Information processing apparatus, machine learning apparatus, information processing method, and machine learning method

Abstract

The invention provides an information processing apparatus capable of appropriately predicting the influence of electromagnetic waves generated from an AC power line when substrate processing is performed. An information processing device (5) is provided with: a current value information generation unit (501) that generates current value information of an alternating current to be supplied to an alternating current device when substrate processing is performed by a substrate processing device provided with the alternating current device connected to an alternating current power supply via an alternating current power line, and a control panel that controls the alternating current device to be connected to the alternating current power supply via an alternating current power line; a control panel that controls the AC device in order to perform substrate processing in which a processing fluid is supplied to the substrate or the processing member while the processing member is brought into contact with the substrate; and an electromagnetic wave influence information generation unit (502) that generates electromagnetic wave influence information indicating the influence of electromagnetic waves generated from the AC power line on the basis of the current value information generated by the current value information generation unit (501).

Description

Technical Field

[0001] The present invention relates to an information processing device, a machine learning device, an information processing method and a machine learning method. Background Art

[0002] A substrate processing device that performs various processes on substrates such as semiconductor wafers is known as a substrate processing device that performs chemical mechanical polishing (CMP). For example, the substrate processing device rotates a polishing table having a polishing pad while supplying a polishing fluid to the polishing pad from a liquid supply nozzle, and presses the substrate against the polishing pad through a substrate holding portion called a top ring to chemically and mechanically polish the substrate. Then, in order to remove foreign matter such as polishing debris attached to the polished substrate, a cleaning tool is contacted with the polished substrate while supplying a cleaning fluid to perform friction cleaning, and the substrate is further dried, thereby completing a series of substrate processing.

[0003] Patent Documents 1 and 2 disclose substrate processing apparatuses including various devices for performing such substrate processing and a control panel for controlling these devices.

[0004] Prior art literature

[0005] Patent Literature

[0006] Patent Document 1: Japanese Patent Application Laid-Open No. 7-263388

[0007] Patent Document 2: Japanese Patent Application Publication No. 2011-249820

[0008] (Problem that the invention aims to solve)

[0009] As disclosed in Patent Documents 1 and 2, a control panel controls each device, and each device is connected to an AC power source via an AC power line to supply AC current. At this time, electromagnetic waves are generated from the AC power line through which the AC current flows. In order not to affect the normal operation of the substrate processing device, it is required to properly control the influence of the electromagnetic waves. Summary of the invention

[0010] In view of the above problems, the present invention aims to provide an information processing device, a machine learning device, an information processing method and a machine learning method that can appropriately predict the influence of electromagnetic waves generated from AC power lines when substrate processing is performed.

[0011] (Methods of solving the problem)

[0012] In order to achieve the above-mentioned purpose, an information processing device of one embodiment of the present invention comprises: a current value information generating unit, which generates current value information of an AC current supplied to an AC device when a substrate is processed by a substrate processing device, the substrate processing device comprises the AC device and a control panel, the AC device is connected to an AC power supply via an AC power line, the control panel controls the AC device to perform the substrate processing, and during the substrate processing, a processing fluid is supplied to the substrate or the processing component while a processing component is brought into contact with the substrate; and an electromagnetic wave influence information generating unit, which generates electromagnetic wave influence information indicating the influence of electromagnetic waves generated from the AC power line based on the current value information generated by the current value information generating unit.

[0013] (Effects of the Invention)

[0014] When an information processing device using one embodiment of the present invention is used, electromagnetic wave influence information of the AC power line through which the AC current flows is generated based on the current value information of the AC current supplied to the AC device when processing a substrate. Therefore, the influence of electromagnetic waves generated from the AC power line when processing a substrate can be appropriately predicted.

[0015] Problems, structures, and effects other than those described above will become apparent from the modes for carrying out the invention described later. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 1 is a diagram showing the overall configuration of an example of the substrate processing system 1 .

[0017] Figure 2 It is a plan view showing an example of the substrate processing apparatus 2 .

[0018] Figure 3 It is a perspective view showing an example of the first polishing section 22A to the fourth polishing section 22D.

[0019] Figure 4 It is a perspective view showing an example of the first roll sponge cleaning section 24A and the second roll sponge cleaning section 24B.

[0020] Figure 5 It is a perspective view showing an example of the first pen-shaped sponge cleaning unit 24C and the second pen-shaped sponge cleaning unit 24D.

[0021] Figure 6 It is a perspective view showing an example of the first drying section 24E and the second drying section 24F.

[0022] Figure 7 It is a block diagram showing an example of the substrate processing apparatus 2 .

[0023] Figure 8It is a schematic diagram showing an example of the control panel 26 .

[0024] Fig. 9 It is a diagram showing a hardware configuration of an example of the computer 900 .

[0025] Fig.10 It is a data structure diagram showing an example of the production history information 30 managed by the database device 3.

[0026] Fig.11 2 is a data structure diagram showing an example of the test information 31 managed by the database device 3 .

[0027] Fig.12 It is a block diagram showing an example of the machine learning device 4.

[0028] Fig.13 FIG. 1 is a diagram showing an example of the first learning model 10A and the first learning data 11A.

[0029] Fig.14 FIG. 1 is a diagram showing an example of the second learning model 10B and the second learning data 11B.

[0030] Fig.15 This is a flowchart showing an example of a machine learning method performed by the machine learning device 4 .

[0031] Fig.16 It is a block diagram showing an example of the information processing device 5 .

[0032] Fig.17 It is a functional explanation diagram showing an example of the information processing device 5 .

[0033] Fig.18 It is a block diagram showing an example of the user terminal device 6.

[0034] Fig.19 This is a flowchart showing an example of an information processing method implemented by the information processing device 5 and the user terminal device 6.

[0035] Fig. 20 1 is a diagram showing an example of the object display screen 12 on which a virtual object is displayed superimposed on the AC power line 270 in the real space. DETAILED DESCRIPTION

[0036] Hereinafter, the embodiment for implementing the present invention will be described with reference to the drawings. Hereinafter, in the description for achieving the purpose of the present invention, the necessary scope is schematically shown, and the description of this part of the present invention mainly describes the necessary scope, and the omitted description belongs to the known technology.

[0037] Figure 11 is an overall configuration diagram showing an example of a substrate processing system 1. The substrate processing system 1 of the present embodiment functions as a system for managing a series of substrate processing, which includes: a chemical mechanical polishing process (hereinafter referred to as "polishing process") for polishing the surface of a semiconductor wafer or the like by pressing the substrate (hereinafter referred to as "wafer") W against a polishing pad supplied with a polishing fluid, thereby polishing the surface of the wafer W flatly; a cleaning process for cleaning the surface of the wafer W by contacting the wafer W with a cleaning tool while supplying a cleaning fluid to the wafer W after the polishing process; and a drying process for drying the surface of the wafer W after the cleaning process, etc.

[0038] The substrate processing system 1 mainly comprises 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. Each device 2 to 6 is, for example, a general-purpose or special-purpose computer (see the following). Fig. 9 ) and connected to a wired or wireless network 7, and can send and receive various data ( Figure 1 In addition, the number of each device 2 to 6 and the connection structure of the network 7 are not limited to Figure 1 The examples may also be changed appropriately.

[0039] The substrate processing apparatus 2 includes: AC equipment, input equipment, output equipment, control equipment and other equipment (details will be described later) connected to an AC power source AC (three-phase AC 200V, etc.) to operate; and a control panel 26 for controlling each equipment in order to perform substrate processing in which a processing component is brought into contact with a wafer W while a processing fluid is supplied to the wafer W or the processing component. The substrate processing apparatus 2 controls the operation of each equipment while referring to the device setting information 255 composed of a plurality of device parameters set for each equipment and the substrate processing recipe information 256 that specifies the processing content of the substrate processing. In the polishing process, a polishing pad as a processing component in contact with the wafer W and a polishing fluid as a processing fluid supplied to the processing component are used. In the cleaning process, a cleaning tool as a processing component in contact with the wafer W and a cleaning fluid as a processing fluid supplied to the wafer W are used.

[0040] The database device 3 is a device for managing production history information 30, which is information on the history of substrate processing using the wafer W, processing components and processing fluid used in the production, and test information 31, which is information on the results of the states of each device when the substrate is processed by the simulation model. In addition to the above, the database device 3 can also store device setting information 255 and substrate processing plan information 256, and in this case, the substrate processing device 2 can also refer to these information.

[0041] When the substrate processing apparatus 2 is used to process the substrate, the database device 3 receives various reports R from the substrate processing apparatus 2 at any time and registers them in the production history information 30, thereby storing the reports R about the substrate processing in the production history information 30. In addition, when the simulation model is used to perform the test of substrate processing and the test of electromagnetic wave noise, the database device 3 stores the execution conditions and execution results of the simulation in the test information 31 by registering them in correspondence with the test information 31. In addition, instead of the simulation, the test of substrate processing can be performed by the substrate processing apparatus 2 for production or a test apparatus (not shown) that can reproduce the same substrate processing as the substrate processing apparatus 2, and the test conditions and test results can be registered in the test information 31.

[0042] The machine learning device 4 acts as a main body in the learning stage of machine learning, for example, obtains a part of the test information 31 from the database device 3 as the first learning data 11A and the second learning data 11B, and generates the first learning model 10A and the second learning model 10B for use by the information processing device 5 through machine learning. The first learning model 10A and the second learning model 10B that have been learned are provided to the information processing device 5 via the network 7 and the recording medium.

[0043] The information processing device 5 acts as the main body of the inference stage of machine learning, and uses the first learning model 10A and the second learning model 10B generated by the machine learning device 4 to predict the influence of electromagnetic waves generated from the AC power line connecting the AC power source AC and the AC equipment when the substrate is processed, and generates electromagnetic wave influence information representing its prediction results, and sends it to the database device 3, the user terminal device 6, etc.

[0044] The user terminal device 6 is a terminal device used by the user, and may be a fixed device or a portable device. The user terminal device 6 accepts various input operations through a display screen such as an application program or a web browser, and displays various information (e.g., notification events, device setting information 255, substrate processing plan information 256, electromagnetic wave influence information, production history information 30, test information 31, etc.) through the display screen.

[0045] In this embodiment, the user terminal device 6 is mainly described as a portable device that can realize augmented reality (AR) or mixed reality (MR), for example, a portable device such as a smart phone, a tablet terminal, a wearable device such as a smart glass, a transparent head-mounted display, etc. In this case, the user terminal device 6 functions as an information processing device, and when the user performs operations with the substrate processing device 2 in the real space, the information processing device overlaps and displays a virtual object representing the influence of electromagnetic waves with respect to the AC power line in the real space based on the electromagnetic wave influence information provided by the information processing device 5, thereby supporting the user.

[0046] (Substrate processing device 2)

[0047] Figure 2 2 is a top view showing an example of a substrate processing apparatus 2. The substrate processing apparatus 2 is configured by including a loading / unloading unit 21, a grinding unit 22, a substrate conveying unit 23, a processing unit 24, and a control unit 25 inside a frame 20 which is roughly rectangular in plan view. The loading / unloading unit 21 is divided from the grinding unit 22, the substrate conveying unit 23, and the processing unit 24 by a first partition wall 200A, and the substrate conveying unit 23 is divided from the processing unit 24 by a second partition wall 200B. For example, a plurality of air supply devices (not shown) driven by motors are provided on the top plate portion and the side wall portion of the frame 20, and the air pressure of the internal space divided by the first partition wall 200A and the second partition wall 200B is respectively operated in a manner to maintain a higher pressure than that of the external space.

[0048] (Loading / unloading unit)

[0049] The loading / unloading unit 21 comprises: a first front loading section 210A to a fourth front loading section 210D for loading a wafer cassette (FOUP, etc.) that can store multiple wafers W in the up-down direction; a transport robot 211 that can move up and down along the storage direction (up-down direction) of the wafers W stored in the wafer cassette; and a horizontal moving mechanism section 212 that enables the transport robot 211 to move along the arrangement direction (short side direction of the frame 20) of the first front loading section 210A to the fourth front loading section 210D.

[0050] The transfer robot 211 is configured to access the wafer cassettes loaded in the first front loading section 210A to the fourth front loading section 210D, the substrate transfer unit 23 (specifically, the elevator 232 described later), and the processing unit 24 (specifically, the first drying section 24E and the second drying section 24F described later), respectively, and is provided with upper and lower arms (not shown) for transferring wafers W therebetween. The lower arm is used when transferring wafers W before processing, and the upper arm is used when transferring wafers W after processing. When transferring wafers W to the substrate transfer unit 23 and the processing unit 24, a movable door (not shown) provided in the first partition wall 200A is opened and closed.

