid supply flow rate information, substrate processing fluid supply pressure information, substrate processing fluid supply valve state information, and substrate processing fluid supply valve primary side pressure information are acquired as substrate processing fluid supply information.
　状態予測部５０１は、上記のように、情報取得部５００により取得された基板処理流体供給情報を入力データとして第１の学習モデル１０Ａに入力することで、当該基板処理流体供給情報が示す状態にて基板処理装置２が動作したときの基板処理流体供給部２２２、２４２ａ、２４５ａの状態を示す基板処理流体供給位置情報を予測する。 By inputting the substrate processing fluid supply information acquired by the information acquisition unit 500 as input data to the first learning model 10A as described above, the state prediction unit 501 predicts the state indicated by the substrate processing fluid supply information. Then, substrate processing fluid supply position information indicating the states of the substrate processing fluid supply units 222, 242a, and 245a when the substrate processing apparatus 2 operates is predicted.
　学習済みモデル記憶部５２は、状態予測部５０１にて用いられる学習済みの第１の学習モデル１０Ａを記憶するデータベースである。なお、学習済みモデル記憶部５２に記憶される第１の学習モデル１０Ａの数は１つに限定されず、例えば、機械学習の手法、基板処理流体供給部２２２、２４２ａ、２４５ａの種類、基板処理流体供給部２２２、２４２ａ、２４５ａの機構の違い、基板処理流体供給情報に含まれるデータの種類、基板処理流体供給位置情報に含まれるデータの種類等のように、条件が異なる複数の学習済みモデルが記憶され、選択的に利用可能としてもよい。学習済みモデル記憶部５２は、外部コンピュータ（例えば、サーバ型コンピュータやクラウド型コンピュータ）の記憶部で代用されてもよく、その場合には、状態予測部５０１は、当該外部コンピュータにアクセスすればよい。 The learned model storage unit 52 is a database that stores the learned first learning model 10A used in the state prediction unit 501. Note that the number of first learning models 10A stored in the learned model storage unit 52 is not limited to one. A plurality of learned models with different conditions, such as differences in the mechanisms of the fluid supply units 222, 242a, and 245a, the types of data included in the substrate processing fluid supply information, and the types of data included in the substrate processing fluid supply position information. may be stored and selectively available. The trained model storage unit 52 may be replaced by a storage unit of an external computer (for example, a server computer or a cloud computer), in which case the state prediction unit 501 may access the external computer. .
　出力処理部５０２は、状態予測部５０１により生成された基板処理流体供給位置情報を出力するための出力処理を行う。例えば、出力処理部５０２は、その基板処理流体供給位置情報をユーザ端末装置６に送信することで、その基板処理流体供給位置情報に基づく表示画面がユーザ端末装置６に表示されてもよいし、その基板処理流体供給位置情報をデータベース装置３に送信することで、その基板処理流体供給位置情報が生産履歴情報３０に登録されてもよい。 The output processing unit 502 performs output processing for outputting the substrate processing fluid supply position information generated by the state prediction unit 501 . For example, the output processing unit 502 may transmit the substrate processing fluid supply position information to the user terminal device 6 so that a display screen based on the substrate processing fluid supply position information may be displayed on the user terminal device 6, The substrate processing fluid supply position information may be registered in the production history information 30 by transmitting the substrate processing fluid supply position information to the database device 3 .
（情報処理方法）
　図１７は、情報処理装置５による情報処理方法の一例を示すフローチャートである。以下では、ユーザがユーザ端末装置６を操作して、特定のウェハＷに対する基板処理流体供給位置情報の「事後予測処理」を行う場合の動作例について説明する。 (Information processing method)
FIG. 17 is a flowchart showing an example of an information processing method by the information processing device 5. As shown in FIG. An operation example in which the user operates the user terminal device 6 to perform "post-prediction processing" of substrate processing fluid supply position information for a specific wafer W will be described below.
　まず、ステップＳ２００において、ユーザが、ユーザ端末装置６に対して、予測対象のウェハＷを特定するウェハＩＤを入力する入力操作を行うと、ユーザ端末装置６は、そのウェハＩＤを情報処理装置５に送信する。 First, in step S200, when the user performs an input operation for inputting a wafer ID specifying a wafer W to be predicted to the user terminal device 6, the user terminal device 6 sends the wafer ID to the information processing device 5. Send to
　次に、ステップＳ２１０において、情報処理装置５の情報取得部５００は、ステップＳ２００にて送信されたウェハＩＤを受信する。ステップＳ２１１において、情報取得部５００は、ステップＳ２１０で受信したウェハＩＤを用いて生産履歴情報３０の流体供給履歴テーブル３０１を参照することで、そのウェハＩＤで特定されたウェハＷに対して流体供給処理が行われたときの基板処理流体供給情報を取得する。 Next, in step S210, the information acquisition unit 500 of the information processing device 5 receives the wafer ID transmitted in step S200. In step S211, the information acquisition unit 500 refers to the fluid supply history table 301 of the production history information 30 using the wafer ID received in step S210, thereby supplying the fluid to the wafer W specified by the wafer ID. Substrate processing fluid supply information is obtained when processing is performed.
　次に、ステップＳ２２０において、状態予測部５０１は、ステップＳ２１１にて取得された基板処理流体供給情報を入力データとして第１の学習モデル１０Ａに入力することで、当該基板処理流体供給情報に対する基板処理流体供給位置情報を出力データとして生成し、その基板処理流体供給位置を予測する。 Next, in step S220, the state prediction unit 501 inputs the substrate processing fluid supply information acquired in step S211 to the first learning model 10A as input data, thereby performing substrate processing with respect to the substrate processing fluid supply information. Fluid supply position information is generated as output data to predict the substrate processing fluid supply position.
