WO2017208357A1 - 生産制御装置および生産制御プログラム - Google Patents

生産制御装置および生産制御プログラム Download PDF

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Publication number
WO2017208357A1
WO2017208357A1 PCT/JP2016/066046 JP2016066046W WO2017208357A1 WO 2017208357 A1 WO2017208357 A1 WO 2017208357A1 JP 2016066046 W JP2016066046 W JP 2016066046W WO 2017208357 A1 WO2017208357 A1 WO 2017208357A1
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Prior art keywords
value
measurement
production
difference
average
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PCT/JP2016/066046
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English (en)
French (fr)
Japanese (ja)
Inventor
暁楠 時
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三菱電機株式会社
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Priority to PCT/JP2016/066046 priority Critical patent/WO2017208357A1/ja
Priority to TW105126046A priority patent/TW201743273A/zh
Publication of WO2017208357A1 publication Critical patent/WO2017208357A1/ja

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/04—Manufacturing
    • 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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

Definitions

  • the present invention relates to production control.
  • Patent Document 1 discloses a technique for collecting information related to operation from a production apparatus, analyzing the collected information, and outputting and analyzing the information obtained by the analysis.
  • Patent Document 2 discloses a technique for collecting processing statuses, searching for processing that satisfies a necessary condition, and instructing a progress plan.
  • Patent Document 3 discloses a technique for extracting determination data from inspection measurement data, processing the determination data, and transmitting the processed determination data to a host process.
  • Patent Document 4 discloses a technique for collecting manufacturing information, distributing manufacturing information based on a definition table, and transmitting a work instruction based on the distributed manufacturing information.
  • production data can be collected and analyzed.
  • the best method for collecting and analyzing production data has not been identified.
  • An object of the present invention is to enable a production apparatus to be controlled based on a measurement value indicating the state of the production apparatus.
  • the production control device of the present invention is A measurement difference calculation unit that calculates a difference between a measurement value indicating the status of the production apparatus and a model value that is a target value as a measurement difference;
  • a parameter control unit configured to change a parameter value of a control parameter for controlling the production apparatus when the measurement difference is greater than a measurement tolerance;
  • the production apparatus can be controlled based on the measurement value indicating the state of the production apparatus.
  • FIG. 1 is a configuration diagram of a production management system 200 according to Embodiment 1.
  • FIG. 1 is a configuration diagram of a production control device 100 according to Embodiment 1.
  • FIG. 3 is a configuration diagram of a model value evaluation unit 130 in the first embodiment.
  • FIG. 3 is a configuration diagram of a parameter value evaluation unit 140 in the first embodiment.
  • FIG. 3 is a configuration diagram of a storage unit 191 in the first embodiment.
  • FIG. 3 is a configuration diagram of production data 300 in the first embodiment.
  • FIG. 6 shows a plurality of measurement value files 310 according to the first embodiment.
  • 3 is a flowchart of a production control method according to Embodiment 1.
  • Embodiment 1 FIG.
  • the production management system 200 will be described with reference to FIGS.
  • the configuration of the production management system 200 will be described based on FIG.
  • the production management system 200 is a system that manages production. Specifically, the production management system 200 is an automated production system that uses a large number of sensors in a next-generation factory.
  • the production management system 200 includes a production control device 100, a plurality of production devices (210A to 210C), an information system 220, a management system 230, and a user terminal 240.
  • Each of the plurality of production apparatuses (210A to 210C) includes a control device (211A to 211C).
  • the production apparatuses 210A to 210C are collectively referred to as production apparatuses 210.
  • the control device 211A to the control device 211C are collectively referred to as the control device 211.
  • the production control apparatus 100 communicates with the control device 211 via the network 201. Further, the production control apparatus 100 communicates with the information system 220 and the management system 230 via the network 202.
  • the production control device 100 is a device that controls the production device 210. Specifically, the production control apparatus 100 is a manufacturing execution system (MES: Manufacturing Execution System). Details of the production control apparatus 100 will be described later.