[0051] in addition, Figure 2 The specific structure of the handling robot 211 and the horizontal moving mechanism 212 is omitted, but it is composed of an appropriate combination of AC equipment such as servo motors; driving force transmission mechanisms such as linear guides, ball screws, gears, belts, couplings, bearings, etc.; output equipment such as fluid pressure cylinders, valves, etc.; input equipment such as linear sensors, encoder sensors, limit sensors, torque sensors, etc.

[0052] (Grinding unit)

[0053] The polishing unit 22 includes first to fourth polishing sections 22A to 22D that respectively perform polishing (planarization) on the wafer W. The first to fourth polishing sections 22A to 22D are arranged side by side along the longitudinal direction of the frame 20 .

[0054] Figure 3 1 is a perspective view showing an example of the first to fourth polishing sections 22A to 22D. The first to fourth polishing sections 22A to 22D have the same basic configuration and function.

[0055] The first grinding section 22A to the fourth grinding section 22D respectively include: a grinding table (processing component supporting part) 220 for supporting a grinding pad 2200 having a grinding surface so as to be rotatable; a top ring (substrate holding part) 221 for rotatably holding a wafer W and grinding the wafer W while pressing it against the grinding pad 2200 on the grinding table 220; a grinding fluid supplying part 222 for supplying a grinding fluid to the grinding pad 2200; a dresser 223 for supporting a dressing disk 2230 so as to be rotatable and making the dressing disk 2230 contact the grinding surface of the grinding pad 2200 to dress the grinding pad 2200; an atomizer 224 for spraying a pad cleaning fluid onto the grinding pad 2200; and an environmental sensor 225 for measuring the internal space state of the frame 20 for performing the grinding process.

[0056] The polishing table 220 includes a rotational movement mechanism 220 b that is supported by a polishing table shaft 220 a and drives the polishing table 220 to rotate about its axis, and a polishing pad surface temperature control mechanism 220 c that controls the surface temperature of the polishing pad 2200 .

[0057] The top ring 221 includes a rotational movement mechanism 221c that is supported by a top ring shaft 221a that can move in the vertical direction and drives the top ring 221 to rotate around its axis, a vertical movement mechanism 221d that moves the top ring 221 in the vertical direction, and a swing movement mechanism 221e that swings (sways) the top ring 221 around the support shaft 221b. The rotational movement mechanism 221c, the vertical movement mechanism 221d, and the swing movement mechanism 221e function as a substrate movement mechanism that moves the relative position of the polishing pad 2200 and the polished surface of the wafer W.

[0058] The polishing fluid supply unit 222 includes: a polishing fluid supply nozzle 222a for supplying the polishing fluid to the polishing surface of the polishing pad 2200; a swing movement mechanism 222c supported by a support shaft 222b and rotatably moving the polishing fluid supply nozzle 222a around the support shaft 222b as the rotation center; a flow rate adjustment unit 222d for adjusting the flow rate of the polishing fluid; and a temperature adjustment mechanism 222e for adjusting the temperature of the polishing fluid. The polishing fluid is a polishing liquid (slurry) or pure water, and may also contain a chemical solution, or a dispersant may be added to the polishing liquid.

[0059] The dresser 223 includes: a rotational movement mechanism portion 223c which is supported by a dresser shaft 223a which is movable in the up-down direction and drives the dresser 223 to rotate around its axis; a vertical movement mechanism portion 223d which moves the dresser 223 in the up-down direction; and a swinging movement mechanism portion 223e which swings the dresser 223 around the support shaft 223b as the center of rotation.

[0060] The atomizer 224 includes a swing mechanism 224b that is supported by a support shaft 224a and rotates the atomizer 224 around the support shaft 224a, and a flow rate adjustment unit 224c that adjusts the flow rate of a pad cleaning fluid. The pad cleaning fluid is a mixed fluid of a liquid (e.g., pure water) and a gas (e.g., nitrogen) or a liquid (e.g., pure water).

[0061] The environmental sensor 225 is composed of an input device arranged in the internal space of the frame 20, and includes, for example, a temperature sensor 225a for measuring the temperature of the internal space; a humidity sensor 225b for measuring the humidity of the internal space; an air pressure sensor 225c for measuring the air pressure of the internal space; an oxygen concentration sensor 225d; and a microphone (sound sensor) 225e. In addition, the environmental sensor 225 may also include a camera (image sensor) that can capture the surface, temperature distribution, airflow distribution, etc. of the polishing pad 2200 during and before and after the polishing process. The camera's captured object is not limited to visible light, and may also be infrared light or ultraviolet light.

[0062] 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 . Then, the top ring 221 presses the polishing surface of the polishing pad 2200 to which the polishing fluid is supplied from the polishing fluid supply nozzle 222 a , for polishing.

[0063] in addition, Figure 3 The specific structure of the rotating moving mechanism parts 220b, 221c, 223c, the up and down moving mechanism parts 221d, 223d and the shaking moving mechanism parts 221e, 222c, 223e, 224b are omitted, but it is composed of an appropriate combination of AC equipment such as servo motors; driving force transmission mechanisms such as linear guides, ball screws, gears, belts, couplings, bearings, etc.; output equipment such as fluid pressure cylinders, valves, etc.; input equipment such as linear sensors, encoder sensors, limit sensors, torque sensors, etc. Figure 3 The specific structure of the flow regulating parts 222d and 224c is omitted, but it is composed of an appropriate combination of output devices such as pumps, valves, and pressure reducing valves for regulating the fluid; and input devices such as flow sensors, pressure sensors, liquid level sensors, temperature sensors, fluid concentration sensors, fluid physical properties sensors, and fluid particle sensors. Figure 3 The specific structure of the temperature control mechanism parts 220c and 222e is omitted in the figure, but it is composed of an appropriate combination of AC equipment such as contact or non-contact heaters; and input equipment such as temperature sensors and current sensors.

[0064] (Substrate transport unit)

[0065] like Figure 2 As shown, the substrate transport unit 23 includes: a first linear conveyor 230A and a second linear conveyor 230B that can move horizontally along the arrangement direction of the first grinding section 22A to the fourth grinding section 22D (the length direction of the frame 20); a swing conveyor 231 arranged between the first linear conveyor 230A and the second linear conveyor 230B; an elevator 232 arranged on the side of the loading / unloading unit 21; and a temporary placement table 233 for the chip W arranged on the side of the processing unit 24.

[0066] The first linear conveyor 230A is disposed adjacent to the first polishing section 22A and the second polishing section 22B, and is a mechanism for conveying the wafer W between four conveying positions (first conveying position TP1 to fourth conveying position TP4 in order from the loading / unloading unit 21 side). The second conveying position TP2 is a position for delivering the wafer W to the first polishing section 22A, and the third conveying position TP3 is a position for delivering the wafer W to the second polishing section 22B.

[0067] The second linear conveyor 230B is disposed adjacent to the third polishing section 22C and the fourth polishing section 22D, and is a mechanism for conveying the wafer W between three conveying positions (the fifth conveying position TP5 to the seventh conveying position TP7 in order from the loading / unloading unit 21 side). The sixth conveying position TP6 is a position for delivering the wafer W to the third polishing section 22C, and the seventh conveying position TP7 is a position for delivering the wafer W to the fourth polishing section 22D.

[0068] The swing conveyor 231 is arranged adjacent to the fourth transfer position TP4 and the fifth transfer position TP5, and has an arm that can move between the fourth transfer position TP4 and the fifth transfer position TP5. The swing conveyor 231 is a mechanism for transferring the wafer W between the first linear conveyor 230A and the second linear conveyor 230B, and temporarily placing the wafer W on the temporary placement table 233. The elevator 232 is arranged adjacent to the first transfer position TP1, and is a mechanism for transferring the wafer W to the transfer robot 211 of the loading / unloading unit 21. When transferring the wafer W, the movable door (not shown) provided on the first partition wall 200A is opened and closed.

[0069] in addition, Figure 2 The specific structure of the first linear conveyor 230A and the second linear conveyor 230B, the swing conveyor 231, and the elevator 232 is omitted, but it is composed of, for example, an appropriate combination of AC equipment such as servo motors; driving force transmission mechanisms such as linear guides, ball screws, gears, belts, couplings, bearings, etc.; output equipment such as fluid pressure cylinders, valves, etc.; input equipment such as linear sensors, encoder sensors, limit sensors, torque sensors, etc.

[0070] (Processing unit)

[0071] like Figure 2As shown, the processing unit 24 includes: a first roller sponge cleaning section 24A and a second roller sponge cleaning section 24B arranged in two upper and lower sections as a substrate cleaning device using a roller sponge 2400; a first pen-shaped sponge cleaning section 24C and a second pen-shaped sponge cleaning section 24D arranged in two upper and lower sections as a substrate cleaning device using a pen-shaped sponge 2401; a first drying section 24E and a second drying section 24F arranged in two upper and lower sections as a substrate drying device for drying the cleaned wafer W; and a first conveying section 24G and a second conveying section 24H conveying the wafer W. In addition, the number and arrangement of the roller sponge cleaning sections 24A, 24B, the pen-shaped sponge cleaning sections 24C, 24D, the drying sections 24E, 24F, and the conveying sections 24G, 24H are not limited to Figure 2 The examples may also be changed appropriately.

[0072] The processing unit 24 includes the first roller sponge cleaning unit 24A and the second roller sponge cleaning unit 24B, the first conveying unit 24G, the first pen-shaped sponge cleaning unit 24C and the second pen-shaped sponge cleaning unit 24D, the second conveying unit 24H, and the first drying unit 24E and the second drying unit 24F, respectively, along the first linear conveyor 230A and the second linear conveyor 230B in a divided state. The processing unit 24 sequentially performs: a primary cleaning process by one of the first roller sponge cleaning unit 24A and the second roller sponge cleaning unit 24B; a secondary cleaning process by one of the first pen-shaped sponge cleaning unit 24C and the second pen-shaped sponge cleaning unit 24D; and a drying process by one of the first drying unit 24E and the second drying unit 24F on the wafer W after the polishing process. In addition, the processing order of each part 24A to 24H of the processing unit 24 may be appropriately changed, and a part of the processing may be omitted. For example, the cleaning process of the roller sponge cleaning parts 24A and 24B may be omitted, and the cleaning process of the pen sponge cleaning parts 24C and 24D may be started. In addition, the processing unit 24 may be equipped with a polishing cleaning part (not shown) instead of one of the roller sponge cleaning parts 24A and 24B and the pen sponge cleaning parts 24C and 24D to perform the polishing cleaning process, or the processing unit 24 may be equipped with a polishing cleaning part (not shown) in addition to one of the roller sponge cleaning parts 24A and 24B and the pen sponge cleaning parts 24C and 24D to perform the polishing cleaning process. In addition, each part 24A to 24H of the processing unit 24 of the present embodiment is placed horizontally to hold (horizontally hold) the wafer W, but the wafer W may be held vertically or tilted.

[0073] The roller sponge 2400 and the pen sponge 2401 are made of synthetic resin such as PVA and nylon and have a porous structure. The roller sponge 2400 and the pen sponge 2401 function as cleaning tools for friction cleaning of the wafer W and are replaceably mounted on the first roller sponge cleaning section 24A and the second roller sponge cleaning section 24B, and the first pen sponge cleaning section 24C and the second pen sponge cleaning section 24D.

[0074] The first transport unit 24G includes a first transport robot 246A that can move in the up-down direction. The first transport robot 246A is configured to be able to access the temporary table 233, the first roller sponge cleaning unit 24A and the second roller sponge cleaning unit 24B, and the first pen-shaped sponge cleaning unit 24C and the second pen-shaped sponge cleaning unit 24D of the substrate transport unit 23, and includes upper and lower arms for transferring wafers W therebetween. For example, the lower arm is used when transferring wafers W before cleaning, and the upper arm is used when transferring wafers W after cleaning. When transferring wafers W to the temporary table 233, a movable door (not shown) provided on the second partition wall 200B is opened and closed.