　次に、ステップＳ２３０において、出力処理部５０２は、ステップＳ２２０にて生成された基板処理流体供給位置情報を出力するための出力処理として、その基板処理流体供給位置情報をユーザ端末装置６に送信する。なお、基板処理流体供給位置情報の送信先は、ユーザ端末装置６に加えて又は代えて、データベース装置３でもよい。 Next, in step S230, the output processing unit 502 transmits the substrate processing fluid supply position information to the user terminal device 6 as output processing for outputting the substrate processing fluid supply position information generated in step S220. . The destination of the substrate processing fluid supply position information may be the database device 3 in addition to or instead of the user terminal device 6 .
　次に、ステップＳ２４０において、ユーザ端末装置６は、ステップＳ２００の送信処理に対する応答として、ステップＳ２３０にて送信された基板処理流体供給位置情報を受信すると、その基板処理流体供給位置情報に基づいて表示画面を表示することで、その基板処理流体供給位置情報がユーザにより視認される。上記の情報処理方法において、ステップＳ２１０、Ｓ２１１が情報取得工程、ステップＳ２２０が状態予測工程、ステップＳ２３０が出力処理工程に相当する。 Next, in step S240, upon receiving the substrate processing fluid supply position information transmitted in step S230 as a response to the transmission processing in step S200, the user terminal device 6 displays based on the substrate processing fluid supply position information. By displaying the screen, the user can visually recognize the substrate processing fluid supply position information. In the above information processing method, steps S210 and S211 correspond to the information acquisition step, step S220 corresponds to the state prediction step, and step S230 corresponds to the output processing step.
　以上のように、本実施形態に係る情報処理装置５及び情報処理方法によれば、流体供給処理における、基板処理流体供給流量情報、基板処理流体供給圧力情報、基板処理流体供給弁状態情報、及び、基板処理流体供給弁一次側圧力情報が第１の学習モデル１０Ａに入力されることで、当該基板処理流体供給情報に対する処理流体供給位置情報が予測されるので、基板処理装置２の動作状態に応じて処理流体供給位置を適切に予測することができる。 As described above, according to the information processing apparatus 5 and the information processing method according to the present embodiment, substrate processing fluid supply flow rate information, substrate processing fluid supply pressure information, substrate processing fluid supply valve state information, and substrate processing fluid supply valve state information in the fluid supply process. By inputting the substrate processing fluid supply valve primary side pressure information to the first learning model 10A, the processing fluid supply position information corresponding to the substrate processing fluid supply information is predicted. Accordingly, the processing fluid supply position can be appropriately predicted.
（第２の実施形態）
　第２の実施形態は、基板処理流体供給位置情報が、基板処理流体供給部２２２、２４２ａ、２４５ａの流体吐出位置及び流体吐出方向を示す基板処理流体供給部位置方向情報である点で第１の実施形態と相違する。以下では、第２の実施形態に係る機械学習装置４ａ及び情報処理装置５ａについて、第１の実施形態と異なる部分を中心に説明する。 (Second embodiment)
The second embodiment is different from the first embodiment in that the substrate processing fluid supply position information is substrate processing fluid supply portion position/direction information indicating the fluid ejection positions and fluid ejection directions of the substrate processing fluid supply portions 222, 242a, and 245a. It differs from the embodiment. In the following, the machine learning device 4a and the information processing device 5a according to the second embodiment will be described, focusing on the differences from the first embodiment.
　図１８は、第２の実施形態に係る機械学習装置４ａの一例を示すブロック図である。図１９は、第２の学習モデル１０Ｂ及び第２の学習用データ１１Ｂの一例を示す図である。第２の学習用データ１１Ｂは、第２の学習モデル１０Ｂの機械学習に用いられる。 FIG. 18 is a block diagram showing an example of a machine learning device 4a according to the second embodiment. FIG. 19 is a diagram showing an example of the second learning model 10B and the second learning data 11B. The second learning data 11B is used for machine learning of the second learning model 10B.
　第２の学習用データ１１Ｂを構成する基板処理流体供給位置情報は、基板処理流体供給部２２２、２４２ａ、２４５ａの位置及び方向を示す基板処理流体供給部位置方向情報である。基板処理流体供給部２２２、２４２ａ、２４５ａの位置及び方向は、例えば、基板処理流体供給部２２２、２４２ａ、２４５ａの３次元位置と３次元方向にて定められる。なお、第２の学習用データ１１Ｂを構成する基板処理流体供給情報は、第１の実施形態と同様であるため、説明を省略する。 The substrate processing fluid supply position information constituting the second learning data 11B is substrate processing fluid supply portion position/direction information indicating the positions and directions of the substrate processing fluid supply portions 222, 242a, and 245a. The positions and directions of the substrate processing fluid supply portions 222, 242a, 245a are determined, for example, by the three-dimensional positions and three-dimensional directions of the substrate processing fluid supply portions 222, 242a, 245a. Note that the substrate processing fluid supply information forming the second learning data 11B is the same as in the first embodiment, so the description is omitted.
　基板処理流体の供給位置及び供給方向の測定は、例えば、予め３次元座標を設定したダミー空間において、試験用のノズル等の基板処理流体供給部から流体を供給し、ダミー研磨テーブル又はダミーウェハの最適な位置に滴下した時の供給位置及び供給方向を測定すればよい。基板処理流体の供給位置及び供給方向は、流体の吐出位置と吐出方向を測定すればよい。吐出方向は、吐出口の中心線の方向を３次元の角度等で表せばよい。 Measurement of the supply position and supply direction of the substrate processing fluid is performed, for example, by supplying the fluid from a substrate processing fluid supply unit such as a test nozzle in a dummy space in which three-dimensional coordinates are set in advance, and determining the optimum value of the dummy polishing table or dummy wafer. It is only necessary to measure the supply position and the supply direction when the liquid is dropped at a specific position. As for the supply position and supply direction of the substrate processing fluid, the ejection position and ejection direction of the fluid may be measured. As for the ejection direction, the direction of the center line of the ejection port may be represented by a three-dimensional angle or the like.