  • MES Manufacturing Execution System
  • the production apparatus 210 is an apparatus that produces products or other items, and includes a control device 211.
  • the control device 211 is a device having a control parameter for controlling the production apparatus 210.
  • the production apparatus 210 produces an object by operating based on the parameter value set in the control parameter.
  • the production apparatus 210 periodically generates production data.
  • the production data includes a plurality of measurement values corresponding to a plurality of indexes.
  • the measured value is a value indicating the status of the production apparatus.
  • the measured value is a value actually measured by the production apparatus 210. The types of indicators will be described later.
  • the information system 220 is a system that communicates with the production control apparatus 100, the management system 230, and the user terminal 240 via the network 202. Specifically, the information system 220 is a data processing center provided in the cloud.
  • the management system 230 is a system that manages the production apparatus 210.
  • the management system 230 is an enterprise resource planning system in ERP (Enterprise Resource Planning).
  • ERP Enterprise Resource Planning
  • the enterprise resource planning system has real-time characteristics.
  • the management system 230 issues a dynamic instruction for each production device 210, so that the entire production can be reconfigured without stopping the production.
  • User terminal 240 is a terminal used by a user to use information system 220.
  • the production control device 100 is a computer including hardware such as a processor 901, a memory 902, an auxiliary storage device 903, an input device 904, a communication device 905, and a display 906. These hardwares are connected to each other via signal lines.
  • the processor 901 is an IC (Integrated Circuit) that performs processing, and controls other hardware.
  • the processor 901 is a CPU, DSP, or GPU.
  • CPU is an abbreviation for Central Processing Unit
  • DSP is an abbreviation for Digital Signal Processor
  • GPU is an abbreviation for Graphics Processing Unit.
  • the memory 902 is a volatile storage device.
  • the memory 902 is also called main memory or main memory.
  • the memory 902 is a RAM (Random Access Memory).
  • the auxiliary storage device 903 is a nonvolatile storage device.
  • the auxiliary storage device 903 is a ROM, HDD, or flash memory. ROM is an abbreviation for Read Only Memory, and HDD is an abbreviation for Hard Disk Drive.
  • Hardware in which the processor 901, the memory 902, and the auxiliary storage device 903 are collected is referred to as a “processing circuit”.
  • the input device 904 is a device that accepts input. Specifically, the input device 904 is a keyboard, a mouse, a numeric keypad, or a touch panel.
  • the communication device 905 is a device that performs communication, and includes a receiver and a transmitter. Specifically, the communication device 905 is a communication chip or a NIC (Network Interface Card).
  • a display 906 is a display device that displays an image or the like. Specifically, the display 906 is a liquid crystal display. The display 906 is also called a monitor.
  • the production control apparatus 100 includes “units” such as a measurement value collection unit 110, a measurement value extraction unit 120, a model value evaluation unit 130, a parameter value evaluation unit 140, and a measurement value provision unit 150 as functional configuration elements. .
  • the function of “part” is realized by software. The function of “part” will be described later.
  • the auxiliary storage device 903 stores a program that realizes the function of “unit”.
  • a program that realizes the function of “unit” is loaded into the memory 902 and executed by the processor 901.
  • the auxiliary storage device 903 stores an OS (Operating System). At least a part of the OS is loaded into the memory 902 and executed by the processor 901. That is, the processor 901 executes a program that realizes the function of “unit” while executing the OS.
  • Data obtained by executing a program that realizes the function of “unit” is stored in a storage device such as the memory 902, the auxiliary storage device 903, a register in the processor 901, or a cache memory in the processor 901.
  • the memory 902 functions as a storage unit 191 that stores data used, generated, input, output, transmitted, or received by the production control apparatus 100. However, other storage devices may function as the storage unit 191.
  • the input device 904 functions as a reception unit 192 that receives input.
