WO2021153228A1 - Dispositif d'estimation d'orientation de platine, dispositif de transport, et procédé d'estimation d'orientation de platine - Google Patents

Dispositif d'estimation d'orientation de platine, dispositif de transport, et procédé d'estimation d'orientation de platine Download PDF

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Publication number
WO2021153228A1
WO2021153228A1 PCT/JP2021/000818 JP2021000818W WO2021153228A1 WO 2021153228 A1 WO2021153228 A1 WO 2021153228A1 JP 2021000818 W JP2021000818 W JP 2021000818W WO 2021153228 A1 WO2021153228 A1 WO 2021153228A1
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WIPO (PCT)
Prior art keywords
stage
estimation
input data
unit
posture estimation
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PCT/JP2021/000818
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English (en)
Japanese (ja)
Inventor
宏昭 臼本
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株式会社Ｓｃｒｅｅｎホールディングス
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Application filed by 株式会社Ｓｃｒｅｅｎホールディングス filed Critical 株式会社Ｓｃｒｅｅｎホールディングス
Priority to KR1020227025709A priority Critical patent/KR20220120645A/ko
Priority to CN202180011089.XA priority patent/CN115023660A/zh
Publication of WO2021153228A1 publication Critical patent/WO2021153228A1/fr

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    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
    • G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
    • G03F7/70—Microphotolithographic exposure; Apparatus therefor
    • G03F7/70691—Handling of masks or workpieces
    • G03F7/70783—Handling stress or warp of chucks, masks or workpieces, e.g. to compensate for imaging errors or considerations related to warpage of masks or workpieces due to their own weight
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
    • G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
    • G03F7/20—Exposure; Apparatus therefor
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
    • G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
    • G03F7/70—Microphotolithographic exposure; Apparatus therefor
    • G03F7/70216—Mask projection systems
    • G03F7/70283—Mask effects on the imaging process
    • G03F7/70291—Addressable masks, e.g. spatial light modulators [SLMs], digital micro-mirror devices [DMDs] or liquid crystal display [LCD] patterning devices
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
    • G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
    • G03F7/70—Microphotolithographic exposure; Apparatus therefor
    • G03F7/70216—Mask projection systems
    • G03F7/70358—Scanning exposure, i.e. relative movement of patterned beam and workpiece during imaging
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03F—PHOTOMECHANICAL PRODUCTION OF TEXTURED OR PATTERNED SURFACES, e.g. FOR PRINTING, FOR PROCESSING OF SEMICONDUCTOR DEVICES; MATERIALS THEREFOR; ORIGINALS THEREFOR; APPARATUS SPECIALLY ADAPTED THEREFOR
    • G03F7/00—Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printing surfaces; Materials therefor, e.g. comprising photoresists; Apparatus specially adapted therefor
    • G03F7/70—Microphotolithographic exposure; Apparatus therefor
    • G03F7/70691—Handling of masks or workpieces
    • G03F7/70716—Stages
    • 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
    • H01L21/67—Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereof; Apparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components ; Apparatus not specifically provided for elsewhere
    • H01L21/67005—Apparatus not specifically provided for elsewhere
    • H01L21/67242—Apparatus for monitoring, sorting or marking
    • H01L21/67288—Monitoring of warpage, curvature, damage, defects or the like
    • 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
    • H01L21/67—Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereof; Apparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components ; Apparatus not specifically provided for elsewhere
    • H01L21/68—Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereof; Apparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components ; Apparatus not specifically provided for elsewhere for positioning, orientation or alignment
    • 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
    • H01L21/67—Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereof; Apparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components ; Apparatus not specifically provided for elsewhere
    • H01L21/683—Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereof; Apparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components ; Apparatus not specifically provided for elsewhere for supporting or gripping
    • H01L21/687—Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereof; Apparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components ; Apparatus not specifically provided for elsewhere for supporting or gripping using mechanical means, e.g. chucks, clamps or pinches
    • H01L21/68714—Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereof; Apparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components ; Apparatus not specifically provided for elsewhere for supporting or gripping using mechanical means, e.g. chucks, clamps or pinches the wafers being placed on a susceptor, stage or support
    • H01L21/68764—Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereof; Apparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components ; Apparatus not specifically provided for elsewhere for supporting or gripping using mechanical means, e.g. chucks, clamps or pinches the wafers being placed on a susceptor, stage or support characterised by a movable susceptor, stage or support, others than those only rotating on their own vertical axis, e.g. susceptors on a rotating caroussel

Definitions

  • the present invention relates to a technique for estimating the yawing angle of a stage in a transfer device that conveys a flat plate-shaped stage by a transfer mechanism.