[0075] The second transfer unit 24H includes a second transfer robot 246B movable in the vertical direction. The second transfer robot 246B is configured to be able to access the first and second pen-shaped sponge cleaning units 24C and 24D, and the first and second drying units 24E and 24F, and includes an arm for transferring wafers W therebetween.

[0076] Figure 4 1 is a perspective view showing an example of the first roller sponge cleaning unit 24A and the second roller sponge cleaning unit 24B. The first roller sponge cleaning unit 24A and the second roller sponge cleaning unit 24B have the same basic structure and function. Figure 4 In the example of FIG. 1 , the first roll sponge cleaning unit 24A and the second roll sponge cleaning unit 24B include a pair of roll sponges 2400 disposed one above the other so as to sandwich the cleaned surface (front surface and back surface) of the wafer W.

[0077] The first roller sponge cleaning section 24A and the second roller sponge cleaning section 24B respectively include: a substrate holding section 241 for holding the chip W; a cleaning fluid supplying section 242 for supplying a cleaning fluid to the chip W; a substrate cleaning section (processing component supporting section) 240 for supporting the roller sponge 2400 so as to be rotatable and allowing the roller sponge 2400 to contact the chip W to clean the chip W; a cleaning tool cleaning section 243 for cleaning the roller sponge 2400 with a cleaning tool cleaning fluid (self-cleaning); and an environmental sensor 244 for measuring the internal space state of the frame 20 performing the cleaning process.

[0078] The substrate holding unit 241 includes a substrate holding mechanism 241 a for holding a plurality of side edge portions of the wafer W and a substrate rotating mechanism 241 b for rotating the wafer W around a third rotation axis perpendicular to the surface of the wafer W to be cleaned. Figure 4 In the example of , the substrate holding mechanism 241a is composed of four rollers, and at least one roller is movably configured to hold or release the side edge of the wafer W. In addition, Figure 4 In the example, the substrate rotating mechanism 241b is composed of two driving rollers, and the driving rollers also serve as the substrate holding mechanism 241a for holding the wafer W. In addition, the substrate holding section 241 may also be composed of: a substrate holding mechanism 241a composed of a plurality of rollers; and a substrate rotating mechanism 241b composed of at least one driving roller. In addition, the substrate holding mechanism 241a may also be composed of a chuck instead of a roller.

[0079] The cleaning fluid supply unit 242 includes: a cleaning fluid supply nozzle 242a for supplying cleaning fluid to the cleaned surface of the wafer W; a swing movement mechanism 242b for rotating the cleaning fluid supply nozzle 242a; a flow rate adjustment unit 242c for adjusting the flow rate and pressure of the cleaning fluid; and a temperature control mechanism 242d for adjusting the temperature of the cleaning fluid. The cleaning fluid may also be any one of pure water (rinsing liquid) or a chemical solution, such as Figure 4 As shown, the cleaning fluid supply nozzle 242a may be provided with a nozzle for pure water and a nozzle for liquid medicine. In addition, the cleaning fluid may be a liquid, a double fluid mixed with a liquid and a gas, or may contain a solid such as dry ice.

[0080] The substrate cleaning unit 240 includes: a cleaning tool rotating mechanism unit 240a that rotates the roller sponge 2400 around a first rotation axis parallel to the surface to be cleaned of the wafer W; a vertical movement mechanism unit 240b that moves at least one of the pair of roller sponges 2400 in the vertical direction in order to change the height of the pair of roller sponges 2400 and the distance between the two; and a linear movement mechanism unit 240c that moves the pair of roller sponges 2400 in a linear direction in the horizontal direction. The vertical movement mechanism unit 240b and the linear movement mechanism unit 240c function as a cleaning tool moving mechanism unit that moves the relative position of the roller sponge 2400 and the surface to be cleaned of the wafer W.

[0081] The cleaning tool cleaning part 243 is arranged at a position that does not interfere with the wafer W, and includes: a cleaning tool cleaning tank 243a that can store and discharge a cleaning tool cleaning fluid; a cleaning tool cleaning plate 243b that is received in the cleaning tool cleaning tank 243a and presses the roller sponge 2400; a flow regulating part 243c that regulates the flow rate and pressure of the cleaning tool cleaning fluid supplied to the cleaning tool cleaning tank 243a; and a flow regulating part 243d that regulates the flow rate and pressure of the cleaning tool cleaning fluid that flows inside the roller sponge 2400 and is discharged from the outer peripheral surface of the roller sponge 2400 to the outside. The cleaning tool cleaning fluid can also be any one of pure water (rinsing liquid) or a chemical solution.

[0082] The environmental sensor 244 includes, for example, a temperature sensor 244a, a humidity sensor 244b, an air pressure sensor 244c, an oxygen concentration sensor 244d, and a microphone (sound sensor) 244e. In addition, the environmental sensor 244 may also include a camera (image sensor) that can capture the surface, temperature distribution, airflow distribution, etc. of the wafer W and the roller sponge 2400 during or before and after the cleaning process. The camera's capture object is not limited to visible light, and may also be infrared light, ultraviolet light, etc.

[0083] In one cleaning process performed by the first roller sponge cleaning section 24A and the second roller sponge cleaning section 24B, the wafer W is rotated by the substrate rotating mechanism section 241b while being held by the substrate holding mechanism section 241a. Then, the roller sponge 2400 rotated about the axis by the cleaning tool rotating mechanism section 240a cleans the wafer W by sliding contact with the cleaned surface of the wafer W while the cleaning fluid is supplied from the cleaning fluid supply nozzle 242a. Then, the substrate cleaning section 240 moves the roller sponge 2400 to the cleaning tool cleaning tank 243a, for example, rotates the roller sponge 2400, or presses it on the cleaning tool cleaning plate 243b, and supplies the cleaning tool cleaning fluid to the roller sponge 2400 through the flow regulating section 243d to clean the roller sponge 2400.

[0084] Figure 5 1 is a perspective view showing an example of the first pen-shaped sponge cleaning unit 24C and the second pen-shaped sponge cleaning unit 24D. The first pen-shaped sponge cleaning unit 24C and the second pen-shaped sponge cleaning unit 24D have the same basic structure and function.

[0085] The first pen-type sponge cleaning unit 24C and the second pen-type sponge cleaning unit 24D are respectively provided with: a substrate holding unit 241 for holding a wafer W; a cleaning fluid supply unit 242 for supplying a cleaning fluid to the wafer W; a substrate cleaning unit (processing component supporting unit) 240 for supporting a pen-type sponge 2401 so as to be rotatable and making the pen-type sponge 2401 contact the wafer W to clean the wafer W; a cleaning tool cleaning unit 243 for cleaning (self-cleaning) the pen-type sponge 2401 with a cleaning tool cleaning fluid; and an environmental sensor 244 for measuring the internal space state of the rack 20 for performing cleaning processing. Hereinafter, the pen-type sponge cleaning units 24C and 24D will be mainly described as being different from the roller sponge cleaning units 24A and 24B.

[0086] The substrate holding unit 241 includes a substrate holding mechanism 241 c for holding a plurality of side edge portions of the wafer W and a substrate rotating mechanism 241 d for rotating the wafer W around a third rotation axis perpendicular to the surface of the wafer W to be cleaned. Figure 5 In the example of , the substrate holding mechanism 241c is composed of four rollers, and at least one roller is movably configured to hold or release the side edge of the wafer W. In addition, Figure 5 In the example, the substrate rotating mechanism 241d is composed of two driving rollers, and the driving roller constituting the substrate rotating mechanism 241b also serves as the substrate holding mechanism 241a for holding the wafer W. In addition, the substrate holding unit 241 may also be composed of: a substrate holding mechanism 241c composed of a plurality of rollers; and a substrate rotating mechanism 241d composed of at least one driving roller. In addition, the substrate holding mechanism 241c may also be composed of a chuck instead of a roller.

[0087] The cleaning fluid supply unit 242 and Figure 4 The device is similarly configured to include a cleaning fluid supply nozzle 242a, a swing movement mechanism 242b, a flow rate adjustment section 242c, and a temperature adjustment mechanism 242d.

[0088] The substrate cleaning unit 240 includes a cleaning tool rotating mechanism 240d for rotating the pen sponge 2401 around a second rotation axis perpendicular to the surface to be cleaned of the wafer W, a vertical movement mechanism 240e for moving the pen sponge 2401 in the vertical direction, and a swing movement mechanism 240f for rotating the pen sponge 2401 in the horizontal direction. The vertical movement mechanism 240e and the swing movement mechanism 240f function as a cleaning tool moving mechanism for moving the relative position of the pen sponge 2401 and the surface to be cleaned of the wafer W.

[0089] The cleaning tool cleaning section 243 is arranged at a position that does not interfere with the chip W, and comprises: a cleaning tool cleaning tank 243e that can store and discharge a cleaning tool cleaning fluid; a cleaning tool cleaning plate 243f that is accommodated in the cleaning tool cleaning tank 243e and presses the pen-shaped sponge 2401; a flow regulating section 243g that regulates the flow rate and pressure of the cleaning tool cleaning fluid supplied to the cleaning tool cleaning tank 243e; and a flow regulating section 243h that regulates the flow rate and pressure of the cleaning tool cleaning fluid that flows through the inner side of the pen-shaped sponge 2401 and is discharged from the outer surface of the pen-shaped sponge 2401 to the outside.

[0090] The environment sensor 244 includes, for example, a temperature sensor 244a, a humidity sensor 244b, an air pressure sensor 244c, an oxygen concentration sensor 244d, and a microphone (sound sensor) 244e. In addition, the environment sensor 244 may include a camera (image sensor) that can capture the surface temperature distribution and airflow distribution of the wafer W and the pen-shaped sponge 2401 during or before and after the cleaning process. The camera is not limited to visible light, and may also capture infrared light, ultraviolet light, and the like.

[0091] In the secondary cleaning process performed by the first pen-shaped sponge cleaning unit 24C and the second pen-shaped sponge cleaning unit 24D, the wafer W is rotated by the substrate rotating mechanism unit 241d while being held by the substrate holding mechanism unit 241c. Then, the pen-shaped sponge 2401 rotated about the axis by the cleaning tool rotating mechanism unit 240d cleans the wafer W by sliding contact with the cleaned surface of the wafer W while the cleaning fluid is supplied from the cleaning fluid supply nozzle 242a. Then, the substrate cleaning unit 240 moves the pen-shaped sponge 2401 to the cleaning tool cleaning tank 243e, for example, rotates the pen-shaped sponge 2401 or presses it on the cleaning tool cleaning plate 243f, and supplies the cleaning tool cleaning fluid to the pen-shaped sponge 2401 through the flow rate adjustment unit 243h to clean the pen-shaped sponge 2401.

[0092] Figure 6 24E and 24F are perspective views showing an example of the first drying section 24E and the second drying section 24F. The first drying section 24E and the second drying section 24F have the same basic configuration and function.

[0093] The first drying section 24E and the second drying section 24F each include a substrate holding section 241 for holding the wafer W, a drying fluid supply section 245 for supplying a drying fluid to the wafer W, and an environmental sensor 244 for measuring the internal space state of the rack 20 for performing the drying process.

[0094] The substrate holding part 241 includes: a substrate holding mechanism part 241e for holding multiple locations of the side edge of the wafer W; and a substrate rotating mechanism part 241g for rotating the wafer W around a third rotating axis perpendicular to the surface to be cleaned of the wafer W. One end of the substrate holding mechanism part 241e is arranged to rotate around a horizontal axis relative to the up-and-down moving mechanism part 241f that moves in the up-and-down direction, and the other end is composed of a chuck that can contact and separate from the peripheral edge of the wafer W. The substrate holding mechanism part 241e is composed of an umbrella mechanism in which the gripping part contacts or moves in a separation direction with respect to the wafer W as the up-and-down moving mechanism part 241f moves in the up-and-down direction. In addition, the substrate holding mechanism part 241e may be composed of a roller instead of a chuck.

[0095] The dry fluid supply unit 245 includes: a dry fluid supply nozzle 245a for supplying dry fluid to the cleaned surface of the chip W; an up-and-down moving mechanism unit 245b for moving the dry fluid supply nozzle 245a in the up-and-down direction; a rocking moving mechanism unit 245c for rotating the dry fluid supply nozzle 245a in the horizontal direction; a flow regulating unit 245d for regulating the flow rate and pressure of the dry fluid; and a temperature regulating mechanism unit 245e for regulating the temperature of the dry fluid. The up-and-down moving mechanism unit 245b and the rocking moving mechanism unit 245c function as a dry fluid supply nozzle moving mechanism unit for moving the relative position of the dry fluid supply nozzle 245a and the cleaned surface of the chip W. The dry fluid is, for example, IPA vapor and pure water (rinsing liquid), such as Figure 6 As shown, the drying fluid supply nozzle 245a may also be provided with a nozzle for IPA vapor and a nozzle for pure water. In addition, the drying fluid may be a liquid, a double fluid mixed with a liquid and a gas, or may contain a solid such as dry ice.