  • the communication device 905 functions as a communication unit that communicates data. In the communication device 905, the receiver functions as a receiving unit that receives data, and the transmitter functions as a transmitting unit that transmits data.
  • the display 906 functions as a display unit that displays an image or the like.
  • the production control apparatus 100 may include a plurality of processors that replace the processor 901.
  • the plurality of processors share execution of a program that realizes the function of “unit”.
  • a program that realizes the function of “unit” can be stored in a computer-readable manner in a nonvolatile storage medium such as a magnetic disk, an optical disk, or a flash memory.
  • a non-volatile storage medium is a tangible medium that is not temporary.
  • Part may be read as “processing” or “process”.
  • the function of “unit” may be realized by firmware.
  • the model value evaluation unit 130 includes an average value calculation unit 131, an average difference calculation unit 132, an average difference determination unit 133, a model value update unit 134, and a notification unit 135. These functions will be described later.
  • the configuration of the parameter value evaluation unit 140 will be described with reference to FIG.
  • the parameter value evaluation unit 140 includes a measurement difference calculation unit 141, a measurement difference determination unit 142, and a parameter control unit 143. These functions will be described later.
  • the storage unit 191 stores a plurality of measurement value files 310, a model value list 320, an average tolerance list 330, a measurement tolerance list 340, and the like.
  • the plurality of measurement value files 310 correspond to a plurality of indices. The types of indicators will be described later.
  • the measurement value file 310 includes a plurality of measurement values obtained from the plurality of production apparatuses 210. Specifically, the measurement value file 310 includes a measurement value for each set of the index and the production apparatus 210.
  • the model value list 320 includes model values for each set of the index and the production apparatus 210.
  • the model value is a target value.
  • the model value is a reference value for product production derived by big data analysis.
  • the average tolerance list 330 includes an average tolerance for each index. The average tolerance is the upper limit of the allowed average difference.
  • the average difference is a difference between an average of a plurality of measurement values and a model value.
  • the measurement tolerance list 340 includes a measurement tolerance for each index. The measurement tolerance is an upper limit of an allowable measurement difference. The measurement difference is a difference between the measurement value and the model value.
  • the operation of the production control apparatus 100 corresponds to a production control method.
  • the procedure of the production control method corresponds to the procedure of the production control program.
  • the measurement value collection process is periodically executed by the measurement value collection unit 110.
  • the measurement value collection unit 110 collects production data 300 from each production device 210.
  • the production data 300 includes a plurality of measurement values corresponding to a plurality of indexes.
  • the production data 300 will be described with reference to FIG.
  • the production data 300 includes index data such as production index data 301, maintenance index data 302, quality index data 303, inventory index data 304, and environmental index data 305.
  • the production index data 301 is data including measurement values related to the production index.
  • the production index will be described later.
  • the maintenance index data 302 is data including measurement values related to the maintenance index.
  • the quality index data 303 is data including measurement values related to the quality index.
  • the quality index will be described later.
  • the inventory index data 304 is data including measurement values related to the inventory index.
  • the environmental index data 305 is data including measurement values related to the environmental index. The environmental index will be described later.
  • the measurement value collection unit 110 After acquiring the production data 300, the measurement value collection unit 110 registers the measurement value included in the index data in the measurement value file 310 corresponding to the type of the index data for each index data included in the production data 300.
  • a plurality of measurement value files 310 will be described with reference to FIG.
  • the plurality of measurement value files 310 are classified into a production index data sheet 311, a maintenance index data sheet 312, a quality index data sheet 313, an inventory index data sheet 314, and an environmental index data sheet 315.
  • the production index data sheet 311 is a measurement value file 310 in which measurement values relating to production indices are registered.
  • the production index is classified into raw material call time, production process identifier, part quality, production process event history, and the like.
  • the measurement value collection unit 110 registers the measurement value included in the production index data 301 in the production index data sheet 311.