  • Patent Document 1 describes a device that draws an exposure pattern on the upper surface of a substrate (W) while moving a stage (10) on which a substrate (W) is placed by a stage moving mechanism (20). ..
  • the stage transfer device mounted on this type of device may be equipped with a pair of straight-ahead mechanisms. Specifically, there is known a mechanism for transporting a stage in a predetermined direction by a pair of linear motors provided in parallel with each other.
  • the conventional transfer device was equipped with a large-scale measuring device in order to grasp the fluctuation of the yawing angle described above. Then, the operation of the transport device was corrected based on the measurement result of the measuring device. However, if a large-scale measuring device is mounted, it becomes difficult to miniaturize the transport device. In addition, by mounting the measuring device, the manufacturing cost of the transport device also increases.
  • each of the plurality of machine learning algorithms has strengths and weaknesses, and the estimation accuracy of each machine learning algorithm varies depending on the operating condition of the transfer device. Therefore, depending on only one trained model generated by one machine learning algorithm, it may not be possible to perform accurate estimation depending on the operating condition of the transport device.
  • the present invention has been made in view of such circumstances, and can estimate the yawing angle of the stage without constantly installing a large-scale measuring device, and realizes high estimation accuracy in many operating conditions of the transport device.
  • the purpose is to provide the technology that can be used.
  • the first invention of the present application is a stage attitude estimation device that estimates the yawing angle of the stage in a transfer device that conveys a flat plate-shaped stage by a transfer mechanism, and is output from the transfer mechanism.
  • An input data acquisition unit that acquires the measured value or a value calculated based on the measured value as input data, and an attitude estimation that estimates the yawing angle of the stage based on the input data and outputs the estimation result.
  • the posture estimation unit includes a unit, a plurality of trained models that output a tentative estimated value of the yawing angle of the stage based on the input data, and a plurality of the trained models that are output from the plurality of trained models. It has an estimated value determining unit that determines the estimated result based on the tentative estimated value.
  • the second invention of the present application is the stage posture estimation device of the first invention, and the plurality of trained models are generated by algorithms different from each other.
  • the third invention of the present application is the stage posture estimation device of the first invention or the second invention, and the estimated value determining unit uses the average value of the plurality of tentative estimated values as the estimated result.
  • the fourth invention of the present application is the stage posture estimation device of the first invention or the second invention, in which weight ratios are set in the plurality of trained models, and the estimated value determining unit determines the weight ratios.
  • the weighted average value of the plurality of tentative estimated values used is used as the estimated result.
  • the fifth invention of the present application is the stage posture estimation device of the fourth invention, and the estimated value determining unit changes the weighting ratio based on a state variable representing an operating state of the transport mechanism.
  • the sixth invention of the present application is the stage posture estimation device of the first invention or the second invention, and the estimated value determining unit is based on a state variable representing an operating state of the transport mechanism, and has a plurality of tentative estimated values. One of them is selected, and the selected tentative estimated value is used as the estimated result.
  • the seventh invention of the present application is the stage attitude estimation device of any one of the first to sixth inventions, wherein the transport mechanism transports the stage by a pair of straight-moving mechanisms, and the input data acquisition unit. Generates the input data based on the difference between the torque values of the pair of straight-ahead mechanisms.
  • the eighth invention of the present application is a transport device, and includes the stage posture estimation device of any one of the first to seventh inventions, the stage, and the transport mechanism.
  • the ninth invention of the present application is a stage attitude estimation method for estimating the yawing angle of the stage in a transport device that transports a flat plate-shaped stage by a transport mechanism, and a) a measured value output from the transport mechanism or the said.
  • the step includes a step of acquiring a value calculated based on a measured value as input data, and b) a step of estimating a yawing angle of the stage based on the input data and outputting an estimation result.
  • the input data is input to the plurality of trained models, and the estimation result is determined based on the plurality of tentative estimation values output from the plurality of trained models.
  • the yawing angle of the stage is estimated based on the measured value output from the transport mechanism or the value calculated based on the measured value. This makes it possible to estimate the yawing angle of the stage without constantly installing a large-scale measuring device.
  • one estimation result is output based on a plurality of tentative estimates output from the plurality of trained models. As a result, high estimation accuracy can be realized in many operating conditions of the transport device.
  • main scanning direction the direction in which the stage moves by the pair of straight-moving mechanisms
  • secondary scanning direction the direction orthogonal to the main scanning direction
  • FIG. 1 is a perspective view of a drawing device 1 provided with a transfer device 10 according to an embodiment of the present invention.