　また、例えば、吐出口の断面と中心線の交差する位置を基準位置、吐出口の中心線の方向を基準方向として、基準位置及び基準方向からの３次元方向の変化分を測定してもよい。 Further, for example, the position where the cross section of the ejection port and the center line intersect may be set as the reference position, and the direction of the center line of the ejection port may be set as the reference direction, and the amount of change in the three-dimensional direction from the reference position and the reference direction may be measured. .
　基板処理流体供給部は、基板処理流体が垂直方向に落下する垂直滴下型、基板処理流体が水平方向に射出される水平射出型、基板処理流体が角度を調整して射出される角度調整射出型のいずれかでよい。 The substrate processing fluid supply unit is a vertical dropping type in which the substrate processing fluid drops vertically, a horizontal injection type in which the substrate processing fluid is ejected horizontally, and an angle adjustment injection type in which the substrate processing fluid is ejected by adjusting the angle. Either
　学習用データ取得部４００は、基板処理流体供給試験情報３１を参照するとともに、必要に応じてユーザ端末装置６によるユーザの入力操作を受け付けることで、第２の学習用データ１１Ｂを取得する。基板処理流体供給試験情報３１には、例えば、基板処理流体供給試験として、試験用の基板処理流体供給部を用いて繰り返し基板処理流体供給処理が行われた場合に、基板処理流体供給部２２２、２４２ａ、２４５ａの吐出口の吐出位置と吐出方向を試験結果情報として登録されている。そして、学習用データ取得部４００は、基板処理流体供給試験情報３１の仕上げ基板処理流体供給試験テーブル３１０から試験ＩＤで特定される基板処理流体供給試験が行われたときの試験結果情報を取得することで、基板処理流体供給位置情報を取得する。 The learning data acquisition unit 400 acquires the second learning data 11B by referring to the substrate processing fluid supply test information 31 and accepting user input operations through the user terminal device 6 as necessary. The substrate processing fluid supply test information 31 includes, for example, the substrate processing fluid supply unit 222 , the substrate processing fluid supply unit 222 , the substrate processing fluid supply unit 222 , the substrate processing fluid supply unit 222 , the substrate processing fluid supply unit 222 , the substrate processing fluid supply unit 222 , the substrate processing fluid supply unit 222 , the substrate processing fluid supply unit 222 , The ejection positions and ejection directions of the ejection ports 242a and 245a are registered as test result information. Then, the learning data acquisition unit 400 acquires test result information when the substrate processing fluid supply test specified by the test ID is performed from the finishing substrate processing fluid supply test table 310 of the substrate processing fluid supply test information 31. Thus, substrate processing fluid supply position information is obtained.
　機械学習部４０１は、第２の学習モデル１０Ｂに第２の学習用データ１１Ｂを複数組入力し、第２の学習用データ１１Ｂに含まれる基板処理流体供給情報と基板処理流体供給位置情報との相関関係を第２の学習モデル１０Ｂに学習させることで、学習済みの第２の学習モデル１０Ｂを生成する。 The machine learning unit 401 inputs a plurality of sets of second learning data 11B to the second learning model 10B, and compares substrate processing fluid supply information and substrate processing fluid supply position information included in the second learning data 11B. By making the second learning model 10B learn the correlation, the learned second learning model 10B is generated.
　図２０は、第２の実施形態に係る情報処理装置５ａとして機能する情報処理装置５ａの一例を示すブロック図である。図２１は、第２の実施形態に係る情報処理装置５ａの一例を示す機能説明図である。 FIG. 20 is a block diagram showing an example of an information processing device 5a functioning as the information processing device 5a according to the second embodiment. FIG. 21 is a functional explanatory diagram showing an example of the information processing device 5a according to the second embodiment.
　情報取得部５００は、第１の実施形態と同様に、基板処理流体供給流量情報、基板処理流体供給圧力情報、基板処理流体供給弁状態情報、及び、基板処理流体供給弁一時側圧力情報を含む基板処理流体供給情報を取得する。 As in the first embodiment, the information acquisition unit 500 includes substrate processing fluid supply flow rate information, substrate processing fluid supply pressure information, substrate processing fluid supply valve state information, and substrate processing fluid supply valve primary side pressure information. Obtain substrate processing fluid supply information.
　状態予測部５０１は、上記のように、情報取得部５００により取得された基板処理流体供給情報を入力データとして第２の学習モデル１０Ｂに入力することで、当該基板処理流体供給情報が示す動作状態にて基板処理装置２が動作したときの基板処理流体供給部２２２、２４２ａ、２４５ａの３次元位置と３次元方向を基板処理流体供給位置方向情報として予測する。 By inputting the substrate processing fluid supply information acquired by the information acquisition unit 500 as input data to the second learning model 10B as described above, the state prediction unit 501 predicts the operating state indicated by the substrate processing fluid supply information. The three-dimensional positions and three-dimensional directions of the substrate processing fluid supply units 222, 242a, and 245a when the substrate processing apparatus 2 operates are predicted as substrate processing fluid supply position direction information.
　以上のように、本実施形態に係る情報処理装置５ａ及び情報処理方法によれば、基板処理流体供給処理における、基板処理流体供給流量情報、基板処理流体供給圧力情報、基板処理流体供給弁状態情報、及び、基板処理流体供給弁一時側圧力情報を含む基板処理流体供給情報が第２の学習モデル１０Ｂに入力されることで、当該基板処理流体供給情報に対する基板処理流体供給位置方向情報が予測されるので、基板処理装置２の供給状態に応じて基板処理流体供給部２２２、２４２ａ、２４５ａの吐出口の位置及び方向を適切に予測することができる。 As described above, according to the information processing apparatus 5a and the information processing method according to the present embodiment, the substrate processing fluid supply flow rate information, the substrate processing fluid supply pressure information, and the substrate processing fluid supply valve state information in the substrate processing fluid supply process. , and the substrate processing fluid supply information including the substrate processing fluid supply valve primary side pressure information is input to the second learning model 10B, whereby the substrate processing fluid supply position direction information for the substrate processing fluid supply information is predicted. Therefore, the positions and directions of the ejection ports of the substrate processing fluid supply units 222, 242a, and 245a can be appropriately predicted according to the supply state of the substrate processing apparatus 2. FIG.