  • the maintenance index data sheet 312 is a measurement value file 310 in which measurement values related to the maintenance index are registered.
  • Maintenance indicators are classified into production process event history, device health status, number of inspections, and the like.
  • the measurement value collection unit 110 registers the measurement value included in the maintenance index data 302 in the maintenance index data sheet 312.
  • the quality index data sheet 313 is a measurement value file 310 in which measurement values related to the quality index are registered.
  • the quality index is classified into parts quality and production process event history.
  • the measurement value collection unit 110 registers the measurement values included in the quality index data 303 in the quality index data sheet 313.
  • the inventory index data sheet 314 is a measurement value file 310 in which measurement values related to the inventory index are registered.
  • the inventory index is classified into raw material call time and production process identifier.
  • the measurement value collection unit 110 registers the measurement values included in the inventory index data 304 in the inventory index data sheet 314.
  • the environmental index data sheet 315 is a measured value file 310 in which measured values related to the environmental index are registered.
  • Environmental indicators are categorized into power consumption, operating hours, and number of inspections.
  • the measured value collection unit 110 registers the measured value included in the environmental index data 305 in the environmental index data sheet 315.
  • step S ⁇ b> 110 the user operates the input device 904 to input index designation to the production control device 100.
  • the index designation is an instruction that designates one of a plurality of indices. That is, the user can specify an index via an HMI (Human Machine Interface).
  • the reception part 192 receives the input parameter
  • An index specified by index specification is called a specified index.
  • Step S120 is measurement value extraction processing.
  • the measurement value extraction unit 120 extracts a measurement value corresponding to the specified index from the measurement value file 310 corresponding to the specified index.
  • the extracted measurement value is the newest measurement value.
  • the measurement value extraction unit 120 selects a measurement value file 310 corresponding to the specified index from the plurality of measurement value files 310. Then, the measurement value extraction unit 120 extracts a measurement value corresponding to the specified index for each production device 210 from the selected measurement value file 310.
  • Step S131 is an average value calculation process.
  • the average value calculation unit 131 calculates a measurement average value using the measurement value extracted in step S120.
  • the measurement average value is an average of a plurality of measurement values corresponding to the plurality of production apparatuses 210.
  • the average value Da can be expressed by the following formula (1) using the measured value Dg. i means the i-th production device 210, and n means the number of production devices 210.
  • Step S132 is an average difference calculation process.
  • the average difference calculation unit 132 calculates the average difference using the average value calculated in step S131 and the model value corresponding to the specified index.
  • the average difference is a difference between the average value and the model value.
  • the average difference calculation unit 132 extracts a model value corresponding to the specified index from the model value list 320, and calculates a difference between the extracted model value and the average value calculated in step S131.
  • the calculated difference is the average difference.
  • the average difference Ee can be expressed by the following formula (2) using the average value Da and the model value Dm.
  • i means the i-th production device 210, and n means the number of production devices 210.
  • Step S133 is an average difference determination process.
  • the average difference determination unit 133 compares the average difference calculated in step S132 with the average tolerance. Specifically, the average difference determination unit 133 extracts an average tolerance corresponding to the designated index from the average tolerance list 330. Then, the average difference determination unit 133 compares the average difference calculated in step S132 with the average tolerance extracted from the average tolerance list 330. If the average difference is less than or equal to the average tolerance, the process proceeds to step S141. If the average difference is greater than the average tolerance, the process proceeds to step S134.
  • Step S134 is a model value update process.
  • the model value update unit 134 updates the model value used in step S132.
  • the model value update unit 134 updates the model value as follows.
  • Information system 220 may provide new model values.
  • the model value update unit 134 acquires a new model value corresponding to the designated index from the information system 220. More specifically, the model value update unit 134 acquires a new model value corresponding to the specified index for each production apparatus 210 from the information system 220.
  • the model value update unit 134 selects a model value corresponding to the specified index for each production apparatus 210 from the model value list 320. Then, the model value update unit 134 updates the model value selected for each production apparatus 210 to a new model value.