  • FIG. 2 is a schematic top view of the drawing apparatus 1.
  • the drawing device 1 is a device that irradiates the upper surface of a substrate W such as a semiconductor substrate or a glass substrate coated with a photosensitive material with spatially modulated light to draw an exposure pattern on the upper surface of the substrate W.
  • the drawing device 1 includes a transfer device 10, a frame 20, a drawing processing unit 30, and a control unit 40.
  • the transport device 10 is a device that transports the flat plate-shaped stage 12 in a substantially constant posture in the horizontal direction on the upper surface of the base 11.
  • the transport device 10 has a transport mechanism including a main scanning mechanism 13 and a sub scanning mechanism 14.
  • the main scanning mechanism 13 is a mechanism for transporting the stage 12 in the main scanning direction.
  • the sub-scanning mechanism 14 is a mechanism for transporting the stage 12 in the sub-scanning direction.
  • the substrate W is held on the upper surface of the stage 12 in a horizontal posture, and moves together with the stage 12 in the main scanning direction and the sub-scanning direction.
  • the frame 20 has a structure for holding the drawing processing unit 30 above the base 11.
  • the frame 20 has a pair of strut portions 21 and a cross-linking portion 22.
  • the pair of support columns 21 are erected at intervals in the sub-scanning direction.
  • Each support column 21 extends upward from the upper surface of the base 11.
  • the cross-linked portion 22 extends in the sub-scanning direction between the upper ends of the two strut portions 21.
  • the stage 12 holding the substrate W passes between the pair of support columns 21 and below the cross-linked portion 22.
  • the drawing processing unit 30 has two optical heads 31, an illumination optical system 32, a laser oscillator 33, and a laser drive unit 34.
  • the two optical heads 31 are fixed to the cross-linked portion 22 at intervals in the sub-scanning direction.
  • the illumination optical system 32, the laser oscillator 33, and the laser drive unit 34 are housed in, for example, the internal space of the cross-linking unit 22.
  • the laser drive unit 34 is electrically connected to the laser oscillator 33. When the laser drive unit 34 is operated, pulsed light is emitted from the laser oscillator 33. Then, the pulsed light emitted from the laser oscillator 33 is introduced into the optical head 31 via the illumination optical system 32.
  • An optical system including a spatial modulator is provided inside the optical head 31.
  • the spatial modulator for example, GLV (Grating Light Valve) (registered trademark), which is a diffraction grating type spatial light modulator, is used.
  • the pulsed light introduced into the optical head 31 is modulated into a predetermined pattern by the spatial modulator and is irradiated on the upper surface of the substrate W. As a result, a photosensitive material such as a resist coated on the upper surface of the substrate W is exposed.
  • the drawing device 1 When the drawing device 1 is in operation, the exposure by the optical head 31 and the transfer of the substrate W by the transfer device 10 are repeatedly executed. Specifically, the sub-scanning mechanism 14 conveys the stage 12 in the sub-scanning direction, and irradiates pulsed light from the optical head 31 to expose a band-shaped region (swath) extending in the sub-scanning direction. After that, the main scanning mechanism 13 conveys the stage 12 in the main scanning direction by one swath. The drawing apparatus 1 draws a pattern on the entire upper surface of the substrate W by repeating such exposure in the sub-scanning direction and transfer of the stage 12 in the main scanning direction.
  • the sub-scanning mechanism 14 conveys the stage 12 in the sub-scanning direction, and irradiates pulsed light from the optical head 31 to expose a band-shaped region (swath) extending in the sub-scanning direction.
  • the main scanning mechanism 13 conveys the stage 12 in the main scanning direction by one swa
  • the control unit 40 is a means for controlling the operation of each unit of the drawing device 1.
  • FIG. 3 is a block diagram showing an electrical connection between the control unit 40 and each unit in the drawing device 1.
  • the control unit 40 is composed of a computer having a processor 41 such as a CPU, a memory 42 such as a RAM, and a storage unit 43 such as a hard disk drive.
  • the storage unit 43 stores a computer program P for controlling the operation of the drawing device 1.
  • the control unit 40 includes a drawing processing unit 30 (including the optical head 31 and the laser driving unit 34 described above) and a main scanning mechanism 13 (including a linear motor 61 and an air guide 62 described later). , A sub-scanning mechanism 14 (including a linear motor 71 described later), a rotating mechanism 15 described later, and various sensors 50 are electrically connected.
  • the control unit 40 reads the computer program P and data D stored in the storage unit 43 into the memory 42, and the processor 41 performs arithmetic processing based on the computer program P and data D in the drawing device 1. The operation of each of the above parts is controlled. As a result, the drawing process in the drawing device 1 proceeds.