[0096] The environmental sensor 244 includes a temperature sensor 244a, a humidity sensor 244b, an air pressure sensor 244c, an oxygen concentration sensor 244d, and a microphone (sound sensor) 244e. In addition, the environmental sensor 244 may also include a camera (image sensor) that can capture the surface, temperature distribution, airflow distribution, etc. of the wafer W during or before and after the drying process.

[0097] In the drying process performed by the first drying section 24E and the second drying section 24F, the wafer W is rotated by the substrate rotating mechanism 241g while being held by the substrate holding mechanism 241e. Then, while the drying fluid is supplied from the drying fluid supply nozzle 245a to the cleaned surface of the wafer W, the drying fluid supply nozzle 245a moves to the side edge side (radially outward) of the wafer W. Then, the wafer W is rotated at a high speed by the substrate rotating mechanism 241g to dry the wafer W.

[0098] in addition, Figures 4 to 6The specific structure of the substrate holding mechanism 241a, 241c, 241e, the substrate rotating mechanism 241b, 241d, 241g, the up and down moving mechanism 240b, 240e, 241f, 245b, the linear moving mechanism 240c, the shaking moving mechanism 240f, 242b, 245c, and the cleaning tool rotating mechanism 240a, 240d is omitted, but it is composed of, for example, an appropriate combination of AC equipment such as servo motors; driving force transmission mechanisms such as linear guides, ball screws, gears, belts, couplings, bearings, etc.; output equipment such as fluid pressure cylinders and valves; and input equipment such as linear sensors, encoder sensors, limit sensors, torque sensors, etc. Figures 4 to 6 The specific structure of the flow regulating parts 243c, 243d, 243g, 243h, and 245d is omitted, but it is composed of an appropriate combination of output devices such as pumps, valves, and pressure reducing valves for regulating the fluid; and input devices such as flow sensors, pressure sensors, liquid level sensors, temperature sensors, fluid concentration sensors, fluid physical properties sensors, and fluid particle sensors. Figures 4 to 6 Although the specific structure of the temperature control mechanism parts 242d and 245e is omitted, it is composed of, for example, an appropriate combination of AC equipment such as a contact or non-contact heater; and input equipment such as a temperature sensor and a current sensor.

[0099] (Control Unit)

[0100] Figure 7 2 is a block diagram showing an example of the substrate processing apparatus 2. The control unit 25 is electrically connected to each unit 21 to 24 and functions as a control unit that controls each unit 21 to 24. The following description will be given by taking the control system (AC device, input device, output device, control device) of the polishing unit 22 and the processing unit 24 as an example, but since the basic configuration and function of the other units 21 and 23 are the same, the description will be omitted.

[0101] The grinding unit 22 is respectively configured on each subunit of the grinding unit 22 (for example, the grinding table 220, the top ring 221, the grinding fluid supply part 222, the dresser 223, the atomizer 224, etc.), and is equipped with: a plurality of AC devices 227 and output devices 228B that become control objects; a plurality of input devices 228A that detect the data (detection values) required to control each subunit; and a control device 229 that controls the AC device 227 and the output device 228B based on the detection values ​​of each input device 228A.

[0102] The input device 228A of the polishing unit 22 includes, for example: a sensor for detecting the rotation speed of the polishing table 220 (polishing pad 2200); a sensor for detecting the rotation torque of the polishing table 220 (polishing pad 2200); a sensor for detecting the surface temperature of the polishing pad 2200; a sensor for detecting the rotation speed of the rotation moving mechanism 221c (wafer W); a sensor for detecting the rotation torque of the rotation moving mechanism 221c (wafer W); a sensor for detecting the position coordinates of the substrate moving mechanism (up and down moving mechanism 221d, swing moving mechanism 221e) that can be converted to the position of the wafer W relative to the polishing pad 2200; a sensor for detecting the moving speed of the substrate moving mechanism; a sensor for detecting the moving torque of the substrate moving mechanism; a sensor for detecting the contact between the wafer W and the polishing pad 2 200; a sensor for detecting the pressure load of the chip W at 200; a sensor for detecting the pressure (positive pressure and negative pressure) of the chip pressing pressure chamber and the retaining ring pressing pressure chamber (both not shown in the figure); a sensor for detecting the flow rate of the pressure fluid supplied to the chip pressing pressure chamber and the retaining ring pressing pressure chamber; a sensor for detecting the flow rate of the polishing fluid supplied from the polishing fluid supply part 222; a sensor for detecting the temperature of the polishing fluid supplied from the polishing fluid supply part 222; a sensor for detecting the shaking position of the polishing fluid supply part 222 to which the polishing fluid supply part 222 can be changed to a dripping position of the polishing fluid; a sensor for detecting the concentration of the polishing fluid; a sensor for detecting the cleanliness of the polishing fluid (for example, the concentration of microparticles contained in the waste liquid of the polishing fluid, the particle diameter, and the number of particles per particle diameter); and an environmental sensor 225, etc.

[0103] The processing unit 24 includes: a plurality of AC devices 247 and output devices 248B which are respectively arranged in each subunit of the processing unit 24 (for example, the first roller sponge cleaning section 24A and the second roller sponge cleaning section 24B, the first pen-type sponge cleaning section 24C and the second pen-type sponge cleaning section 24D, the first drying section 24E and the second drying section 24F, the first conveying section 24G and the second conveying section 24H, etc.) and become the control objects; a plurality of input devices 248A for detecting data (detection values) required for controlling each subunit; and a control device 249 for controlling the operation of the AC device 247 and the output device 248B based on the detection values ​​of each input device 248A.

[0104] The input device 248A of the processing unit 24 includes, for example: a sensor for detecting the holding pressure when the substrate holding mechanism 241a, 241c, 241e holds the chip W; a sensor for detecting the rotation speed of the substrate rotating mechanism 241b, 241d, 241g (chip W); a sensor for detecting the rotation torque of the substrate rotating mechanism 241b, 241d, 241g (chip W); a sensor for detecting the flow rate of the cleaning fluid or the drying fluid; a sensor for detecting the pressure of the cleaning fluid or the drying fluid; a sensor for detecting the position coordinates of the cleaning fluid supply unit 242 or the drying fluid supply unit 245 which can be changed to the dripping position of the cleaning fluid; a sensor for detecting the temperature of the cleaning fluid or the drying fluid; a sensor for detecting the concentration of the cleaning fluid or the drying fluid; a sensor for detecting the fluid properties of the cleaning fluid or the drying fluid; a sensor for detecting the rotation of the cleaning tool (roller sponge 2400, pen sponge 2401) by the cleaning tool rotating mechanism 240a a sensor for detecting the rotational speed of the cleaning tool when the cleaning tool is in rotation; a sensor for detecting the rotational torque of the cleaning tool rotating mechanism 240a; a sensor for detecting the position coordinates of the cleaning tool moving mechanism (up and down moving mechanism 240b, 240e, linear moving mechanism 240c, and shaking moving mechanism 240f) that can be converted to the position of the cleaning tool relative to the chip W; a sensor for detecting the moving speed of the cleaning tool moving mechanism; a sensor for detecting the moving torque of the cleaning tool moving mechanism; a sensor for detecting the pressing load of the cleaning tool when the cleaning tool is brought into contact with the chip W or the cleaning plates 243b, 243f of the cleaning tool; a sensor for detecting the flow rate of the cleaning fluid of the cleaning tool; a sensor for detecting the pressure of the cleaning fluid of the cleaning tool; a sensor for detecting the cleanliness of the cleaning fluid of the cleaning tool (for example, the concentration of microparticles contained in the waste liquid of the cleaning tool cleaning tanks 243a, 243e, the particle diameter, and the number of particles per particle diameter); and an environmental sensor 244, etc.

[0105] The control unit 25 includes a control unit 250, a communication unit 251, an input unit 252, an output unit 253, and a storage unit 254. The control unit 25 is composed of, for example, a general-purpose or dedicated computer (see the following). Fig. 9 ) and constituted.

[0106] The communication unit 251 is connected to the network 7 and functions as a communication interface for sending and receiving various data. The input unit 252 receives various input operations, and the output unit 253 outputs various information via a display screen, a signal tower light, or a buzzer, and functions as a user interface.

[0107] The storage unit 254 stores various programs (operating system (OS), application programs, web browser, etc.) and data (device setting information 255, substrate processing plan information 256, etc.) used when the substrate processing device 2 operates. The device setting information 255 and the substrate processing plan information 256 are data that can be edited by the user via the display screen.

[0108] The control unit 250 obtains the detection values ​​of multiple input devices 218A, 228A, 238A, 248A (hereinafter referred to as the "input device group") through multiple control devices 219, 229, 239, 249 (hereinafter referred to as the "control device group"), and performs a series of substrate processing such as loading, grinding, cleaning, drying, and unloading by coordinating the actions of multiple AC devices 217, 227, 237, 247 (hereinafter referred to as the "AC device group"); and multiple output devices 218B, 228B, 238B, 248B (hereinafter referred to as the "output device group").

[0109] Figure 8 2 is a schematic diagram showing an example of a control panel 26. The control panel 26 is composed of a box-shaped frame 26a and a cover 26b that is partially detachable from the box. In addition, the substrate processing apparatus 2 may also include a plurality of control panels 26, for example, each unit 21 to 24 may include a control panel 26. The following mainly describes the control panel 26 for controlling the polishing unit 22.

[0110] The control panel 26 is configured with: an AC distribution board 260 connected to an AC power source AC; an AC equipment control circuit 261 connected to the AC distribution board 260; an AC / DC converter 262 connected to the AC distribution board 260 and converting the AC power supplied from the AC power source AC into DC power (DC 24V, etc.); a DC distribution board 263 connected to the AC / DC converter 262; a programmable logic controller (PLC) 264 connected to the DC distribution board 263; an AC terminal block 265 connected to the AC equipment control circuit 261; and an input terminal block 266 and an output terminal block 267 connected to the programmable logic controller 264.

[0111] The AC device control circuit 261 and the programmable logic controller 264 constitute a device for controlling a control device group (control devices 219, 229, 239, 249) of the AC device group (AC devices 217, 227, 237, 247). Figure 8 2 is a control device 229 of the grinding unit 22 for controlling the AC device 227 of the grinding unit 22 .

[0112] The AC device control circuit 261 includes: a motor drive circuit 261A that supplies AC current to the motors that operate as the AC devices 217, 227, 237, and 247; and a heater drive circuit 261B that supplies AC current to the heaters that operate as the AC devices 217, 227, 237, and 247. The motor is composed of any type of motor, such as a servo motor, an inverter motor, and a series motor. The motor drive circuit 261A is composed of, for example, a servo driver, an inverter, a relay, etc., and can also drive a plurality of motors. The heater drive circuit 261B is composed of, for example, an amplifier, a relay, etc., and can also drive a plurality of heaters.

[0113] In addition, as part of the wiring 27 for connecting the various devices, the control panel 26 includes: an AC power line 270 connecting the AC power source AC and the AC device group via the AC device control circuit 261, etc.; a DC power line 271 connecting the AC / DC converter 262 and the control device group; and a DC power line 272 connecting the control device group and the input device group via the input terminal block 266. Figure 8 The input signal line 272 represents the input device 228A of the grinding unit 22; the programmable logic controller 264 is connected to the output device group ( Figure 8 and a communication signal line 274 connecting the programmable logic controller 264 and the AC device control circuit 261.

[0114] The AC power line 270 in the control panel 26 includes: a primary-side motor power line 270A connected to the AC power source AC side relative to the motor drive circuit 261A; a secondary-side motor power line 270B connected to the motor side relative to the motor drive circuit 261A; a primary-side heater power line 270C connected to the AC power source AC side relative to the heater drive circuit 261B; and a secondary-side heater power line 270D connected to the heater side relative to the heater drive circuit 261B. A plurality of connectors (not shown) are mounted on the frame 26a of the control panel 26, and the wiring 27 is connected via the connectors. In addition, the arrangement and number of each device in the control panel 26 can also be appropriately changed, and the connection relationship and number of the wiring 27 can also be appropriately changed.

