Method for inspecting laminate material, method for manufacturing laminate material, and system for inspecting laminate material

Abstract

To inspect a substrate or a plurality of layers included in a laminate material, or manufacture the laminate material on the basis of an inspection result.SOLUTION: A method for inspecting a laminate material of the present invention is a method for inspecting a laminate material manufactured through a plurality of processes of laminating a plurality of layers on a substrate, and the method includes, with the substrate for which one process of the plurality of processes is performed as an inspection target, a step of acquiring a surface image of the inspection target, and a step of inferring whether the cause of a specific abnormality occurs in the process by using at least the surface image.SELECTED DRAWING: Figure 12

Description

[Technical Field]

[0001] The present disclosure relates to a method for inspecting a laminate, a method for manufacturing a laminate, and an inspection system for a laminate. [Background technology]

[0002] Conventionally, laminated materials manufactured by stacking multiple layers including a superconducting layer have been known. For example, Japanese Patent Application Laid-Open Publication No. 2015-198015 (Patent Document 1) discloses an oxide superconducting thin film wire formed by stacking a metal substrate, a ceramic intermediate layer, an oxide superconducting layer, an Ag protective layer, and a Cu stabilization layer. The Cu stabilization layer is formed on the outer periphery of a laminate in which the metal substrate, the ceramic intermediate layer, the oxide superconducting layer, and the Ag protective layer are stacked in this order. This oxide superconducting thin film wire can prevent swelling and peeling of the resin coating. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2015-198015 Summary of the Invention [Problem to be solved by the invention]

[0004] Defects may occur on the surface of the substrate or one of the layers included in a laminate manufactured by laminating multiple layers onto a substrate. These defects may degrade the properties required for the laminate. Therefore, if these defects remain in the laminate, the percentage of the laminate that has the desired quality (yield) may decrease. However, Patent Document 1 does not consider the inspection of the substrate or multiple layers included in the laminate.

[0005] The purpose of the present disclosure is to solve the above-mentioned problems, and its purpose is to inspect a substrate or multiple layers included in a laminate, or to manufacture a laminate based on the inspection results. [Means for solving the problem]

[0006] The disclosed method for inspecting laminated materials is a method for inspecting laminated materials manufactured through multiple processes of stacking multiple layers onto a substrate, and includes the steps of: inspecting a substrate that has undergone one of the multiple processes, using an imaging device to acquire a surface image of the inspection object; and using a control device to use at least the surface image to infer whether a specific abnormality has occurred in the process.

[0007] The method for manufacturing a laminated material of the present disclosure includes a first manufacturing step of polishing a substrate, a second manufacturing step of forming an intermediate layer on the substrate after the first manufacturing step, a third manufacturing step of forming a superconducting layer on the intermediate layer after the second manufacturing step, a fourth manufacturing step of forming a protective layer on the superconducting layer after the third manufacturing step, a fifth manufacturing step of forming a stabilizing layer on the protective layer after the fourth manufacturing step, and an inspection step of inspecting the laminated material. The inspection step includes a step in which the substrate after at least one of the first manufacturing step, the second manufacturing step, the third manufacturing step, and the fourth manufacturing step is inspected, and includes a step in which an imaging device acquires a surface image of the inspection object, and a step in which a control device uses at least the surface image to infer whether a cause of a specific abnormality has occurred.

[0008] The laminated material inspection system disclosed herein is an inspection system that inspects laminated material manufactured through multiple processes of stacking multiple layers onto a substrate, and includes an imaging device that inspects a substrate that has undergone one of the multiple processes and captures a surface image of the inspection object, and an inference device that uses at least the surface image to infer whether a specific abnormality has occurred in the process. [Effects of the Invention]