  • FIG. 4 is a partial cross-sectional view of a portion of the transport device 10 cut along a plane perpendicular to the main scanning direction.
  • the transport device 10 includes a base 11, a stage 12, a main scanning mechanism 13, a sub-scanning mechanism 14, a rotating mechanism 15, a lower support plate 16, a middle support plate 17, and a stage posture estimation. It has a device 18.
  • the base 11 is a support base that supports each part of the transport device 10.
  • the base 11 has a flat plate-like outer shape that extends in the main scanning direction and the sub-scanning direction.
  • Four legs 111 and two dampers 112 are provided on the lower surface of the base 11. The lengths of the legs 111 and the damper 112 can be adjusted individually. Therefore, the posture of the base 11 can be adjusted horizontally by adjusting the lengths of the legs 111 and the damper 112.
  • the lower support plate 16, the middle support plate 17, and the stage 12 each have a flat outer shape.
  • the lower support plate 16 is movably supported in the main scanning direction by the main scanning mechanism 13 on the base 11.
  • the middle-stage support plate 17 is movably supported on the lower-stage support plate 16 by the sub-scanning mechanism 14 in the sub-scanning direction.
  • the stage 12 is rotatably supported around a vertical axis by a rotation mechanism 15 on the middle support plate 17.
  • the stage 12 has an upper surface on which the substrate W can be placed. Further, on the upper surface of the stage 12, a chuck pin for holding the substrate W or a plurality of suction holes for sucking the substrate W are provided.
  • the main scanning mechanism 13 is a mechanism for moving the lower support plate 16 with respect to the base 11 in the main scanning direction.
  • the main scanning mechanism 13 has a pair of straight traveling mechanisms 60.
  • the pair of straight-moving mechanisms 60 are provided at both ends of the upper surface of the base 11 in the sub-scanning direction. As shown in FIGS. 2 and 4, each of the pair of straight-moving mechanisms 60 has a linear motor 61 and an air guide 62, respectively.
  • the linear motor 61 has a stator 611 and a mover 612.
  • the stator 611 is laid on the upper surface of the base 11 along the main scanning direction. That is, the pair of stators 611 are arranged parallel to each other.
  • the mover 612 is fixed to the lower support plate 16 via an air bearing 622 described later.
  • the main scanning mechanism 13 has a control board 63 for controlling the operation of the linear motor 61.
  • a control board 63 for example, a servo pack (registered trademark) is used.
  • the control board 63 is electrically connected to the control unit 40.
  • the control board 63 calculates the torque to be generated in the linear motor 61 according to the command from the control unit 40.
  • a drive signal corresponding to the calculated torque is supplied to the stator 611 of each linear motor 61.
  • the mover 612 moves in the main scanning direction along the stator 611 due to the magnetic attraction and repulsion generated between the stator 611 and the mover 612.
  • the air guide 62 has a guide rail 621 and an air bearing 622.
  • the guide rail 621 is laid on the upper surface of the base 11 along the main scanning direction. That is, the stator 611 of the linear motor 61 and the guide rail 621 of the air guide 62 are arranged in parallel with each other.
  • the air bearing 622 is fixed to the lower support plate 16 and the mover 612. Further, the air bearing 622 is arranged above the guide rail 621.
  • a gas outlet 623 is provided on the lower surface of the air bearing 622.
  • gas is constantly supplied from the utility of the factory to the air bearing 622, and the pressurized gas is blown out from the gas outlet 623 toward the upper surface of the guide rail 621.
  • the air bearing 622 is floated and supported on the guide rail 621 in a non-contact manner. Therefore, when the linear motor 61 is driven, the lower support plate 16 moves smoothly along the main scanning direction with low friction in a state of being floated and supported by the air guide 62.
  • the sub-scanning mechanism 14 is a mechanism for moving the middle-stage support plate 17 with respect to the lower-stage support plate 16 in the sub-scanning direction.
  • the sub-scanning mechanism 14 includes a linear motor 71 and a pair of guide mechanisms 72.
  • the linear motor 71 is provided substantially in the center of the upper surface of the lower support plate 16 in the main scanning direction.
  • the linear motor 71 has a stator 711 and a mover 712.
  • the stator 711 is laid on the upper surface of the lower support plate 16 along the sub-scanning direction.
  • the mover 712 is fixed to the middle support plate 17. When the linear motor 71 is driven, the mover 712 moves in the sub-scanning direction along the stator 711 due to the magnetic attraction and repulsion generated between the stator 711 and the mover 712.