[0115] (Hardware Configuration of Each Device)

[0116] Fig. 9 1 is a diagram showing an example of a hardware configuration of a computer 900. The control unit 25, the database device 3, the machine learning device 4, the information processing device 5, and the user terminal device 6 of the substrate processing apparatus 2 are respectively configured by a general-purpose or dedicated computer 900.

[0117] Computer 900 Fig. 9 As shown, its main components include 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) unit 922, an external device I / F unit 924, an I / O (input and output) device I / F unit 926, and a media input and output unit 928. In addition, the above components may be omitted as appropriate depending on the purpose of using the computer 900.

[0118] The processor 912 is composed of one or more arithmetic processing devices (CPU (Central Processing Unit), MPU (Micro-processing unit), DSP (Digital Signal Processor), GPU (Graphics Processing Unit), etc.), and unifies the entire computer 900. The memory 914 stores various data and programs 930, and is composed of, for example, a volatile memory (DRAM, SRAM, etc.) that functions as a main memory, a non-volatile memory (ROM), a flash memory, etc.

[0119] The input device 916 is composed of, for example, a keyboard, a mouse, a numeric keypad, an electronic pen, etc., and plays the function of an input unit. The output device 917 is composed of, for example, a voice (sound) output device, a vibration device, etc., and plays the function of an output unit. The display device 918 is composed of, for example, a liquid crystal display, an organic EL display, electronic paper, a projector, etc., and plays the function of a display unit. The input device 916 and the display device 918, such as a touch panel display, can also be integrally constructed. The storage device 920 is composed of, for example, an HDD, an SSD (Solid State Drive), etc., and plays the function of a storage unit. The storage device 920 stores various data required for the execution of the operating system and the program 930.

[0120] The communication I / F unit 922 is connected to a network 940 such as the Internet or an enterprise network (or may be connected to a network 940 such as a wireless network) via a wired or wireless connection. Figure 1The I / F unit 926 is connected to an I / O device 960 such as various sensors and actuators, and functions as a communication unit for sending and receiving various signals and data such as sensor detection signals and control signals for actuators with the I / O device 960. The media input / output unit 928 is composed of a drive device such as a digital versatile optical drive (DVD drive) and a CD drive, and reads and writes data to a media (non-temporary storage medium) 970 such as a DVD and a CD.

[0121] In the computer 900 having the above-mentioned structure, the processor 912 calls the program 930 stored in the storage device 920 to the memory 914 for execution, and controls each part of the computer 900 via the bus 910. In addition, the program 930 may be stored in the memory 914 instead of the storage device 920. The program 930 may be recorded in the medium 970 in the form of an installable file or an executable file, and provided to the computer 900 via the media input and output unit 928. The program 930 may also be provided to the computer 900 by downloading through the network 940 via the communication I / F unit 922. In addition, the computer 900 may also realize various functions realized by the execution of the program 930 by the processor 912 with hardware such as FPGA (field programmable gate array) and ASIC (application specific integrated circuit).

[0122] The computer 900 is an electronic device of any type, such as a fixed computer or a portable computer. The computer 900 may be a client computer, a server computer, or a cloud computer. The computer 900 may also be applied to devices other than the devices 2 to 6 .

[0123] (Production history information 30)

[0124] Fig.103 is a data structure diagram showing an example of the production history information 30 managed by the database device 3. The production history information 30 is a table in which reports R acquired when substrate processing for the production are classified and registered, and includes, for example, a wafer history table 300 for each wafer W; a polishing history table 301 for polishing processing; a cleaning history table 302 for cleaning processing; and a drying history table 303 for drying processing. In addition to the above, the production history information 30 also includes an event history table for event information and an operation history table for operation information, but detailed descriptions are omitted.

[0125] In each record of the wafer history table 300, for example, the wafer ID, cassette number, slot number, substrate processing recipe information 256, start time, end time, and unit ID of each process are registered. Fig.10 The polishing process, cleaning process, and drying process are exemplified in the figure, but other processes can be registered in the same manner. The substrate processing solution information 256 can be registered in the same manner, and the reference object information of the substrate processing solution information 256 can be registered as the substrate processing solution information 256. The unit ID is used to identify the unique unit ID representing the unit used in each process, and the unit ID is associated with the unit type (for example, substrate transport, polishing, drum sponge cleaning, pen sponge cleaning, drying, etc.) representing the type of the unit.

[0126] In each record of the polishing history table 301, substrate status information indicating the state of the wafer W, processing component status information indicating the state of the processing component (polishing pad 2200), and processing fluid status information indicating the supply state of the processing fluid (polishing fluid) are respectively recorded. In each record of the cleaning history table 302, substrate status information indicating the state of the wafer W, processing component status information indicating the state of the processing component (roller sponge 2400 and pen sponge 2401), and processing fluid status information indicating the supply state of the processing fluid (cleaning fluid) are respectively recorded. In each record of the drying history table 303, substrate status information indicating the state of the wafer W and processing fluid status information indicating the supply state of the processing fluid (drying fluid) are respectively recorded.

[0127] The substrate status information is information indicating the status of the wafer W held by the substrate holding portion. The substrate status information may be, for example, a detection value of each input device sampled at a predetermined time interval by the input device group (or the AC device group and the output device group) possessed by the substrate holding portion (or a command value to each AC device group and each output device), or a setting value in the device setting information 255 or the substrate processing recipe information 256.

[0128] The processing component status information may be, for example, a detection value of each input device (or an AC device group and an output device group) sampled at a prescribed time interval by an input device group (or an AC device group and an output device group) possessed by a processing component support portion, or a setting value in the device setting information 255 or the substrate processing plan information 256.

[0129] The processing fluid status information may be, for example, the detection value of each input device (or the instruction value for each AC device group and each output device) sampled at a prescribed time interval by the input device group (or AC device group and output device group) possessed by the processing fluid supply unit, or it may be a set value in the device setting information 255 or the substrate processing plan information 256.

[0130] By referring to the polishing history table 301, the cleaning history table 302 and the drying history table 303, the processing contents when the substrate processing is performed on the wafer W specified by the wafer ID, and the states of the wafer W, the processing components and the processing fluid can be extracted. Specific contents of each information will be described later.

[0131] (Test information 31)

[0132] Fig.11 3 is a data structure diagram showing an example of test information 31 managed by the database device 3. The test information 31 includes: a grinding test table 310 in which execution conditions and execution results obtained when simulating a grinding process are classified and registered; a cleaning test table 311 in which execution conditions and execution results obtained when simulating a cleaning process are classified and registered; and a drying test table 312 in which execution conditions and execution results obtained when simulating a drying process are classified and registered.

[0133] In each record of the polishing test table 310, the cleaning test table 311, and the drying test table 312, for example, the test ID, the substrate processing plan information 256, the substrate state information, the processing component state information, the processing fluid state information, and the test result information are registered. The substrate processing plan information 256, the substrate state information, the processing component state information, and the processing fluid state information are information indicating the execution conditions of the simulation, and since the data structure thereof is the same as that of the polishing history table 301, the cleaning history table 302, and the drying history table 303, the detailed description thereof is omitted.

[0134] The test result information is information indicating the execution result of the simulation, and includes: current value information of the AC current supplied to the AC device via the AC power line 270 when the substrate is processed; and electromagnetic wave influence information indicating the influence of the electromagnetic wave generated from the AC power line 270 when the substrate is processed. The current value information is the current value recorded for each of the plurality of AC power lines 270, and the electromagnetic wave influence information is the influence of the electromagnetic wave recorded for each of the plurality of AC power lines 270. The current value information and the electromagnetic wave influence information included in the test result information may be acquired as time series data during a specific target period, or may be acquired as time point data at a specific target time point.

[0135] (Machine Learning Device 4)

[0136] Fig.12 2 is a block diagram showing an example of the machine learning device 4. The machine learning device 4 includes a control unit 40, a communication unit 41, a learning data storage unit 42, and a learned model storage unit 43.

[0137] 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 (e.g., substrate processing device 2, database device 3, information processing device 5, user terminal device 6, test device (not shown) etc.) via the network 7, and functions as a communication interface for sending and receiving various data.

[0138] The learning data acquisition unit 400 is connected to an external device via the communication unit 41 and the network 7 to acquire the first learning data 11A and the second learning data 11B. The learning data acquisition unit 400 acquires the first learning data 11A composed of substrate processing information as input data and current value information as output data, and acquires the second learning data 11B composed of current value information as input data and electromagnetic wave influence information as output data. The first learning data 11A and the second learning data 11B are data used as teacher data (training data), verification data, and test data in teacher learning. In addition, the electromagnetic wave influence information is data used as a correct answer label in teacher learning.

[0139] The learning data storage unit 42 is a database storing a plurality of sets of first learning data 11A and second learning data 11B acquired by the learning data acquisition unit 400. The specific configuration of the database constituting the learning data storage unit 42 may be appropriately designed.

[0140] The machine learning unit 401 performs machine learning using the plurality of sets of first learning data 11A and second learning data 11B stored in the learning data storage unit 42. That is, the machine learning unit 401 inputs the plurality of sets of first learning data 11A into the first learning model 10A, causing the first learning model 10A to learn the correlation between the substrate processing information and the current value information included in the first learning data 11A, thereby generating a learned first learning model 10A. In addition, the machine learning unit 401 inputs the plurality of sets of second learning data 11B into the second learning model 10B, causing the second learning model 10B to learn the correlation between the current value information and the electromagnetic wave influence information included in the second learning data 11B, thereby generating a learned second learning model 10B.

[0141] The learned model storage unit 43 is a database that stores the learned first learning model 10A and the second learning model 10B (specifically, the adjusted weighted parameter group) generated by the machine learning unit 401. The learned first learning model 10A and the second learning model 10B stored in the learned model storage unit 43 are provided to the real system (for example, the information processing device 5) via the network 7 and the recording medium. Fig.12 Although the learning data storage unit 42 and the learned model storage unit 43 are shown as separate storage units, they may be configured as a single storage unit.

[0142] In addition, the number of the first learning model 10A and the second learning model 10B stored in the learned model storage unit 43 is not limited to one, and multiple learning models with different conditions may be stored, for example, machine learning methods, differences in the structure of the substrate holding unit, differences in the structure of the processing component holding unit, types of data included in the substrate processing information, types of data included in the current value information, types of data included in the electromagnetic wave influence information, etc. In this case, multiple types of learning data having data corresponding to multiple learning models with different conditions may be stored in the learning data storage unit 42.

[0143] Fig.13 FIG. 1 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 information and current value information.

[0144] The substrate processing information constituting the first learning data 11A includes at least one of the following information: substrate processing scheme information 256 indicating the processing content of substrate processing (grinding processing, cleaning processing, drying processing, etc.); substrate status information indicating the state of the chip W; processing component status information indicating the state of the processing components (grinding pad 2200, roller sponge 2400 and pen-type sponge 2401); and processing fluid status information indicating the supply status of the processing fluid (grinding fluid, cleaning fluid and drying fluid).

[0145] The substrate processing recipe information 256 is information indicating the processing contents of the grinding process, the cleaning process, the drying process, etc. The processing contents of the grinding process include, for example, the table rotation speed of the grinding table 220, the top ring pressing time of the top ring 221, the wafer pressing load, the wafer rotation speed, the supply amount and supply timing of the grinding fluid of the grinding fluid supply unit 222, the dresser operation time of the dresser 223, the atomizer operation time of the atomizer 224, etc. The processing contents of the cleaning process include, for example, the roller sponge operation time, the roller sponge rotation speed, the wafer rotation speed, the supply amount and supply timing of the cleaning fluid in the roller sponge cleaning process, the pen sponge operation time, the pen sponge rotation speed, the wafer rotation speed, the supply amount and supply timing of the cleaning fluid in the pen sponge cleaning process, etc. The processing contents of the drying process include, for example, the drying operation time, the wafer rotation speed, the supply amount and supply timing of the drying fluid in the drying process, etc. In addition, the substrate processing recipe information 256 can be set for each wafer W, or can be set for a group of multiple wafers constituting a batch.

[0146] The substrate status information includes at least one of the size, thickness, and film type of the wafer W.