[0009] The present disclosure allows for the inspection of a substrate or multiple layers included in a laminate, and also allows for the manufacturing of a laminate based on the inspection results. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a cross-sectional view of a superconducting wire 10. As shown in FIG. [Figure 2] FIG. 2 is a diagram showing an outline of a manufacturing process for superconducting wire 10 according to the first embodiment. [Figure 3] FIG. 3 is a diagram illustrating an example of a manufacturing system in step S11. [Figure 4] FIG. 4 is a diagram showing the configuration of the control device 100. As shown in FIG. [Figure 5] FIG. 5 is a diagram illustrating an example of a manufacturing system in step S12. [Figure 6] FIG. 6 is a diagram illustrating an example of a manufacturing system in step S13. [Figure 7] FIG. 7 is a diagram showing an example of a manufacturing system in step S14. [Figure 8] FIG. 8 is a diagram illustrating an example of a manufacturing system in step S15. [Figure 9] FIG. 9 is a diagram showing an example of an inspection system in steps S21, S22, S23, and S24. [Figure 10] FIG. 10 is a diagram showing an example of the trained model 144. [Figure 11] FIG. 11 is a diagram showing the input and output of the trained model 144(1) used in step S21 of the first embodiment. [Figure 12] FIG. 12 is a diagram showing the inspection method in step S21. [Figure 13] FIG. 13 is a diagram showing the input and output of the trained model 144(2) used in step S22 of the first embodiment. [Figure 14] FIG. 14 is a diagram showing the inspection method in step S22. [Figure 15] FIG. 15 is a diagram showing the input and output of the trained model 144(3) used in step S23 of the first embodiment. [Figure 16] FIG. 16 is a diagram showing the inspection method in step S23. [Figure 17] FIG. 17 is a diagram showing the input and output of the trained model 144(3) used in step S24 of the first embodiment. [Figure 18] FIG. 18 is a diagram showing the inspection method in step S24. [Figure 19] FIG. 19 is a diagram showing the first measure taken in step S31. [Figure 20] FIG. 20 is a diagram showing the second measure taken in step S32. [Figure 21] FIG. 21 is a diagram showing the third measure taken in step S33. [Figure 22] FIG. 22 is a diagram showing the fourth measure taken in step S34. [Figure 23] FIG. 23 is a diagram illustrating an outline of a manufacturing process for superconducting wire 10 according to the second embodiment. [Figure 24] FIG. 24 is a diagram showing the input and output of the trained model 144(0) used in step S20A of the second embodiment. [Figure 25] FIG. 25 is a diagram showing the input and output of the trained model 144(1) used in step S21A of the second embodiment. [Figure 26] FIG. 26 is a diagram showing the input and output of the trained model 144(2) used in step S22A of the second embodiment. [Figure 27] FIG. 27 is a diagram showing the input and output of the trained model 144(3) used in step S23A of the second embodiment. [Figure 28] FIG. 28 is a diagram showing the input and output of the trained model 144(4) used in step S24A of the second embodiment. [Figure 29] FIG. 29 is a diagram showing the input and output of the trained model 144(5) used in step S25A of the third embodiment. [Figure 30] FIG. 30 is a diagram showing the fifth measure taken in step S35. [Figure 31] FIG. 31 is a diagram showing defect locations based on a surface image and locations where the critical current of the laminate is reduced. [Figure 32] FIG. 32 is a diagram showing the rule base RB(1) used in step S21A of the third embodiment. [Figure 33] FIG. 33 is a diagram showing the rule base RB(2) used in step S22A of the third embodiment. [Figure 34] FIG. 34 is a diagram showing the rule base RB(3) used in step S23A of the third embodiment. [Figure 35] FIG. 35 is a diagram showing the rule base RB(4) used in step S24A of the third embodiment. [Figure 36] FIG. 36 is a diagram showing the rule base RB(5) used in step S25A of the third embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] [Description of the embodiments of the present disclosure] First, embodiments of the present disclosure will be listed and described.

[0012] (1) An inspection method for laminated materials according to one embodiment of the present disclosure is a method for inspecting laminated materials manufactured through multiple processes of stacking multiple layers onto a substrate, and includes the steps of: inspecting a substrate that has undergone one of the multiple processes, using an imaging device to acquire a surface image of the inspection object; and using at least the surface image, using a control device to infer whether a specific abnormality has occurred in the process.

[0013] According to the above method, it is possible to detect whether or not a cause of a specific abnormality has occurred using a surface image of a substrate after one of a plurality of processes.

[0014] (2) In the method for inspecting a laminated material described above in (1), the laminated material is manufactured by laminating a substrate, an intermediate layer, a superconducting layer, a protective layer, and a stabilizing layer in this order.

[0015] According to the above method, it is possible to use surface images of the substrate, intermediate layer, superconducting layer, protective layer, or stabilizing layer to detect whether a specific cause of abnormality has occurred in the manufacturing process thereof.

[0016] (3) In the laminate inspection method of (1) or (2) above, the inferring step includes a step in which the control device infers from the surface image of the substrate that has undergone the polishing process whether or not at least one of the following causes has occurred: insufficient drying of the polishing liquid, insufficient drying of the cleaning liquid, scratches on the rolling roll, and transfer of dirt from the rolling roll.