  • the pair of guide mechanisms 72 are provided at both ends of the upper surface of the lower support plate 16 in the main scanning direction.
  • the pair of guide mechanisms 72 each have a guide rail 721 and a ball bearing 722.
  • the guide rail 721 is laid on the upper surface of the lower support plate 16 along the sub-scanning direction.
  • the ball bearing 722 is fixed to the lower surface of the middle support plate 17. Further, the ball bearing 722 can move in the sub-scanning direction along the guide rail 721. Therefore, when the linear motor 71 is driven, the middle support plate 17 moves in the sub-scanning direction with respect to the lower support plate 16.
  • the rotation mechanism 15 is a mechanism for adjusting the angle around the vertical axis of the stage 12 with respect to the middle support plate 17.
  • a motor is used for the rotation mechanism 15.
  • the stage 12 rotates about the vertical axis with respect to the middle support plate 17.
  • the angle (yaw angle) ⁇ around the vertical axis of the stage 12 can be adjusted.
  • the stage 12 can be moved in the main scanning direction and the sub-scanning direction with respect to the base 11 by the main scanning mechanism 13, the sub-scanning mechanism 14, and the rotation mechanism 15, and the yawing angle ⁇ is adjusted. It is possible to do.
  • the posture measuring device 80 can be installed in the transport device 10.
  • the posture measuring device 80 is a device for measuring the yawing angle ⁇ of the stage 12.
  • the posture measuring device 80 includes a mirror 81 fixed to the stage 12 and a laser interferometer 82.
  • the mirror 81 is fixed to the edge portion of the stage 12 in the main scanning direction.
  • the laser interferometer 82 is fixed to the upper surface of the base 11.
  • the laser interferometer 82 irradiates the mirror 81 with two laser beams. Then, the optical path difference between the two laser beams is detected by the interference of the two laser beams reflected from the mirror 81. Then, the yawing angle ⁇ of the stage 12 is measured based on the optical path difference.
  • the posture measuring device 80 is installed when performing the pre-learning process described later. After the pre-learning is completed, the posture measuring device 80 can be removed and the transport device 10 can be used.
  • FIG. 5 is a block diagram showing the configuration of the stage posture estimation device 18.
  • the stage posture estimation device 18 is a device that estimates the yawing angle ⁇ of the stage 12 based on the measured values output from the main scanning mechanism 13.
  • the stage posture estimation device 18 includes an input data acquisition unit 91 and a posture estimation unit 92.
  • the input data acquisition unit 91 has a measurement value input unit 911 and an input data generation unit 912.
  • the posture estimation unit 92 has a plurality of trained models M1, M2, M3, ..., And an estimation value determination unit 921.
  • the stage attitude estimation device 18 is composed of a computer having a processor such as a CPU, a memory such as a RAM, and a storage unit such as a hard disk drive. Each function of the measurement value input unit 911, the input data generation unit 912, and the estimation value determination unit 921 is realized by operating the processor according to the computer program stored in the storage unit.
  • the trained models M1, M2, M3, ... Are inference programs whose parameters have been adjusted by pre-learning using a machine learning algorithm.
  • Machine learning algorithms for obtaining trained models M1, M2, M3, ... include, for example, a neural network including a layer neural network and deep learning, a decision tree algorithm including a random forest, gradient boosting, and the like. So-called supervised machine learning algorithms, such as support vector machines, are used.
  • the plurality of trained models M1, M2, M3, ... Are generated by different machine learning algorithms, respectively.
  • the stage posture estimation device 18 may be configured by the same computer as the control unit 40 described above, or may be configured by a computer different from the control unit 40.
  • FIG. 6 is a flowchart showing the flow of the pre-learning process.
  • the posture measuring device 80 described above is installed in the transport device 10 (step S11). Then, the next steps S12 to S15 are repeatedly executed while operating the main scanning mechanism 13.
  • the measured value output from the control board 63 is input to the measured value input unit 911 (step S12).
  • the measured value is, for example, the torque value of the pair of linear motors 61 of the main scanning mechanism 13.
  • the measured value input to the measured value input unit 911 includes other items such as the air pressure of the air bearing 622, the temperature of the guide rail 621, the driving sound of the transport device 10, the vibration of the stage 12, and the position of the stage 12. It may be measured by various sensors 50.
  • the input data generation unit 912 generates the input data d based on the measurement value input to the measurement value input unit 911 (step S13). For example, when the measured values are the torque values of the pair of linear motors 61, the input data generation unit 912 calculates the difference between the torque values. Then, the input data d is generated by removing unnecessary frequencies from the calculated difference time series data. Even when the measured value input to the measured value input unit 911 is other than the torque value, the input data generation unit 912 generates input data d suitable for machine learning by performing a predetermined calculation and filtering process. ..