（他の実施形態）
　本発明は上述した実施形態に制約されるものではなく、本発明の主旨を逸脱しない範囲内で種々変更して実施することが可能である。そして、それらはすべて、本発明の技術思想に含まれるものである。 (Other embodiments)
The present invention is not limited to the above-described embodiments, and various modifications can be made without departing from the gist of the present invention. All of them are included in the technical idea of the present invention.
　上記実施形態では、データベース装置３、機械学習装置４及び情報処理装置５は、別々の装置で構成されたものとして説明したが、それら３つの装置が、単一の装置で構成されていてもよいし、それら３つの装置のうち任意の２つの装置が、単一の装置で構成されていてもよい。また、機械学習装置４及び情報処理装置５の少なくとも一方は、基板処理装置２の制御ユニット２６又はユーザ端末装置６に組み込まれていてもよい。 In the above embodiment, the database device 3, the machine learning device 4, and the information processing device 5 are described as being composed of separate devices, but these three devices may be composed of a single device. However, any two of the three devices may be configured as a single device. At least one of the machine learning device 4 and the information processing device 5 may be incorporated in the control unit 26 of the substrate processing apparatus 2 or the user terminal device 6 .
　上記実施形態では、基板処理装置２が、各ユニット２１～２５を備えるものとして説明したが、基板処理装置２は、研磨ユニット２２の研磨処理を行う際にウェハＷに研磨処理流体を供給する機能、仕上げユニット２４の洗浄処理を行う際にウェハＷに洗浄処理流体を供給する機能、及び、仕上げユニット２４の乾燥処理を行う際にウェハＷに処理流体を供給する機能のうち少なくとも１つを備えていればよく、他のユニットは省略されていてもよい。 In the above embodiment, the substrate processing apparatus 2 has been described as having the respective units 21 to 25, but the substrate processing apparatus 2 has a function of supplying polishing processing fluid to the wafer W when the polishing unit 22 performs polishing processing. , a function of supplying the cleaning fluid to the wafer W when performing the cleaning process of the finishing unit 24, and a function of supplying the processing fluid to the wafer W when performing the drying process of the finishing unit 24. other units may be omitted.
　上記実施形態では、機械学習部４０１による機械学習を実現する学習モデルとして、ニューラルネットワークを採用した場合について説明したが、他の機械学習のモデルを採用してもよい。他の機械学習のモデルとしては、例えば、決定木、回帰木等のツリー型、バギング、ブースティング等のアンサンブル学習、再帰型ニューラルネットワーク、畳み込みニューラルネットワーク、ＬＳＴＭ等のニューラルネット型(ディープラーニングを含む)、階層型クラスタリング、非階層型クラスタリング、ｋ近傍法、ｋ平均法等のクラスタリング型、主成分分析、因子分析、ロジスティク回帰等の多変量解析、サポートベクターマシン等が挙げられる。 In the above embodiment, a case where a neural network is adopted as a learning model for realizing machine learning by the machine learning unit 401 has been described, but other machine learning models may be adopted. Other machine learning models include, for example, tree types such as decision trees and regression trees, ensemble learning such as bagging and boosting, recurrent neural networks, convolutional neural networks, and neural network types such as LSTM (including deep learning ), hierarchical clustering, non-hierarchical clustering, k-nearest neighbor method, k-means method and other clustering types, principal component analysis, factor analysis, logistic regression and other multivariate analyzes, and support vector machines.
　上記実施形態では、試験結果情報は、試験装置においてダミー研磨テーブル又はダミーウェハを用いた基板処理流体供給試験において基板処理流体の供給が行われたときの基板処理流体供給位置を示す情報であるが、基板処理流体供給部２２２、２４２ａ、２４５ａの状態を検出するセンサを設置した実際の研磨ユニット２２及び仕上げユニット２４を用いて実際のウェハＷの基板処理流体の供給が行われたときの状態を示す情報として継続的に取得されるようにしてもよい。継続的に取得した試験結果情報は、機械学習装置４によって継続的に学習される。 In the above embodiment, the test result information is information indicating the substrate processing fluid supply position when the substrate processing fluid is supplied in the substrate processing fluid supply test using the dummy polishing table or the dummy wafer in the test apparatus. The state when the substrate processing fluid is actually supplied to the wafer W using the actual polishing unit 22 and the finishing unit 24 in which sensors for detecting the states of the substrate processing fluid supply units 222, 242a, and 245a are shown. It may be continuously acquired as information. The continuously acquired test result information is continuously learned by the machine learning device 4 .
　また、試験結果情報は、センサを設置しない研磨ユニット２２及び仕上げユニット２４において、人が基板処理流体供給位置を判断し、データにラベル付けをして継続的に取得されるようにしてもよい。 In addition, the test result information may be continuously obtained in the polishing unit 22 and the finishing unit 24 in which no sensor is installed, by manually determining the substrate processing fluid supply position and labeling the data.
　さらに、実際の研磨ユニット２２及び仕上げユニット２４を用いて継続的に取得された情報をクラウドへアップロードし、クラウドで機械学習した後、学習されたモデルを基板処理装置２へ展開してもよい。また、クラウドへアップロードすることなく、基板処理装置２内で処理方法を学習してもよい。 Furthermore, information continuously acquired using the actual polishing unit 22 and finishing unit 24 may be uploaded to the cloud, machine-learned in the cloud, and then the learned model may be deployed to the substrate processing apparatus 2. Alternatively, the processing method may be learned within the substrate processing apparatus 2 without uploading to the cloud.