[0147] The processing component status information includes at least one of the condition of the polishing pad 2200, the condition of the roller sponge 2400, and the condition of the pen-shaped sponge 2401. The condition of the polishing pad 2200 is represented by, for example, surface properties, flatness, cleanliness, wetness, etc., and is set based on the use status of the polishing pad 2200 (use time, pressing load during use, presence or absence of dressing, presence or absence of replacement, image of the surface of the polishing pad 2200, rotation speed of the polishing pad 2200, rotation speed of the wafer W, number of processed sheets). The condition of the polishing pad 2200 may also change over time during the polishing process. The condition of the roller sponge 2400 and the pen-shaped sponge 2401 is represented by, for example, consumption and contamination, and is set based on the use status of the roller sponge 2400 and the pen-shaped sponge 2401 (use time, pressing load during use, presence or absence of replacement, image of the surface of the roller sponge 2400 and the pen-shaped sponge 2401, rotation speed of the roller sponge 2400 and the pen-shaped sponge 2401, rotation speed of the wafer W, number of processed sheets). The states of the roller sponge 2400 and the pen sponge 2401 may change over time during the cleaning process, for example.

[0148] The processing fluid state information includes at least one of the state of the polishing fluid, the state of the cleaning fluid, and the state of the drying fluid. The state of the polishing fluid, the cleaning fluid, and the drying fluid includes, for example, flow rate, dripping position, pressure, fluid properties (density, viscosity), etc.

[0149] The current value information constituting the first learning data 11A is information indicating the current value of the AC current flowing through the AC power line 270 in the control panel 26. When the AC power line 270 disposed in the control panel 26 includes at least one of the primary-side motor power line 270A, the secondary-side motor power line 270B, the primary-side heater power line 270C, and the secondary-side heater power line 270D, the current value information is information indicating the current value of the AC current flowing through the at least one AC power line 270. In this case, Fig.13 As shown, the current value information may be information indicating the current value for each of the plurality of AC power lines 270. In addition, the current value information may be information indicating the current value of the AC current flowing through the AC power line 270 disposed outside the control board 26.

[0150] The learning data acquisition unit 400 acquires the first learning data 11A by referring to the test information 31 and accepting an input operation from the user through the user terminal device 6 as necessary.

[0151] For example, the learning data acquisition unit 400 obtains the substrate processing scheme information 256, substrate status information, processing component status information, and processing fluid status information when performing a simulation specified by the test ID by referring to the test information 31, as the substrate processing information of the first learning data 11A. In addition, the substrate processing information can also be obtained as time series data during the entire substrate processing period, as time series data during an object period of a part of the substrate processing period, or as time point data at a specific object time point. When the definition of the substrate processing information is changed, it is only necessary to appropriately change the data structure of the input data in the first learning model 10A and the first learning data 11A.

[0152] Furthermore, the learning data acquisition unit 400 obtains the current value information in the test result information when performing the simulation specified by the same test ID by referring to the test information 31, as the current value information corresponding to the above-mentioned substrate processing information. In addition, the current value information can also be obtained as time series data of the entire substrate processing period or time series data of the object period of a part of the substrate processing period, or as time point data of a specific object time point. When the definition of the current value information is changed, it is only necessary to appropriately change the data structure of the output data in the first learning model 10A and the first learning data 11A.

[0153] The first learning model 10A adopts a neural network-like structure, and includes an input layer 100, an intermediate layer 101, and an output layer 102. Synapses (not shown) connecting neurons are laid between the layers, and each synapse has a corresponding weight. The weight parameter group composed of the weights of each synapse is adjusted by machine learning.

[0154] The input layer 100 has neurons corresponding to the number of substrate processing information as input data, and each value of the substrate processing information is input to each neuron. The output layer 102 has neurons corresponding to the number of current value information as output data, and the prediction result (inference result) of the current value information corresponding to the substrate processing information is output as output data.

[0155] Fig.14 1 is a diagram showing an example of the second learning model 10B and the second learning data 11B. The second learning model 10B and the second learning data 11B used for machine learning are composed of current value information and electromagnetic wave influence information.

[0156] The current value information constituting the second learning data 11B is information indicating the current value of the AC current flowing through the AC power line 270 in the control board 26 , and is similar to the current value information constituting the first learning data 11A, so detailed description is omitted.

[0157] The electromagnetic wave influence information constituting the second learning data 11B is information indicating the influence of electromagnetic waves generated from the AC power line 270 when the substrate is processed. For example, when the distance from the AC power line 270 is defined as the noise distance (LG1, LG2, ..., LGn), the electromagnetic wave influence information is defined as the noise level (NL1, NL2, ..., NLn) indicating the intensity of the influence of the electromagnetic waves relative to each noise distance (LG1, LG2, ..., LGn). In this case, Fig.14 As shown, the electromagnetic wave influence information may also indicate the influence of the electromagnetic wave on each of the plurality of AC power lines 270 .

[0158] The learning data acquisition unit 400 acquires the second learning data 11B by referring to the test information 31 and accepting an input operation from the user through the user terminal device 6 as necessary.

[0159] For example, the learning data acquisition unit 400 obtains the current value information in the test result information when performing the simulation specified by the test ID by referring to the test information 31, as the current value information of the second learning data 11B. In addition, the current value information can also be obtained as time series data during the entire substrate processing period, as time series data during a part of the substrate processing period, or as time point data at a specific object time point. When the definition of the current value information is changed, it is only necessary to appropriately change the data structure of the input data in the second learning model 10B and the second learning data 11B.

[0160] Furthermore, the learning data acquisition unit 400 obtains the electromagnetic wave influence information in the test result information when performing the simulation specified by the same test ID by referring to the test information 31, as the electromagnetic wave influence information corresponding to the above-mentioned current value information. In addition, the electromagnetic wave influence information can also be obtained as time series data during the entire substrate processing period or time series data during an object period of a part of the substrate processing period, or as time point data at a specific object time point. In the case of changing the definition of the electromagnetic wave influence information, it is only necessary to appropriately change the data structure of the output data in the second learning model 10B and the second learning data 11B.

[0161] The second learning model 10B adopts a neural network-like structure, for example, and is configured similarly to the first learning model 10A, so a detailed description thereof will be omitted.

[0162] (Machine Learning Methods)

[0163] Fig.151 is a flowchart showing an example of a machine learning method implemented by the machine learning device 4. The following description is about generating a learning model 10 using a plurality of sets of learning data 11, but is applicable to the case where a first learning model 10A and a second learning model 10B are generated using first learning data 11A and second learning data 11B, respectively.

[0164] First, in step S100, the learning data acquisition unit 400 acquires a desired amount of learning data 11 from the test information 31, etc., as a preliminary preparation for starting machine learning, and stores the acquired learning data 11 in the learning data storage unit 42. The amount of learning data 11 prepared here can be set in consideration of the inference accuracy required for the finally obtained learning model 10.

[0165] Next, in step S110, the machine learning unit 401 prepares a pre-learning learning model 10 to start machine learning. The pre-learning learning model 10 prepared here is composed of a neural network model, and the weight of each synapse is set to an initial value.

[0166] Next, in step S120 , the machine learning unit 401 acquires, for example, a set of learning data 11 at random from the plurality of sets of learning data 11 stored in the learning data storage unit 42 .

[0167] Next, in step S130, the machine learning unit 401 inputs the input data (substrate processing information or current value information) included in a set of learning data 11 into the input layer 100 of the learning model 10 prepared before learning (or during learning). As a result, output data (current value information or electromagnetic wave influence information) is output from the output layer 102 of the learning model 10 as an inference result, but the output data is generated by the learning model 10 before learning (or during learning). Therefore, in the state before learning (or during learning), the output data output as the inference result represents information different from the correct answer label (current value information or electromagnetic wave influence information) included in the learning data 11.

[0168] Next, in step S140, the machine learning unit 401 compares the answer label included in the set of learning data 11 acquired in step S120 with the output data output from the output layer as the inference result in step S130, and performs machine learning by performing a process of adjusting the weight of each synapse (backward propagation). Thus, the machine learning unit 401 causes the learning model 10 to learn the correlation between the input data and the output data.

[0169] Secondly, in step S150, the machine learning unit 401 determines whether the specified learning termination conditions are met based on, for example, the correct answer label contained in the learning data 11, the evaluation value of the error function of the output data output as the inference result; and the remaining number of unlearned learning data 11 stored in the learning data storage unit 42.

[0170] In step S150, if 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 performs the process of steps S120 to S140 multiple times for the learning model 10 being learned using the unlearned learning data 11. On the other hand, in step S150, if the machine learning unit 401 determines that the learning end condition is satisfied and ends the machine learning (Yes in step S150), the process proceeds to step S160.

[0171] Then, in step S160, the machine learning unit 401 stores the learned model 10 (adjusted weight parameter group) generated by adjusting the weights corresponding to each synapse in the learned model storage unit 43, and ends. Fig.15 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 learning model storage step.

[0172] As described above, when the machine learning device 4 and the machine learning method of this embodiment are used, it is possible to provide: a first learning model 10A that can predict (infer) the current value information of the AC current supplied to the AC device when the substrate is processed based on the substrate processing information; and a second learning model 10B that can predict (infer) electromagnetic wave influence information representing the influence of the electromagnetic waves generated from the AC power line 270 when the substrate is processed.

[0173] (Information processing device 5)

[0174] Fig.16 It is a block diagram showing an example of the information processing device 5 . Fig.17 1 is a functional explanatory diagram showing an example of the information processing device 5. The information processing device 5 includes a control unit 50, a communication unit 51, and a storage unit 52.

[0175] The control unit 50 performs the functions of the substrate processing substrate processing information acquisition unit 500, the current value information generation unit 501, the electromagnetic wave influence information generation unit 502 and the output processing unit 503. The communication unit 51 is connected to the external device (for example, the substrate processing device 2, the database device 3, the machine learning device 4, and the user terminal device 6) via the network 7, and performs the function of a communication interface for sending and receiving various data. The storage unit 52 stores various programs (operating system and user terminal program, etc.) and data (first learning model 10A and second learning model 10B) used when the information processing device 5 operates.

[0176] The substrate processing information acquisition unit 500 is connected to an external device via the communication unit 51 and the network 7. For example, by referring to the substrate processing plan information 256 of the substrate processing device 2 and the production history information 30 of the database device 3, the substrate processing information including the substrate processing plan information 256, substrate status information, processing component status information and processing fluid status information is acquired.

[0177] The current value information generating unit 501 generates current value information based on the substrate processing information acquired by the substrate processing information acquiring unit 500. In the present embodiment, the current value information generating unit 501 generates current value information corresponding to the substrate processing information by inputting the substrate processing information acquired by the substrate processing information acquiring unit 500 into the first learning model 10A that has learned the correlation between the substrate processing information and the current value information.

[0178] The electromagnetic wave influence information generating unit 502 generates the electromagnetic wave influence information based on the current value information generated by the current value information generating unit 501. In the present embodiment, the electromagnetic wave influence information generating unit 502 generates the electromagnetic wave influence information corresponding to the current value information by inputting the current value information generated by the current value information generating unit 501 into the second learning model 10B which has learned the correlation between the current value information and the electromagnetic wave influence information.

[0179] The storage unit 52 stores the first learning model 10A and the second learning model 10B that have been learned and used by the electromagnetic wave influence information generating unit 502. In addition, the number of the first learning model 10A and the second learning model 10B stored in the storage unit 52 is not limited to one. For example, the method of machine learning, the difference in the structure of the substrate holding unit, the difference in the structure of the processing component holding unit, the type of data included in the substrate processing information, the type of data included in the current value information, the type of data included in the electromagnetic wave influence information, etc., can also store multiple learned models with different conditions and selectively use them. The storage unit 52 can also be replaced by the storage unit of an external computer (for example, a server-type computer and a cloud-based computer). In this case, the current value information generating unit 501 and the electromagnetic wave influence information generating unit 502 only need to access the external computer.

[0180] The output processing unit 503 performs output processing for outputting the electromagnetic wave influence information generated by the electromagnetic wave influence information generating unit 502. For example, the output processing unit 503 may send the electromagnetic wave influence information to the user terminal device 6 to display a display screen based on the electromagnetic wave influence information on the user terminal device 6, or may send the electromagnetic wave influence information to the database device 3 to register the electromagnetic wave influence information in the production history information 30.