  • the input data generation unit 912 may use the measurement value itself input to the measurement value input unit 911 as the input data d. That is, the input data generation unit 912 may use the measured value output from the transport mechanism or the value calculated by performing a predetermined calculation and the filtering process on the measured value as the input data d.
  • the posture estimation unit 92 performs machine learning using the input data d generated by the input data generation unit 912 as input and the measurement result ⁇ m of the posture measuring device 80 as teacher data (step S14). That is, the posture estimation unit 92 learns the relationship between the input data d and the measurement result ⁇ m of the posture measuring device 80 by the machine learning algorithm described above.
  • the posture estimation unit 92 of the present embodiment performs the machine learning of step S14 in parallel by a plurality of different machine learning algorithms. Therefore, the machine learning in step S14 generates a plurality of different trained models M1, M2, M3, ...
  • the posture estimation unit 92 compares the output values of the trained models M1, M2, M3, ... Generated by the machine learning in step S14 with the measurement result ⁇ m which is the teacher data. Then, when the difference between the output values of the trained models M1, M2, M3, ... And the measurement result ⁇ m is not equal to or less than the preset threshold value, the posture estimation unit 92 determines the trained models M1, M2. , M3, ... It is determined that the estimation accuracy has not reached a desired level (step S15: no). In this case, the stage posture estimation device 18 repeats the processes of steps S12 to S14 described above. By repeating machine learning in this way, the estimation accuracy of the trained models M1, M2, M3, ... Is gradually improved.
  • the posture estimation unit 92 causes each trained model M1, It is determined that the estimation accuracy of M2, M3, ... Has reached a desired level. In this case, the posture estimation unit 92 ends machine learning (step S15: yes). Then, the posture measuring device 80 is removed from the transport device 10 (step S16). The stage posture estimation device 18 may end machine learning in step S15 when the number of repetitions of steps S12 to S14 reaches a preset upper limit value.
  • FIG. 7 is a flowchart showing the flow of the estimation process.
  • the measured value output from the control board 63 is input to the measured value input unit 911 (step S21).
  • the same type of measurement value as in step S12 described above is input.
  • the measured value input in step S12 is the torque value of the pair of linear motors 61
  • the measured value input in step S21 is also the torque value of the pair of linear motors 61.
  • the input data generation unit 912 generates the input data d based on the measurement value input to the measurement value input unit 911 (step S22).
  • the same process as in step S13 described above is executed. That is, when the process executed in step S13 is the difference calculation and the filter process, the input data d is generated by executing the difference calculation and the filter process in the step S22 as well.
  • the posture estimation unit 92 inputs the generated input data d into the plurality of trained models M1, M2, M3, ... (Step S23). Then, the trained models M1, M2, M3, ... Output the tentative estimated values ⁇ 1, ⁇ 2, ⁇ 3, ... Of the yawing angle ⁇ of the stage 12 corresponding to the input data d. As a result, a plurality of tentative estimated values ⁇ 1, ⁇ 2, ⁇ 3, ... Are obtained for one input data d (step S24).
  • the estimation value determination unit 921 of the posture estimation unit 92 determines one estimation result ⁇ r based on the plurality of provisional estimation values ⁇ 1, ⁇ 2, ⁇ 3, ... (Step S25). Specifically, for example, the estimation value determination unit 921 calculates the average value of a plurality of provisional estimation values ⁇ 1, ⁇ 2, ⁇ 3, ..., And determines the calculated average value as the estimation result ⁇ r. However, the estimated value determination unit 921 may determine the estimated result ⁇ r by another method.
  • FIG. 8 is a flowchart showing a second example of a method of determining the estimation result by the estimation value determination unit 921.
  • the weighting ratios w1, w2, w3, ... are set in advance for each of the trained models M1, M2, M3, ...
  • the weighting ratios w1, w2, w3, ... Are stored in advance in the storage unit of the computer constituting the stage posture estimation device 18.
  • the estimated value determining unit 921 first reads the weighted ratios w1, w2, w3, ... From the storage unit (step S31). Then, the estimated value determination unit 921 calculates and calculates the weighted average value of a plurality of tentative estimated values ⁇ 1, ⁇ 2, ⁇ 3, ... Using the read weighted ratios w1, w2, w3, ... Let the weighted average value be the estimation result ⁇ r (step S32).
  • the estimation result ⁇ r using the weighted average in step S32 can be calculated by the following equation (1).