（機械学習プログラム及び情報処理プログラム）
　本発明は、機械学習装置４が備える各部としてコンピュータ９００を機能させるプログラム（機械学習プログラム）や、機械学習方法が備える各工程をコンピュータ９００に実行させるためのプログラム（機械学習プログラム）の態様で提供することもできる。また、本発明は、情報処理装置５が備える各部としてコンピュータ９００を機能させるためのプログラム（情報処理プログラム）や、上記実施形態に係る情報処理方法が備える各工程をコンピュータ９００に実行させるためのプログラム（情報処理プログラム）の態様で提供することもできる。 (Machine learning program and information processing program)
The present invention is provided in the form of a program (machine learning program) that causes the computer 900 to function as each part of the machine learning device 4, and a program (machine learning program) that causes the computer 900 to execute each step of the machine learning method. You can also Further, the present invention provides a program (information processing program) for causing the computer 900 to function as each unit provided in the information processing apparatus 5, and a program for causing the computer 900 to execute each step provided in the information processing method according to the above embodiment. It can also be provided in the form of (information processing program).
（推論装置、推論方法及び推論プログラム）
　本発明は、上記実施形態に係る情報処理装置５（情報処理方法又は情報処理プログラム）の態様によるもののみならず、基板処理流体供給位置情報を推論するために用いられる推論装置（推論方法又は推論プログラム）の態様で提供することもできる。その場合、推論装置（推論方法又は推論プログラム）としては、メモリと、プロセッサとを含み、このうちのプロセッサが、一連の処理を実行するものとすることができる。当該一連の処理とは、基板処理流体供給情報を取得する情報取得処理（情報取得工程）と、情報取得処理にて基板処理流体供給情報を取得すると、当該基板処理流体供給情報が示す基板処理流体供給状態にて基板処理装置２が動作したときの基板処理流体供給位置を示す基板処理流体供給位置情報を推論する推論処理（推論工程）とを含む。 (Inference Apparatus, Inference Method and Inference Program)
The present invention can be applied not only to the aspect of the information processing apparatus 5 (information processing method or information processing program) according to the above-described embodiment, but also to an inference apparatus (inference method or inference method) used for inferring substrate processing fluid supply position information. program). In that case, the inference device (inference method or inference program) may include a memory and a processor, and the processor of these may execute a series of processes. The series of processes includes information acquisition processing (information acquisition step) for acquiring substrate processing fluid supply information, and substrate processing fluid indicated by the substrate processing fluid supply information acquired in the information acquisition processing. Inference processing (inference step) for inferring substrate processing fluid supply position information indicating the substrate processing fluid supply position when the substrate processing apparatus 2 operates in the supply state.
　推論装置（推論方法又は推論プログラム）の態様で提供することで、情報処理装置５を実装する場合に比して簡単に種々の装置への適用が可能となる。推論装置（推論方法又は推論プログラム）が基板処理流体供給位置情報を推論する際、上記実施形態に係る機械学習装置４及び機械学習方法により生成された学習済みの学習モデルを用いて、状態予測部５０１が実施する推論手法を適用してもよいことは、当業者にとって当然に理解され得るものである。 By providing it in the form of an inference device (inference method or inference program), it can be applied to various devices more easily than when the information processing device 5 is implemented. When the inference device (inference method or inference program) infers substrate processing fluid supply position information, the machine learning device 4 and the learned model generated by the machine learning method according to the above embodiment are used to generate a state prediction unit It should be understood by those skilled in the art that the reasoning techniques implemented by 501 may also be applied.
　本発明は、情報処理装置、推論装置、機械学習装置、情報処理方法、推論方法、及び、機械学習方法に利用可能である。 The present invention can be used for information processing devices, inference devices, machine learning devices, information processing methods, inference methods, and machine learning methods.
１…基板処理システム、２…基板処理装置、３…データベース装置、
４、４ａ…機械学習装置、５、５ａ…情報処理装置、
６…ユーザ端末装置、７…ネットワーク、
１０Ａ…第１の学習モデル、１０Ｂ…第２の学習モデル、
１１Ａ…第１の学習用データ、１１Ｂ…第２の学習用データ、
２０…ハウジング、２１…ロード／アンロードユニット、
２２…研磨ユニット、２２Ａ～２２Ｄ…研磨部、２３…基板搬送ユニット、
２４…仕上げユニット、２４Ａ、２４Ｂ…ロールスポンジ洗浄部、
２４Ｃ、２４Ｄ…ペンスポンジ洗浄部、２４Ｅ、２４Ｆ…乾燥部、
２４Ｇ、２４Ｈ…搬送部、２５…膜厚測定ユニット、２６…制御ユニット、
３０…生産履歴情報、３１…仕上げ試験情報、
４０…制御部、４１…通信部、４２…学習用データ記憶部、
４３…学習済みモデル記憶部、
５０…制御部、５１…通信部、５２…学習済みモデル記憶部、
２２０…研磨テーブル、２２１…トップリング、
２２２…研磨流体供給ノズル（基板処理流体供給部）、
２２３…ドレッサ、２２４…アトマイザ、
２４０…基板洗浄部、２４１…基板保持部、
２４２…洗浄流体供給部（基板処理流体供給部）、
２４３…洗浄具洗浄部、２４４…環境センサ、
２４５…乾燥流体供給部（基板処理流体供給部）、
２６０…制御部、２１…通信部、２６２…入力部、２６３…出力部、２６４…記憶部、
３００…ウェハ履歴テーブル、３０１…仕上げ履歴テーブル、３１０…仕上げ試験テーブル、
４００…学習用データ取得部、４０１…機械学習部、
５００…情報取得部、５０１…状態予測部、５０２…出力処理部、
９００…コンピュータ、
２２００…研磨パッド、２２３０…ドレッサディスク、２４００…ロールスポンジ、
２４０１…ペンスポンジ

  DESCRIPTION OF SYMBOLS 1... Substrate processing system, 2... Substrate processing apparatus, 3... Database apparatus,
4, 4a... machine learning device, 5, 5a... information processing device,
6... User terminal device, 7... Network,
10A... first learning model, 10B... second learning model,
11A... First learning data, 11B... Second learning data,
20... housing, 21... load/unload unit,
22... Polishing unit, 22A to 22D... Polishing part, 23... Substrate transfer unit,