  • Step S135 is a notification process.
  • the notification unit 135 notifies the management system 230 that the average difference corresponding to the designated index is larger than the average tolerance.
  • the reporting unit 135 transmits an event for notifying that the average difference corresponding to the designated index is larger than the average tolerance to the management system 230.
  • the management system 230 inquires of the information system 220 whether or not the model value corresponding to the designated index needs to be changed. When there is feedback from the information system 220 that the model value corresponding to the specified index needs to be changed, the information system 220 checks whether or not the production plan needs to be changed. After step S135, the process ends.
  • Step S141 is a measurement difference calculation process.
  • the measurement difference calculation unit 141 calculates a measurement difference using the measurement value extracted in step S120 and the model value corresponding to the specified index.
  • the measurement difference is a difference between the measurement value and the model value.
  • the measurement difference calculation unit 141 extracts the model value corresponding to the specified index from the model value list 320, and calculates the difference between the extracted model value and the measurement value extracted in step S120.
  • the calculated difference is a measurement difference.
  • the measurement difference Ec can be expressed by the following equation (3) using the measurement value Dg and the model value Dm.
  • i means the i-th production device 210, and n means the number of production devices 210.
  • Step S142 is a measurement difference determination process.
  • the measurement difference determination unit 142 compares the measurement difference calculated in step S141 with the measurement tolerance. Specifically, the measurement difference determination unit 142 extracts a measurement tolerance corresponding to the specified index from the measurement tolerance list 340. Then, the measurement difference determination unit 142 compares the measurement difference calculated in step S141 with the measurement tolerance extracted from the measurement tolerance list 340. If the measurement difference is less than or equal to the measurement tolerance, the process ends. If the measurement difference is larger than the measurement tolerance, the process proceeds to step S143.
  • Step S143 is a parameter control process.
  • the parameter control unit 143 changes the parameter value of the control parameter that controls the production apparatus 210.
  • the parameter control unit 143 changes the parameter value for each production apparatus 210 as follows. First, the parameter control unit 143 acquires a parameter value set in the control device 211 of the production apparatus 210 from the control device 211. At this time, the acquisition of the parameter value has priority over the collection of production data. Next, the parameter control unit 143 changes the acquired parameter value. Specifically, the parameter control unit 143 determines the change amount based on the magnitude of the measurement difference, and increases or decreases the parameter value based on the magnitude of the measurement value and the model value. Then, the parameter control unit 143 gives the changed parameter value to the control device 211. The control device 211 receives the changed parameter value and updates the set parameter value to the changed parameter value. After step S143, the process ends.
  • the measurement value providing process is periodically executed by the measurement value providing unit 150.
  • the measurement value providing unit 150 provides a plurality of measurement value files 310 to the information system 220. Specifically, the measurement value providing unit 150 compresses the data sheet for each data sheet shown in FIG. 7 and transmits the compressed data sheet to the information system 220.
  • the production control apparatus 100 can optimally manage the control parameters of the production apparatus 210 by comparing model values such as product indices and environmental indices with measured values of production data. Specifically, when the measured value is significantly different from the model value, it is possible to dynamically issue a control instruction online on the next cycle when production data is collected. As a result, the production process can be optimized. If the measured average value is significantly different from the model value, the production control apparatus 100 immediately notifies the management system 230. The notification is reflected in the ERP as a production event, and procurement and production plans are adjusted at an early timing.
  • the function of the production control apparatus 100 may be realized by hardware.
  • FIG. 9 shows a configuration when the functions of the production control apparatus 100 are realized by hardware.
  • the production control apparatus 100 includes a processing circuit 990.
  • the processing circuit 990 is also called a processing circuit.
  • the processing circuit 990 is a dedicated electronic that realizes the function of “unit” such as the measurement value collection unit 110, the measurement value extraction unit 120, the model value evaluation unit 130, the parameter value evaluation unit 140, the measurement value provision unit 150, and the storage unit 191. Circuit.