[0181] (User terminal device 6)

[0182] Fig.18 1 is a block diagram showing an example of the user terminal device 6. The user terminal device 6 includes a control unit 60, a communication unit 61, a storage unit 62, an input unit 63, an output unit 64, a sensor group 65, and a camera 66.

[0183] The control unit 60 performs the functions of the electromagnetic wave influence information acquisition unit 600, the spatial position information acquisition unit 601, and the object information generation unit 602. The communication unit 61 is connected to an external device (for example, a substrate processing device 2, a database device 3, a machine learning device 4, and an information processing device 5, etc.) via a network 7, and functions as a communication interface for sending and receiving various data. The storage unit 62 stores various programs (operating system and user terminal program, etc.) and data used when the user terminal device 6 operates. The input unit 63 accepts various input operations, and the output unit 64 outputs various information via a display screen and voice, thereby performing the function of a user interface. The sensor group 65 detects the position, acceleration, angular velocity, posture, etc. of its own device. The camera 66 takes still images and animations.

[0184] The electromagnetic wave influence information acquisition unit 600 is connected to an external device via the communication unit 61 and the network 7 , for example, sends a request to generate electromagnetic wave influence information to the information processing device 5 , and acquires the electromagnetic wave influence information from the information processing device 5 as a response.

[0185] The spatial position information acquisition unit 601 acquires spatial position information indicating the position of the AC power line 270 in the control panel 26 in the real space. For example, the spatial position information acquisition unit 601 monitors whether the feature point of the AC power line 270 is included in the shooting range when the camera 66 shoots the real space, and when the feature point including the AC power line 270 is detected, the spatial position information of the AC power line 270 is acquired based on the feature point. The feature point may be based on the outer shape and outer color of the AC power line 270, or may be based on the text printed on the AC power line 270. In addition, when the design drawing data of the control panel 26 is stored in the storage unit 62, the spatial position information acquisition unit 601 refers to the design drawing data, and when the feature point of the control panel 26 is detected in the design drawing data in the shooting range when the camera 66 shoots the real space, the spatial position information of the AC power line 270 may also be acquired based on the feature point.

[0186] The object information generation unit 602 generates object information for displaying a virtual object representing the influence of electromagnetic waves in an overlapping manner with respect to the AC power line 270 in the real space based on the spatial position information acquired by the spatial position information acquisition unit 601 and the electromagnetic wave influence information acquired by the electromagnetic wave influence information acquisition unit 600. In addition, the object information generation unit 602 may also generate object information for displaying the influence of real electromagnetic waves on a general display screen.

[0187] (Information Processing Method)

[0188] Fig.19 This is a flowchart showing an example of an information processing method implemented by the information processing device 5 and the user terminal device 6. The following describes an operation example in which, when the user removes the cover 26b from the frame 26a of the control panel 26 and checks the state inside the control panel 26, the user terminal device 6 is operated to display a virtual object indicating the influence of electromagnetic waves superimposed on the AC power line 270.

[0189] First, in step S200, when the user inputs the device ID of a specific substrate processing device 2 and the chip ID of a specific chip W in the display screen for the confirmation operation displayed on the user terminal device 6, and indicates the input operation to start the confirmation operation, the electromagnetic wave impact information acquisition unit 600 of the user terminal device 6 sends a request for generating electromagnetic wave impact information including the device ID and the chip ID to the information processing device 5.

[0190] Secondly, in step S210, when the substrate processing information acquisition unit 500 of the information processing device 5 receives the request for generating electromagnetic wave influence information sent in step S200, based on the device ID and chip ID contained in the request for generating electromagnetic wave influence information, by referring to the device setting information 255 of the substrate processing device 2 specified by the device ID and the production history information 30 specified by the chip ID, the substrate processing plan information 256, substrate status information, processing component status information and processing fluid status information are acquired as substrate processing information.

[0191] Next, in step S211 , the current value information generating unit 501 uses the substrate processing information acquired in step S210 as input data and generates current value information corresponding to the substrate processing information based on output data output by the first learning model 10A.

[0192] Next, in step S212 , the electromagnetic wave influence information generating unit 502 uses the current value information generated in step S211 as input data, and generates electromagnetic wave influence information corresponding to the current value information based on the output data output by the second learning model 10B.

[0193] Next, in step S213 , the output processing unit 503 sends the electromagnetic wave influence information to the user terminal device 6 as output processing for outputting the electromagnetic wave influence information generated in step S212 .

[0194] Then, in step S220 , the electromagnetic wave influence information acquisition unit 600 of the user terminal device 6 acquires (receives) the electromagnetic wave influence information transmitted in step S213 as a response to the request to generate the electromagnetic wave influence information in step S200 .

[0195] On the other hand, in step S230, the spatial position information acquisition unit 601 captures the real space through the camera 66 based on the input operation instructing the start of the confirmation operation, and monitors whether the captured range includes the feature points of the AC power line 270 in the control panel 26. At this time, the user who performs the confirmation operation updates the captured range of the real space captured by the camera 66 by changing his own position and the direction of the camera 66. At this time, the spatial position information acquisition unit 601 may monitor the feature points of each part of the control panel 26 in addition to the AC power line 270, or may refer to the design drawing data of the control panel 26.

[0196] Then, in step S231, the spatial position information acquisition unit 601 detects feature points including the AC power line 270 in the shooting range of the camera 66 in the real space, and acquires spatial position information indicating the position of the AC power line 270 in the real space based on the feature points.

[0197] Next, in step S240, the object information generation unit 602 generates object information for displaying a virtual object representing the influence of electromagnetic waves in an overlapping manner with respect to the AC power line 270 in the real space based on the spatial position information acquired in step S231 and the electromagnetic wave influence information acquired in step S220. Then, in step S241, the object information generation unit 602 displays the object display screen on the output unit 64 of the user terminal device 6 based on the generated object information.

[0198] Fig. 20 The figure shows an example of the object display screen 12 in which a virtual object is superimposed on the AC power line 270 in the real space. In the object display screen 12, a virtual object 120 representing the influence of electromagnetic waves is superimposed on the AC power line 270 in the real space captured by the camera 66.

[0199] exist Fig. 20 In the virtual object 120 shown, the influence of electromagnetic waves on the secondary-side motor power line 270B arranged at the uppermost side among the plurality of secondary-side motor power lines 270B connected to the motor drive circuit 261A is shown. Fig. 20 In the virtual object 120 shown, the noise levels (NL1, NL2, NL3) for the three stages of noise distances (LG1, LG2, LG3) are shown by three sub-objects 121 to 123. The three sub-objects 121 to 123 are represented by a cylindrical shape with the AC power line 270 of the object as the center, and the radius of the cylinder is made to correspond to the noise distance (LG1, LG2, LG3), and the light and dark colors of the cylinder ( Fig. 20 The darker the color, the stronger the noise level) corresponds to the noise level (NL1, NL2, NL3) to indicate the influence of electromagnetic waves (distance and intensity).

[0200] In addition, the object display screen 12 may also display various information about the AC power line 270 on which the virtual object 120 is superimposed. Fig. 20 As shown, when the secondary-end motor power line 270B of the virtual object 120 is overlapped and displayed as being connected to the motor of the rotating and moving mechanism part 220b that drives the grinding table 220 of the first grinding part 22A to rotate, the information about the grinding process in the substrate processing scheme information 256 included in the substrate processing information can also be displayed on the object display screen 12, and the information of the AC equipment 217, 227, 237, 247 (here, the motor of the rotating and moving mechanism part 220b) connected to the secondary-end motor power line 270B and the information of the control equipment 219, 229, 239, 249 (here, the control equipment 229 that controls the motor of the rotating and moving mechanism part 220b) can also be displayed.

[0201] In addition, for example, when the electromagnetic wave influence information is generated as a time series, the object display screen 12 may also change the virtual object 120 in a time series in accordance with the electromagnetic wave influence information. Furthermore, the object display screen 12 may also overlap and display the virtual object 120 on each of the plurality of AC power lines 270, or may be configured to accept an input operation of selecting an AC power line 270 on which to overlap and display the virtual object 120, and overlap and display the virtual object 120 on the selected AC power line 270.

[0202] The user can visually recognize the virtual object 120 displayed on the object display screen 12, and can grasp the influence of the electromagnetic wave generated from the AC power line 270. Then, according to the user changing the position of the user and the direction of the camera 66, the user terminal device 6 repeatedly performs the process of updating the object display screen 12. In addition, according to the change of the substrate processing information, the user terminal device 6 repeatedly performs the process of updating the object display screen 12. Therefore, since the user can immediately visually recognize the change of the influence of the electromagnetic wave with the change of the substrate processing information, the confirmation operation can be easily performed.

[0203] In the above information processing method, step S210 is equivalent to the substrate processing information acquisition process, step S211 is equivalent to the current value information generation process, step S212 is equivalent to the electromagnetic wave impact information generation process, steps S230 and S231 are equivalent to the spatial position information acquisition process, and step S240 is equivalent to the object information generation process.

[0204] As described above, when the information processing device 5 and the information processing method of the present embodiment are used, since the electromagnetic wave influence information of the AC power line 270 through which the AC current flows is generated based on the current value information of the AC current supplied to the AC devices 217, 227, 237, and 247 when the substrate processing is performed, it is possible to appropriately predict the influence of the electromagnetic wave generated from the AC power line 270 when the substrate processing is performed. At this time, since the current value information corresponding to the substrate processing information is generated based on the substrate processing information when the substrate processing is performed, it is possible to appropriately predict the influence of the electromagnetic wave generated from the AC power line 270 while reflecting the content of the substrate processing.

[0205] In addition, when the user terminal device 6 and the information processing method of the present embodiment are used, since the virtual object (AR display or MR display) representing the influence of electromagnetic waves is displayed overlapping with the AC power line 270 in the real space, it is possible to properly understand whether the influence of the electromagnetic waves caused by the AC power line 270 acts on other wiring 27 such as the DC power line 271, the input signal line 272, the output signal line 273, and the communication signal line 274.

[0206] (Other embodiments)

[0207] The present invention is not limited to the above-described embodiments, and can be implemented with various modifications within the scope of the present invention, all of which are included in the technical concept of the present invention.

[0208] In the above embodiment, it is described that the database device 3, the machine learning device 4, the information processing device 5 and the user terminal device 6 are respectively composed of different devices, however, these four devices may also be composed of a single device, or any two or three of the four devices may be composed of a single device. In addition, at least one of the machine learning device 4 and the information processing device 5 may also be embedded in the control unit 25 of the substrate processing device 2 or the user terminal device 6. For example, the first learning model 10A and the second learning model 10B may also be stored in the storage unit 62 of the user terminal device 6, and the control unit 60 further performs the functions of the substrate processing information acquisition unit 500, the current value information generation unit 501 and the electromagnetic wave influence information generation unit 502.

[0209] In the above embodiment, it is described that the substrate processing device 2 is equipped with each unit 21 to 24. However, the substrate processing device 2 only needs to be a device that performs at least one of a grinding process and a cleaning process as a substrate processing, and can also replace the chemical mechanical grinding process with a physical mechanical grinding process as a grinding process. That is, the substrate processing device 2 can also be a substrate grinding device that uses a grinding pad as a processing component and a grinding fluid as a processing fluid to perform a chemical mechanical grinding process or a physical mechanical grinding process as a substrate processing, and can also be a substrate cleaning device that uses a cleaning tool as a processing component and a cleaning fluid as a processing fluid to perform a cleaning process as a substrate processing. In this case, the substrate processing device can also appropriately omit the units that are not used in the grinding process and the cleaning process in each unit 21 to 24.

[0210] In the above-mentioned embodiment, the learning model for implementing the machine learning by the machine learning unit 401 is described as a case where a neural network is used, but other machine learning models may also be used. Other machine learning models include, for example, tree-type models such as decision trees and regression trees, integrated learning such as bagging and boosting, recurrent neural networks, stacked neural networks, neural network-like models such as LSTM (including deep learning), hierarchical clustering, non-hierarchical clustering, clustering types such as k-nearest neighbor method and k-means method, principal component analysis, factor analysis, multivariate analysis such as logistic regression, support vector machine, etc.

[0211] In the current value information generating unit 501 of the information processing device 5 of the above-mentioned embodiment, it is described that when the current value information is generated by the substrate processing information acquired by the substrate processing information acquiring unit 500, the first learning model 10A that has been learned is used, but other methods can also be used. Other methods can be, for example, simulation models and calculation formulas. That is, the current value information generating unit 501 can also generate the current value information when the substrate processing is performed in the state indicated by the substrate processing information by inputting the substrate processing information acquired by the substrate processing information acquiring unit 500 as input data into the simulation model or calculation formula.