24... Finishing unit, 24A, 24B... Roll sponge cleaning part,
24C, 24D... pen sponge washing section, 24E, 24F... drying section,
24G, 24H... transport unit, 25... film thickness measurement unit, 26... control unit,
30...Production history information, 31...Finishing test information,
40... control unit, 41... communication unit, 42... learning data storage unit,
43 ... learned model storage unit,
50... Control unit, 51... Communication unit, 52... Learned model storage unit,
220... polishing table, 221... top ring,
222: Polishing fluid supply nozzle (substrate processing fluid supply unit),
223...dresser, 224...atomizer,
240... Substrate cleaning part, 241... Substrate holding part,
242... Cleaning fluid supply unit (substrate processing fluid supply unit),
243...Cleaning tool cleaning unit, 244...Environmental sensor,
245 ... dry fluid supply unit (substrate processing fluid supply unit),
260... control unit, 21... communication unit, 262... input unit, 263... output unit, 264... storage unit,
300 ... Wafer history table, 301 ... Finishing history table, 310 ... Finishing test table,
400... Learning data acquisition unit, 401... Machine learning unit,
500... Information acquisition unit, 501... State prediction unit, 502... Output processing unit,
900... computer,
2200 Polishing pad 2230 Dresser disk 2400 Roll sponge
2401... Pen sponge

Claims (15)

  1. 　基板に処理流体を供給する一又は複数の基板処理流体供給部を備える基板処理装置により行われる前記基板の処理における、前記基板処理流体供給部から供給される基板処理流体の供給状態を示す基板処理流体供給状態情報、を含む基板処理流体供給情報を取得する情報取得部と、
    　前記基板処理流体供給情報と、前記基板処理装置が動作したときの前記基板処理流体供給部が供給する流体の供給位置を示す基板処理流体供給位置情報との相関関係を機械学習により学習させた学習モデルに、前記情報取得部により取得された前記基板処理流体供給情報を入力することで、当該基板処理流体供給情報に対する前記基板処理流体供給位置情報を予測する状態予測部と、
    を備える、
    　情報処理装置。     Substrate processing showing a supply state of a substrate processing fluid supplied from the substrate processing fluid supply unit in the substrate processing performed by the substrate processing apparatus having one or more substrate processing fluid supply units for supplying the processing fluid to the substrate an information acquisition unit for acquiring substrate processing fluid supply information including fluid supply state information;
    learning by machine learning a correlation between the substrate processing fluid supply information and substrate processing fluid supply position information indicating a supply position of the fluid supplied by the substrate processing fluid supply unit when the substrate processing apparatus is operated; a state prediction unit that predicts the substrate processing fluid supply position information with respect to the substrate processing fluid supply information by inputting the substrate processing fluid supply information acquired by the information acquisition unit into a model;
    comprising
    Information processing equipment.
  2. 　前記基板処理流体供給情報に含まれる前記基板処理流体供給状態情報は、
    　　前記基板処理流体供給部から前記基板に供給される前記基板処理流体の供給流量を示す基板処理流体供給流量情報、及び、
    　　前記基板処理流体供給部から前記基板に供給される前記基板処理流体の供給圧力を示す基板処理流体供給圧力情報、の少なくとも１つを含む、
    　請求項１に記載の情報処理装置。     The substrate processing fluid supply state information included in the substrate processing fluid supply information includes:
    substrate processing fluid supply flow rate information indicating a supply flow rate of the substrate processing fluid supplied to the substrate from the substrate processing fluid supply unit; and
    substrate processing fluid supply pressure information indicating the supply pressure of the substrate processing fluid supplied to the substrate from the substrate processing fluid supply unit;
    The information processing device according to claim 1 .
  3. 　前記基板処理流体供給情報は、さらに、前記基板処理流体供給部へ流体を供給する供給系統において前記基板処理流体供給部の上流に接続され前記基板処理流体の流量を調整する基板処理流体供給弁の状態を取得する基板処理流体供給弁状態情報を含む
    　請求項１又は２に記載の情報処理装置。     The substrate processing fluid supply information further includes a substrate processing fluid supply valve that is connected upstream of the substrate processing fluid supply unit in a supply system that supplies fluid to the substrate processing fluid supply unit and that adjusts the flow rate of the substrate processing fluid. 3. The information processing apparatus according to claim 1, further comprising substrate processing fluid supply valve state information for acquiring a state.
  4. 　前記基板処理流体供給弁状態情報は、
    　　前記基板処理流体供給弁の開度を示す基板処理流体供給弁開度状態情報、及び、
    　　前記基板処理流体供給弁のon-off状態を示す基板処理流体供給弁on-off状態情報、の少なくとも１つを含む、
    　請求項３に記載の情報処理装置。     The substrate processing fluid supply valve state information includes:
    substrate processing fluid supply valve opening state information indicating the opening degree of the substrate processing fluid supply valve;
    substrate processing fluid supply valve on-off state information indicating the on-off state of the substrate processing fluid supply valve;
    The information processing apparatus according to claim 3.