  • the processing circuit 990 is a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, a logic IC, a GA, an ASIC, an FPGA, or a combination thereof.
  • GA is an abbreviation for Gate Array
  • ASIC is an abbreviation for Application Specific Integrated Circuit
  • FPGA is an abbreviation for Field Programmable Gate Array.
  • the production control apparatus 100 may include a plurality of processing circuits that substitute for the processing circuit 990.
  • the plurality of processing circuits share the function of “unit”.
  • the functions of the production control device 100 may be realized by a combination of software and hardware. That is, a part of the function of “unit” may be realized by software, and the rest of the function of “unit” may be realized by hardware.
  • the embodiment is an example of a preferred embodiment and is not intended to limit the technical scope of the present invention.
  • the embodiment may be implemented partially or in combination with other embodiments.
  • the procedure described using the flowchart and the like may be changed as appropriate.
  • 100 production control device 110 measurement value collection unit, 120 measurement value extraction unit, 130 model value evaluation unit, 131 average value calculation unit, 132 average difference calculation unit, 133 average difference determination unit, 134 model value update unit, 135 notification unit 140 parameter value evaluation unit, 141 measurement difference calculation unit, 142 measurement difference determination unit, 143 parameter control unit, 150 measurement value providing unit, 191 storage unit, 192 reception unit, 200 production management system, 201 network, 202 network, 210 Production equipment, 211 Control equipment, 220 Information system, 230 Management system, 240 User terminal, 300 Production data, 301 Production index data, 302 Maintenance index data, 303 Quality index data, 304 Inventory index data, 305 Environment indicator Data, 310 Measurement value file, 311 Production index data sheet, 312 Maintenance index data sheet, 313 Quality index data sheet, 314 Inventory index data sheet, 315 Environmental index data sheet, 320 Model value list, 330 Average tolerance list, 340 measurement Tolerance list, 901 processor, 902 memory, 903 auxiliary storage device, 904 input device, 905 communication device

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PCT/JP2016/066046 2016-05-31 2016-05-31 生産制御装置および生産制御プログラム WO2017208357A1 (ja)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021200222A1 (ja) * 2020-03-31 2021-10-07 ダイキン工業株式会社 仕様記述プログラム及び仕様記述方法
WO2022145225A1 (ja) * 2020-12-28 2022-07-07 東京エレクトロン株式会社 パラメータ導出装置、パラメータ導出方法及びパラメータ導出プログラム

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2000252179A (ja) * 1999-03-04 2000-09-14 Hitachi Ltd 半導体製造プロセス安定化支援システム
JP2010087459A (ja) * 2008-09-08 2010-04-15 Toshiba Corp 故障原因特定装置および方法
JP5877908B2 (ja) * 2012-10-24 2016-03-08 東京エレクトロン株式会社 補正値算出装置、補正値算出方法及びコンピュータプログラム

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2000252179A (ja) * 1999-03-04 2000-09-14 Hitachi Ltd 半導体製造プロセス安定化支援システム
JP2010087459A (ja) * 2008-09-08 2010-04-15 Toshiba Corp 故障原因特定装置および方法
JP5877908B2 (ja) * 2012-10-24 2016-03-08 東京エレクトロン株式会社 補正値算出装置、補正値算出方法及びコンピュータプログラム

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2021200222A1 (ja) * 2020-03-31 2021-10-07 ダイキン工業株式会社 仕様記述プログラム及び仕様記述方法
JP2021163058A (ja) * 2020-03-31 2021-10-11 ダイキン工業株式会社 仕様記述プログラム及び仕様記述方法
WO2022145225A1 (ja) * 2020-12-28 2022-07-07 東京エレクトロン株式会社 パラメータ導出装置、パラメータ導出方法及びパラメータ導出プログラム

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