[0017] According to the above method, it is possible to detect whether or not the above-mentioned causes have occurred during the substrate polishing process, using the surface image of the substrate after polishing.

[0018] (4) In any one of the above-mentioned methods for inspecting laminated materials (1) to (3), the inferring step includes a step in which the control device infers, after the process of forming the intermediate layer on the substrate, whether or not a cause of abnormal discharge has occurred during the formation of the intermediate layer from a surface image of the intermediate layer and data on the manufacturing conditions of the intermediate layer.

[0019] According to the above method, it is possible to detect whether or not the above-mentioned causes have occurred during the intermediate layer deposition process by using a surface image of the intermediate layer after deposition and data on the manufacturing conditions of the intermediate layer.

[0020] (5) In the method for inspecting a laminated material according to any one of (1) to (4) above, the inferring step includes a step in which the control device infers, after the process of forming a superconducting layer on a substrate, whether or not a cause of a defect in the manufacturing conditions of the superconducting layer has occurred, from a surface image of the superconducting layer and data on the manufacturing conditions of the superconducting layer.

[0021] According to the above method, it is possible to detect whether or not the above-mentioned causes have occurred in the process of forming the superconducting layer by using a surface image of the superconducting layer after it has been formed and data on the manufacturing conditions of the superconducting layer.

[0022] (6) In any one of the above-mentioned methods for inspecting a laminated material (1) to (5), the inferring step includes a step in which the control device infers, after the process of forming the protective layer on the substrate, whether or not a cause of abnormal discharge has occurred during the formation of the protective layer from a surface image of the protective layer and data on the manufacturing conditions of the protective layer.

[0023] According to the above method, it is possible to detect whether or not the above-mentioned causes have occurred in the protective layer formation process by using a surface image of the protective layer after formation and data on the manufacturing conditions of the protective layer.

[0024] (7) In any one of the laminate inspection methods (1) to (6) above, the inferring step includes a step in which the control device infers whether or not there is a cause for foreign matter adhesion to the substrate from a surface image of the substrate before polishing.

[0025] According to the above method, it is possible to detect whether or not the above causes have occurred before polishing the substrate, using the surface image of the substrate before polishing.

[0026] (8) In any one of the laminate inspection methods (1) to (7) above, the inferring step includes a step in which the control device infers from a surface image of the substrate that has undergone the substrate polishing step whether or not there is a cause for insufficient polishing in the substrate polishing step.

[0027] According to the above method, it is possible to detect whether or not the above causes have occurred in the process of polishing the substrate, using an image of the surface of the substrate that has been polished.

[0028] (9) In any one of the above-mentioned laminate inspection methods (1) to (8), the inferring step includes a step in which the control device infers whether or not there is a cause of abnormal discharge during the intermediate layer deposition process from the surface image of the intermediate layer, the crystalline orientation of the intermediate layer, the surface temperature of the intermediate layer, the manufacturing temperature of the intermediate layer, the manufacturing humidity of the intermediate layer, and the set temperature during the intermediate layer deposition process, after the intermediate layer deposition process has been performed on the substrate.

[0029] According to the above method, it is possible to detect whether or not the above-mentioned causes have occurred during the process of forming an intermediate layer on a substrate using a surface image of the intermediate layer, the crystalline orientation of the intermediate layer, the surface temperature of the intermediate layer, the manufacturing temperature of the intermediate layer, the manufacturing humidity of the intermediate layer, and the set temperature during the process of forming the intermediate layer.

[0030] (10) In the method for inspecting a laminated material according to any one of (1) to (9) above, the inferring step includes a step in which the control device infers, after the step of forming a superconducting layer on the substrate, whether or not there is a cause of the defect, such as an abnormality in the concentration of oxygen gas, in the step of forming the superconducting layer, from a surface image of the superconducting layer, the crystalline orientation of the superconducting layer, the surface temperature of the superconducting layer, the manufacturing temperature of the superconducting layer, the manufacturing humidity of the superconducting layer, and the set temperature in the step of forming the superconducting layer.

[0031] According to the above method, it is possible to detect whether or not the above-mentioned causes have occurred in the process of forming a superconducting layer on a substrate by using a surface image of the superconducting layer, the crystal orientation of the superconducting layer, the surface temperature of the superconducting layer, the manufacturing temperature of the superconducting layer, the manufacturing humidity of the superconducting layer, and the set temperature in the process of forming the superconducting layer.