  5. 　前記基板処理流体供給情報は、さらに、前記基板処理流体供給部へ流体を供給する供給系統において前記基板処理流体供給部の上流に接続され前記基板処理流体の流量を調整する基板処理流体供給弁の一次側の圧力を取得する基板処理流体供給弁一次側圧力情報を含む
    　請求項１乃至請求項４のいずれか一項に記載の情報処理装置。     The substrate processing fluid supply information further includes a substrate processing fluid supply valve that is connected upstream of the substrate processing fluid supply unit in a supply system that supplies fluid to the substrate processing fluid supply unit and that adjusts the flow rate of the substrate processing fluid. 5. The information processing apparatus according to any one of claims 1 to 4, further comprising substrate processing fluid supply valve primary side pressure information for obtaining primary side pressure.
  6. 　前記基板処理装置は、１又は複数の前記基板処理流体供給部をそれぞれ有する１又は複数のユニットを備え、
    　前記基板処理流体供給部へ流体を供給する供給系統において、前記基板処理流体供給弁は、１つの前記ユニットにおける全ての前記基板処理流体供給部より上流に設置される
    　請求項３乃至請求項５のいずれか一項に記載の情報処理装置。     The substrate processing apparatus comprises one or more units each having one or more of the substrate processing fluid supply units,
    6. The supply system for supplying fluid to the substrate processing fluid supply section, wherein the substrate processing fluid supply valve is installed upstream of all the substrate processing fluid supply sections in one unit. The information processing device according to any one of the items.
  7. 　前記基板処理流体供給部へ流体を供給する供給系統において、前記基板処理流体供給弁は、１つの前記基板処理装置における全ての前記ユニットより上流に設置される
    　請求項３乃至請求項６のいずれか一項に記載の情報処理装置。     7. The supply system for supplying the fluid to the substrate processing fluid supply section, wherein the substrate processing fluid supply valve is installed upstream of all the units in one substrate processing apparatus. The information processing device according to item 1.
  8. 　１又は複数の前記基板処理装置を設置する基板処理システムにおいて、
    　前記基板処理流体供給部へ流体を供給する供給系統において、前記基板処理流体供給弁は、１つの前記基板処理システムにおける全ての前記基板処理装置より上流に設置される
    　請求項３乃至請求項７のいずれか一項に記載の情報処理装置。     In a substrate processing system in which one or more substrate processing apparatuses are installed,
    8. The supply system for supplying the fluid to the substrate processing fluid supply unit, wherein the substrate processing fluid supply valve is installed upstream of all the substrate processing apparatuses in one substrate processing system. The information processing device according to any one of the items.
  9. 　前記基板処理流体供給位置情報は、
    　　前記基板に設定された座標上の位置情報、及び、
    　　予め設定された基準位置に対する変化分情報、の少なくとも１つを含む、
    　請求項１乃至請求項８のいずれか一項に記載の情報処理装置。     The substrate processing fluid supply position information includes:
    Positional information on the coordinates set on the substrate; and
    change amount information with respect to a preset reference position,
    The information processing apparatus according to any one of claims 1 to 8.
  10. 　前記基板処理流体供給位置情報は、
    　　前記基板処理流体供給部の流体吐出位置及び流体吐出方向を示す基板処理流体供給部位置方向情報を含む、
    　請求項１乃至請求項８のいずれか一項に記載の情報処理装置。     The substrate processing fluid supply position information includes:
    including position and direction information of the substrate processing fluid supply unit indicating a fluid ejection position and a fluid ejection direction of the substrate processing fluid supply unit;
    The information processing apparatus according to any one of claims 1 to 8.
  11. 　メモリと、プロセッサとを備える推論装置であって、
    　前記プロセッサは、
    　　基板に処理流体を供給する１又は複数の基板処理流体供給部を備える基板処理装置が動作したときの動作状態として、前記基板処理流体供給部から供給される基板処理流体の供給状態を示す基板処理流体供給状態情報を含む基板処理流体供給情報を取得する情報取得処理と、
    　　前記情報取得処理にて前記基板処理流体供給情報を取得すると、前記基板処理流体供給情報が示す前記基板処理流体の供給状態にて前記基板処理装置が処理したときの前記基板処理流体供給部が供給する流体の供給位置を示す基板処理流体供給位置情報を推論する推論処理と、を実行する、
    　推論装置。     An inference device comprising a memory and a processor,
    The processor
    Substrate processing showing a supply state of a substrate processing fluid supplied from the substrate processing fluid supply unit as an operating state when a substrate processing apparatus having one or more substrate processing fluid supply units for supplying the processing fluid to a substrate operates. an information acquisition process for acquiring substrate processing fluid supply information including fluid supply state information;
    When the substrate processing fluid supply information is acquired in the information acquisition process, the substrate processing fluid supply unit supplies the substrate processing fluid when the substrate processing apparatus performs processing in the substrate processing fluid supply state indicated by the substrate processing fluid supply information. an inference process for inferring substrate processing fluid supply position information indicating the supply position of the fluid to be processed;
    reasoning device.