[0212] In the electromagnetic wave influence information generating unit 502 of the information processing device 5 of the above-mentioned embodiment, the case where the learned second learning model 10B is used when generating the electromagnetic wave influence information based on the current value information generated by the current value information generating unit 501 is described, but other methods may also be used, and other methods may include, for example, simulation models and calculation formulas. That is, the electromagnetic wave influence information generating unit 502 may also generate the electromagnetic wave influence information when the alternating current indicated by the current value information is supplied to the alternating current device by inputting the current value information obtained by the current value information generating unit 501 as input data into the simulation model or calculation formula.

[0213] (Machine learning programs and information processing programs)

[0214] The present invention can also be provided in the form of a program (machine learning program) for causing the computer 900 to function as each unit of the machine learning device 4; and a program (machine learning program) for causing the computer 900 to execute each step of the machine learning method. In addition, the present invention can also be provided in the form of a program (information processing program) for causing the computer 900 to function as each unit of the information processing device 5 and the user terminal device 6; and a program (information processing program) for causing the computer 900 to execute each step of the information processing method of the above-mentioned embodiment.

[0215] Explanation of symbols

[0216] 1: Substrate processing system 2: Substrate processing device 3: Database device 4: Machine learning device 5: Information processing device 6: User terminal device 7: Network 10: Learning model 10A: First learning model 10B: Second learning model 11: Learning data 11A: First learning data 11B: Second learning data 12: Object display screen 21: Loading / unloading unit 22: Polishing unit 22A~22B: Polishing unit 23: Substrate conveying unit 24: Processing unit 24A, 24B: Roller sponge cleaning unit 24C, 24D: Pen sponge cleaning unit 24E, 24F: Drying unit 24G, 24H: Conveying unit 25: Control unit 26: Control panel 26a: Frame 26b: Cover 27: Wiring 30: Production history information 31: Test information 40: Control unit 41: Communication unit 42: Learning data storage unit 43: Learning completed model storage unit 50: Control unit 51: Communication unit 52: Storage unit (learning Completed model storage unit) 60: control unit 61: communication unit 62: storage unit 63: input unit 64: output unit 65: sensor group 66: camera 211: transfer robot 212: horizontal movement mechanism unit 217: communication device 218A: input device 218B: output device 219: control device 220: polishing table (processing component support unit) 221: top ring (substrate holding unit) 222: polishing fluid supply unit 223: dresser 224: atomizer 227: AC device 228A: input device 228B: output device 229: control device 230A, 230B: linear conveyor 231: swing conveyor 237: AC device 238A: input device 238B: output device 239: control device 240: substrate cleaning part (processing component support part) 241: substrate holding part 242: cleaning fluid supply part 243: cleaning tool cleaning part 245: drying fluid supply part 246A,246B: Second transfer robot 247: AC device 248A: Input device 248B: Output device 249: Control device 250: Control unit 251: Communication unit 252: Input unit 253: Output unit 254: Storage unit 255: Device setting information 256: Substrate processing plan information 260: AC distribution board 261: AC device control circuit 261A: Motor drive circuit 261B: Heater drive circuit 262: DC converter 263: DC distribution board 264: Programmable logic controller 265: AC terminal block 266: Input terminal block 267: Output terminal block 270: AC power line 270A: Primary end power line 27 0B: secondary end motor power line 270C: primary end heater power line 270D: secondary end heater power line 271: DC power line 272: input signal line 273: output signal line 274: communication signal line 400: learning data acquisition unit 401: machine learning unit 500: substrate processing information acquisition unit 501: current value information generation unit 502: electromagnetic wave influence information generation unit 503: output processing unit 600: electromagnetic wave influence information acquisition unit 601: spatial position information acquisition unit 602: object information generation unit 2200: polishing pad (processing component) 2400: roller sponge (processing component) 2401: pen-shaped sponge (processing component). 、

Claims

1. An information processing device, characterized in that: have: a current value information generating unit that generates current value information of an alternating current supplied to an alternating current device when a substrate is processed by a substrate processing apparatus, the substrate processing apparatus comprising the alternating current device and a control panel, the alternating current device being connected to an alternating current power source via an alternating current power line, the control panel controlling the alternating current device to perform the substrate processing, wherein a processing fluid is supplied to the substrate or the processing component while a processing component is brought into contact with the substrate during the substrate processing; and An electromagnetic wave influence information generating unit generates electromagnetic wave influence information indicating influence of electromagnetic waves generated from the AC power line based on the current value information generated by the current value information generating unit.

2. The information processing device according to claim 1, wherein: The electromagnetic wave influence information generating unit generates the electromagnetic wave influence information corresponding to the current value information by inputting the current value information generated by the current value information generating unit into a learning model, and the learning model machine learns the correlation between the current value information and the electromagnetic wave influence information.

3. The information processing device according to claim 1, wherein: further comprising a substrate processing information acquisition unit, the substrate processing information acquisition unit acquiring substrate processing information indicating a status of the substrate processing, The current value information generating unit generates the current value information based on the substrate processing information acquired by the substrate processing information acquiring unit, The substrate processing information includes at least one of the following information: Processing solution information indicating processing contents of the substrate processing; substrate status information indicating a status of the substrate; processing element status information indicating the status of the processing element; and Process fluid status information indicating a supply status of the process fluid.

4. The information processing device according to claim 3, wherein: The current value information generating unit generates the current value information corresponding to the substrate processing information by inputting the substrate processing information acquired by the substrate processing information acquiring unit into a learning model, and the learning model machine learns the correlation between the substrate processing information and the current value information.

5. The information processing device according to any one of claims 1 to 4, characterized in that: The current value information generating unit generates the current value information of the AC current flowing through the AC power line in the control panel, The electromagnetic wave influence information generating unit generates the electromagnetic wave influence information indicating the influence of the electromagnetic wave generated from the AC power line in the control panel, The AC power line in the control panel includes at least one of the following power lines: a primary-side motor power line connected to the AC power source side with respect to a motor drive circuit disposed in the control panel so as to supply the AC current to the motor operating as the AC device; a secondary-side motor power line connected to the motor side relative to the motor drive circuit; a primary-side heater power line connected to the AC power source side with respect to a heater drive circuit disposed in the control panel in such a manner as to supply the AC current to a heater operating as the AC device; and A secondary-side heater power line is connected to the heater side with respect to the heater drive circuit.

6. The information processing device according to claim 5, characterized in that Further possesses: a spatial position information acquisition unit that acquires spatial position information indicating a position in a real space where the AC power line in the control panel exists; and An object information generating unit generates object information for causing a virtual object representing the influence of the electromagnetic wave to be displayed overlapping the AC power line in the real space based on the spatial position information acquired by the spatial position information acquiring unit and the electromagnetic wave influence information generated by the electromagnetic wave influence information generating unit.

7. An information processing device, characterized in that: have: a spatial position information acquisition unit, the spatial position information acquisition unit acquiring spatial position information indicating a position where an AC power line in a control panel exists in a real space in a substrate processing device, the substrate processing device comprising an AC device and the control panel, the AC device being connected to an AC power source via the AC power line, the control panel controlling the AC device for substrate processing, in which a processing fluid is supplied to the substrate or the processing component while a processing component is brought into contact with the substrate; and An object information generating unit generates object information for causing a virtual object representing the influence of the electromagnetic wave to be displayed overlapping the AC power line in the real space based on the spatial position information acquired by the spatial position information acquiring unit and the electromagnetic wave influence information representing the influence of the electromagnetic wave generated from the AC power line.

8. A machine learning device, characterized in that: have: A learning data storage unit, the learning data storage unit storing a plurality of sets of learning data, the learning data consisting of current value information and electromagnetic wave influence information, the current value information being current value information of an alternating current supplied to an alternating current device when a substrate is processed by a substrate processing device, the substrate processing device comprising the alternating current device and a control panel, the alternating current device being connected to an alternating current power source via an alternating current power line, the control panel controlling the alternating current device in order to process the substrate, the electromagnetic wave influence information indicating the influence of electromagnetic waves generated from the alternating current power line when the substrate is processed, wherein a processing fluid is supplied to the substrate or the processing component while a processing component is brought into contact with the substrate during the substrate processing; a machine learning unit that inputs a plurality of sets of the learning data into a learning model so that the learning model learns the correlation between the current value information and the electromagnetic wave influence information; and A learned model storage unit stores the learned model in which the correlation is learned by the machine learning unit.

9. A machine learning device, characterized in that have: a learning data storage unit, the learning data storage unit storing a plurality of sets of learning data, the learning data consisting of substrate processing information and current value information, the substrate processing information indicating a state of substrate processing by a substrate processing device, the substrate processing device comprising an AC device and a control panel, the AC device being connected to an AC power source via an AC power line, the control panel controlling the AC device in order to perform the substrate processing, the current value information being current value information of an AC current supplied to the AC device when performing the substrate processing, wherein a processing fluid is supplied to the substrate or the processing component while a processing component is brought into contact with the substrate during the substrate processing; a machine learning unit that inputs a plurality of sets of the learning data into a learning model so that the learning model learns the correlation between the substrate processing information and the current value information; and A learned model storage unit stores the learned model in which the correlation is learned by the machine learning unit.

10. An information processing method, characterized in that: have: a current value information generating step of generating current value information of an AC current supplied to an AC device when a substrate is processed by a substrate processing apparatus, the substrate processing apparatus comprising the AC device and a control panel, the AC device being connected to an AC power source via an AC power line, the control panel controlling the AC device to perform the substrate processing, wherein a processing fluid is supplied to the substrate or the processing component while a processing component is brought into contact with the substrate during the substrate processing; and The electromagnetic wave influence information generating step generates electromagnetic wave influence information indicating the influence of the electromagnetic wave generated from the AC power line based on the current value information generated by the current value information generating step.

11. An information processing method, characterized in that: have: a spatial position information acquisition step of acquiring spatial position information indicating a position of an AC power line in a control panel in a real space in a substrate processing device, the substrate processing device comprising an AC device and the control panel, the AC device being connected to an AC power source via the AC power line, the control panel controlling the AC device for substrate processing, wherein a processing fluid is supplied to the substrate or the processing component while a processing component is brought into contact with the substrate during the substrate processing; and An object information generating step generates object information for causing a virtual object representing the influence of the electromagnetic wave to be displayed overlapping the AC power line in the real space based on the spatial position information acquired through the spatial position information acquiring step and the electromagnetic wave influence information representing the influence of the electromagnetic wave generated from the AC power line.

12. A machine learning method, characterized in that: have: a learning data storage step of storing a plurality of sets of learning data in a learning data storage unit, the learning data consisting of current value information and electromagnetic wave influence information, the current value information being current value information of an alternating current supplied to an alternating current device when a substrate is processed by a substrate processing device, the substrate processing device comprising the alternating current device and a control panel, the alternating current device being connected to an alternating current power source via an alternating current power line, the control panel controlling the alternating current device in order to process the substrate, the electromagnetic wave influence information indicating the influence of electromagnetic waves generated from the alternating current power line when the substrate is processed, wherein a processing fluid is supplied to the substrate or the processing component while a processing component is brought into contact with the substrate during the substrate processing; A machine learning step of inputting a plurality of sets of the learning data into a learning model so that the learning model learns the correlation between the current value information and the electromagnetic wave influence information; and The learned model storage step stores the learned model having learned the correlation in the machine learning step in a learned model storage unit.

13. A machine learning method, characterized in that: have: a learning data storage step of storing a plurality of sets of learning data in a learning data storage unit, the learning data consisting of substrate processing information and current value information, the substrate processing information indicating a state of substrate processing by a substrate processing device, the substrate processing device comprising an AC device and a control panel, the AC device being connected to an AC power source via an AC power line, the control panel controlling the AC device in order to perform the substrate processing, the current value information being current value information of an AC current supplied to the AC device when performing the substrate processing, wherein a processing fluid is supplied to the substrate or the processing component while a processing component is brought into contact with the substrate during the substrate processing; A machine learning step of inputting a plurality of sets of the learning data into a learning model so that the learning model learns the correlation between the substrate processing information and the current value information; and The learned model storage step stores the learned model having learned the correlation in the machine learning step in a learned model storage unit.

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