  • ⁇ r (w1, ⁇ 1 + w2, ⁇ 2 + w3, ⁇ 3) / (w1 + w2 + w3) (1)
  • the weighting ratio of the trained model is relatively set. It is good to set it high. Then, by calculating the weighted average value as described above, a more preferable estimation result ⁇ r can be obtained.
  • FIG. 9 is a flowchart showing a third example of a method of determining the estimation result by the estimation value determination unit 921.
  • the weighting ratios w1, w2, w3, ... Corresponding to each of the trained models M1, M2, M3, ... are not fixed values but depend on the operating state of the main scanning mechanism 13. Change.
  • the estimated value determining unit 921 first acquires a state variable representing the operating state of the main scanning mechanism 13 (step S41).
  • the state variable may be a measured value input to the measured value input unit 911 described above, a variable acquired by another sensor, or an operation set by the user for the control unit 40. It may be a mode or the like.
  • the estimated value determination unit 921 changes the weighting ratios w1, w2, w3, ... Based on the acquired state variables (step S42). As a result, the weighting ratio of the trained model capable of exhibiting high estimation accuracy is increased according to the operating state of the main scanning mechanism 13. For example, in the operation state represented by a certain state variable, when the estimation accuracy of the trained model M2 is particularly high among the plurality of trained models M1, M2, M3, ... , The plurality of weighting ratios w1, w2, w3, ... Are changed so that the value of the weighting ratio w2 becomes relatively high.
  • the estimated value determination unit 921 calculates and calculates the weighted average value of the plurality of tentative estimated values ⁇ 1, ⁇ 2, ⁇ 3, ... Using the changed weighted ratios w1, w2, w3, ... Let the weighted average value be the estimation result ⁇ r (step S43).
  • the trained model to be emphasized can be changed for each operating state. Therefore, it is possible to obtain a more accurate estimation result ⁇ r by increasing the weighting ratio of the trained model that can exhibit high estimation accuracy for each operating state.
  • FIG. 10 is a flowchart showing a fourth example of a method of determining an estimation result by the estimation value determination unit 921.
  • the estimated value determination unit 921 first acquires a state variable representing the operating state of the main scanning mechanism 13 (step S51).
  • the state variable may be a measured value input to the measured value input unit 911 described above, a variable acquired by another sensor, or an operation set by the user for the control unit 40. It may be a mode or the like.
  • the estimated value determination unit 921 selects one of a plurality of tentative estimated values ⁇ 1, ⁇ 2, ⁇ 3, ... Based on the acquired state variables, and estimates the selected tentative estimated values ⁇ r. (Step S52). For example, in the operation state represented by a certain state variable, when the estimation accuracy of the trained model M2 is particularly high among the plurality of trained models M1, M2, M3, ... , The tentative estimated value ⁇ 2 output from the trained model M2 is used as the estimation result ⁇ r.
  • the estimation value determination unit 921 outputs the estimation result ⁇ r to the control unit 40 (step S26).
  • the control unit 40 corrects the yawing angle ⁇ of the stage 12 based on the estimation result ⁇ r of the yawing angle ⁇ output from the posture estimation unit 92 (step S27). Specifically, the control unit 40 operates the rotation mechanism 15 or adjusts the torque value of either of the pair of linear motors 61. As a result, the yawing angle ⁇ of the stage 12 is corrected so as to approach a desired value.
  • the transport device 10 estimates the yawing angle ⁇ of the stage 12 based on the measured value output from the main scanning mechanism 13 or the input data d which is a value calculated based on the measured value.
  • the yawing angle ⁇ of the stage 12 can be estimated without constantly installing the large-scale posture measuring device 80.
  • one estimation result ⁇ r is obtained based on a plurality of tentative estimation values ⁇ 1, ⁇ 2, ⁇ 3, ... Output from the plurality of trained models M1, M2, M3, ... Output. Therefore, high estimation accuracy can be realized in many operating conditions of the transport device 10. Further, in the present embodiment, a plurality of trained models M1, M2, M3, ... Are generated by different machine learning algorithms. Therefore, in an operating situation where it is difficult for a certain machine learning algorithm to exhibit high estimation accuracy, another machine learning algorithm can complement it. As a result, the yawing angle ⁇ of the stage 12 can be estimated accurately in more operating conditions.
  • the measurement value input unit 911 acquires the torque value of the linear motor 61 from the control board 63.
  • the measured value input unit 911 may acquire the torque value of the linear motor 61 by another method.
  • a torque sensor may be attached to each linear motor 61 of the straight-ahead mechanism 60, and a torque value may be acquired from the torque sensor.
  • the same input data d is input to all the trained models M1, M2, M3, ...