  12. 　基板に基板洗浄流体を供給する基板処理流体供給部を備える基板処理装置により行われる前記基板の処理における、前記基板処理流体供給部から供給される基板処理流体の供給状態を示す基板処理流体供給状態情報を含む基板処理流体供給情報と、前記基板処理流体供給情報が示す前記基板処理流体の供給状態にて前記基板処理装置が処理したときの前記基板処理流体供給部が供給する流体の供給位置を示す基板処理流体供給位置情報とで構成される学習用データを複数組記憶する学習用データ記憶部と、
    　複数組の前記学習用データを学習モデルに入力することで、前記基板処理流体供給情報と前記基板処理流体供給位置情報との相関関係を前記学習モデルに学習させる機械学習部と、
    　前記機械学習部により前記相関関係を学習させた前記学習モデルを記憶する学習済みモデル記憶部と、を備える、
    　機械学習装置。     A substrate processing fluid supply state indicating a supply state of the substrate processing fluid supplied from the substrate processing fluid supply unit in the substrate processing performed by the substrate processing apparatus having the substrate processing fluid supply unit for supplying the substrate cleaning fluid to the substrate. substrate processing fluid supply information including information; and a supply position of the fluid supplied by the substrate processing fluid supply unit when the substrate processing apparatus performs processing in the supply state of the substrate processing fluid indicated by the substrate processing fluid supply information. a learning data storage unit for storing a plurality of sets of learning data configured with substrate processing fluid supply position information shown;
    a machine learning unit that causes the learning model to learn the correlation between the substrate processing fluid supply information and the substrate processing fluid supply position information by inputting a plurality of sets of the learning data into the learning model;
    a learned model storage unit that stores the learning model for which the correlation has been learned by the machine learning unit;
    Machine learning device.
  13. 　基板に基板洗浄流体を供給する基板処理流体供給部を備える基板処理装置により行われる前記基板の処理における、前記基板処理流体供給部から供給される基板処理流体の供給状態を示す基板処理流体供給状態情報を含む基板処理流体供給情報を取得する情報取得工程と、
    　前記基板処理流体供給情報と、前記基板処理流体供給情報が示す前記基板処理流体の供給状態にて前記基板処理装置が処理したときの前記基板処理流体供給部が供給する流体の供給位置を示す基板処理流体供給位置情報との相関関係を機械学習により学習させた学習モデルに、前記情報取得工程により取得された前記基板処理流体供給情報を入力することで、当該基板処理流体供給情報に対する前記基板処理流体供給位置情報を予測する状態予測工程と、を備える、
    　情報処理方法。     A substrate processing fluid supply state indicating a supply state of the substrate processing fluid supplied from the substrate processing fluid supply unit in the substrate processing performed by the substrate processing apparatus having the substrate processing fluid supply unit for supplying the substrate cleaning fluid to the substrate. an information obtaining step of obtaining substrate processing fluid supply information including information;
    and a substrate indicating a supply position of the fluid supplied by the substrate processing fluid supply unit when the substrate processing apparatus processes in the supply state of the substrate processing fluid indicated by the substrate processing fluid supply information. By inputting the substrate processing fluid supply information acquired by the information acquisition step into a learning model obtained by learning the correlation with the processing fluid supply position information by machine learning, the substrate processing with respect to the substrate processing fluid supply information a state prediction step of predicting fluid supply position information;
    Information processing methods.
  14. 　メモリと、プロセッサとを備える推論装置により実行される推論方法であって、
    　前記プロセッサは、
    　　　基板に基板洗浄流体を供給する洗浄流体供給部を備える基板処理装置により行われる前記基板の処理における、前記基板処理流体供給部から供給される基板処理流体の供給状態を示す基板処理流体供給状態情報を含む基板処理流体供給情報を取得する情報取得工程と、
    　　前記情報取得工程にて前記基板処理流体供給情報を取得すると、前記基板処理流体供給情報が示す前記基板処理流体の供給状態にて前記基板処理装置が処理したときの前記基板処理流体供給部が供給する流体の供給位置を示す基板処理流体供給位置情報を推論する推論工程と、を実行する、
    　推論方法。     An inference method executed by an inference device comprising a memory and a processor,
    The processor
    Substrate processing fluid supply state information indicating a supply state of the substrate processing fluid supplied from the substrate processing fluid supply unit in the substrate processing performed by the substrate processing apparatus having the cleaning fluid supply unit for supplying the substrate cleaning fluid to the substrate. an information acquisition step of acquiring substrate processing fluid supply information including
    When the substrate processing fluid supply information is acquired in the information acquiring step, the substrate processing fluid supply unit supplies the substrate processing fluid when the substrate processing apparatus performs processing in the substrate processing fluid supply state indicated by the substrate processing fluid supply information. performing an inference step of inferring substrate processing fluid supply position information indicating the supply position of the fluid to be processed;
    reasoning method.
  15. 　基板に基板洗浄流体を供給する洗浄流体供給部を備える基板処理装置により行われる前記基板の処理における、前記基板処理流体供給部から供給される基板処理流体の供給状態を示す基板処理流体供給状態情報を含む基板処理流体供給情報と、前記基板処理流体供給情報が示す前記基板処理流体の供給状態にて前記基板処理装置が処理したときの前記基板処理流体供給部が供給する流体の供給位置を示す基板処理流体供給位置情報とで構成される学習用データを学習用データ記憶部に複数組記憶する学習用データ記憶工程と、
    　複数組の前記学習用データを学習モデルに入力することで、前記基板処理流体供給情報と前記基板処理流体供給位置情報との相関関係を前記学習モデルに学習させる機械学習工程と、
    　前記機械学習工程により前記相関関係を学習させた前記学習モデルを学習済みモデル記憶部に記憶する学習済みモデル記憶工程と、を備える、
    　機械学習方法。

          Substrate processing fluid supply state information indicating a supply state of the substrate processing fluid supplied from the substrate processing fluid supply unit in the substrate processing performed by the substrate processing apparatus having the cleaning fluid supply unit for supplying the substrate cleaning fluid to the substrate. and a supply position of the fluid supplied by the substrate processing fluid supply unit when the substrate processing apparatus performs processing in the supply state of the substrate processing fluid indicated by the substrate processing fluid supply information. a learning data storage step of storing a plurality of sets of learning data including substrate processing fluid supply position information in a learning data storage unit;
    a machine learning step of causing the learning model to learn the correlation between the substrate processing fluid supply information and the substrate processing fluid supply position information by inputting a plurality of sets of the learning data into the learning model;
    a learned model storage step of storing the learning model, the correlation of which has been learned by the machine learning step, in a learned model storage unit;
    machine learning method.
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