  • the input data generation unit 912 may perform different processing for each trained model on the measurement value input to the measurement value input unit 911. Then, different input data generated by different processes may be input to the plurality of trained models M1, M2, M3, .... In this way, more suitable input data can be input for each trained model.
  • the transport device 10 of the above embodiment includes not only the main scanning mechanism 13 but also the sub-scanning mechanism 14 and the rotation mechanism 15.
  • the present invention may be intended for a transfer device that does not include a sub-scanning mechanism 14 and a rotating mechanism 15.
  • the transport device 10 of the above embodiment was mounted on the drawing device 1.
  • the present invention may be intended for a transfer device mounted on a device other than the drawing device 1.
  • the transfer device may be mounted on a device that applies a processing liquid to a substrate held on a stage.
  • the transfer device may be mounted on a device that prints on a recording medium held on the stage.
  • the yawing angle ⁇ of the stage 12 is actually measured by the laser interferometer 82 in the pre-learning process.
  • the yawing angle ⁇ of the stage 12 may be actually measured by another method.
  • the yawing angle ⁇ of the stage 12 may be actually measured based on the image of the stage 12 acquired by the camera.
  • the straight-ahead mechanism 60 of the above-described embodiment has a linear motor 61.
  • a mechanism that converts the rotary motion output from the rotary motor into a linear motion by a ball screw may be used.

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  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Condensed Matter Physics & Semiconductors (AREA)
  • Manufacturing & Machinery (AREA)
  • Computer Hardware Design (AREA)
  • Microelectronics & Electronic Packaging (AREA)
  • Power Engineering (AREA)
  • Container, Conveyance, Adherence, Positioning, Of Wafer (AREA)
  • Exposure And Positioning Against Photoresist Photosensitive Materials (AREA)

Abstract

La présente invention concerne un dispositif d'estimation d'orientation de platine (18) qui comprend : une unité d'acquisition de données d'entrée (91) ; et une unité d'estimation d'orientation (92) qui estime un angle de lacet d'une platine sur la base de données d'entrée. Grâce à cette configuration, il est possible d'estimer l'angle de lacet de la platine sans qu'il soit nécessaire qu'un dispositif de mesure à grande échelle soit installé en tout temps. En outre, l'unité d'estimation d'orientation (92) détermine un résultat d'estimation (θr) sur la base d'une pluralité de valeurs d'estimation provisoires (θ1, θ2, θ3, ...) délivrées par une pluralité de modèles entraînés (M1, M2, M3, ...). Grâce à cette configuration, il est possible d'obtenir une précision d'estimation élevée lorsqu'un dispositif de transport fonctionne dans diverses conditions.
PCT/JP2021/000818 2020-01-28 2021-01-13 Dispositif d'estimation d'orientation de platine, dispositif de transport, et procédé d'estimation d'orientation de platine WO2021153228A1 (fr)

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KR1020227025709A KR20220120645A (ko) 2020-01-28 2021-01-13 스테이지 자세 추정 장치, 반송 장치, 및 스테이지 자세 추정 방법
CN202180011089.XA CN115023660A (zh) 2020-01-28 2021-01-13 载物台姿势推定装置、搬送装置以及载物台姿势推定方法

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JP2003264133A (ja) * 2002-03-08 2003-09-19 Nikon Corp ステージ制御装置、露光装置、デバイス製造方法、及びステージ制御方法
JP2016072434A (ja) * 2014-09-30 2016-05-09 株式会社Ｓｃｒｅｅｎホールディングス パターン形成装置およびパターン形成方法
WO2019189661A1 (fr) * 2018-03-29 2019-10-03 国立大学法人奈良先端科学技術大学院大学 Procédé et dispositif de création d'ensemble de données d'apprentissage
JP2020001127A (ja) * 2018-06-28 2020-01-09 勇貴 高橋 ピッキングシステム，ピッキング処理装置及びプログラム

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JP2003264133A (ja) * 2002-03-08 2003-09-19 Nikon Corp ステージ制御装置、露光装置、デバイス製造方法、及びステージ制御方法
JP2016072434A (ja) * 2014-09-30 2016-05-09 株式会社Ｓｃｒｅｅｎホールディングス パターン形成装置およびパターン形成方法
WO2019189661A1 (fr) * 2018-03-29 2019-10-03 国立大学法人奈良先端科学技術大学院大学 Procédé et dispositif de création d'ensemble de données d'apprentissage
JP2020001127A (ja) * 2018-06-28 2020-01-09 勇貴 高橋 ピッキングシステム，ピッキング処理装置及びプログラム

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