[0032] (11) In the method for inspecting a laminated material according to any one of (1) to (10) above, the inferring step includes a step in which the control device infers, after the step of forming the protective layer on the substrate, whether or not there is a cause of abnormal discharge or transport scratches in the step of forming the protective layer from a surface image of the protective layer, the surface temperature of the protective layer, and the magnitude of the critical current.

[0033] According to the above method, it is possible to detect whether or not the above-mentioned causes have occurred during the process of forming a protective layer on a substrate, using a surface image of the protective layer, the surface temperature of the protective layer, and the magnitude of the critical current.

[0034] (12) In any one of the above-mentioned laminate inspection methods (1) to (11), the inferring step includes a step in which the control device infers whether or not there is a cause of temperature abnormality in the process of forming the stabilization layer from the surface image of the stabilization layer, the manufacturing temperature of the stabilization layer, the set temperature in the process of forming the stabilization layer, and the magnitude of the critical current after the process of forming the stabilization layer on the substrate has been performed.

[0035] According to the above method, it is possible to detect whether or not the above-mentioned causes have occurred during the process of forming a stabilization layer on a substrate using a surface image of the stabilization layer, the manufacturing temperature of the stabilization layer, the set temperature during the process of forming the stabilization layer, and the magnitude of the critical current.

[0036] (13) In any one of the above-mentioned laminate inspection methods (1) to (12), the inferring step includes a step in which the control device infers that a specific cause of an abnormality has occurred in the process when the defect location based on the surface image coincides with the location where the decrease in critical current from the normal value is equal to or greater than a reference value.

[0037] According to the above method, it is possible to detect whether or not a specific cause of an abnormality has occurred in a process by using a surface image and a critical current.

[0038] (14) In the laminate inspection method according to (3) to (13) above, the inferring step includes a step of performing inference using a trained model.

[0039] According to the above method, it is possible to use a trained model to detect whether or not the cause of a specific abnormality has occurred using a surface image of a substrate after one of multiple processes.

[0040] (15) A method for manufacturing a laminate according to an embodiment of the present disclosure includes a first manufacturing step of polishing a substrate, a second manufacturing step of forming an intermediate layer on the substrate after the first manufacturing step, a third manufacturing step of forming a superconducting layer on the intermediate layer after the second manufacturing step, a fourth manufacturing step of forming a protective layer on the superconducting layer after the third manufacturing step, a fifth manufacturing step of forming a stabilizing layer on the protective layer after the fourth manufacturing step, and an inspection step of inspecting the laminate. The inspection step includes a step of inspecting the substrate after at least one of the first, second, third, and fourth manufacturing steps, using an imaging device to acquire a surface image of the inspection target, and a step of inferring whether a cause of a specific abnormality has occurred using at least the surface image.

[0041] According to the above method, a laminate can be manufactured while detecting whether or not a cause of a specific abnormality has occurred using a surface image of a substrate after one of the first to fourth processes.

[0042] (16) The manufacturing method of the laminated material of (15) above further comprises a step of implementing prescribed countermeasures when it is inferred that a specific cause of abnormality has occurred in the inspection step, and a step of repeating the processing from the first manufacturing step on a new substrate.

[0043] According to the above method, when it is inferred that a specific cause of an abnormality has occurred, a prescribed countermeasure is implemented and the processing is repeated from the first manufacturing process on a new substrate, thereby enabling the production of a defect-free laminate.

[0044] (17) In the manufacturing method of the laminated material described above in (16), the inspection process includes a first inspection process in which the substrate after the first manufacturing process is inspected, and the process of implementing countermeasures includes a first countermeasure process in which the drying method after cleaning the substrate is changed and the rolling roll is polished and cleaned.

[0045] According to the above method, if it is inferred that the cause of a specific abnormality has occurred in the first inspection process, in which the substrate after the first manufacturing process is inspected, the above first countermeasure is implemented and the processing from the first manufacturing process is carried out again on a new substrate, thereby making it possible to manufacture a laminate material without defects.

[0046] (18) In the manufacturing method of the laminated material described above in (16) or (17), the inspection process includes a second inspection process in which the substrate after the second manufacturing process is inspected is the target, and the process of taking countermeasures includes a second countermeasure process in which the log during the deposition of the intermediate layer is checked, and if there is an abnormality in the log, the manufacturing conditions are changed, and the target is polished and cleaned.

[0047] According to the above method, if it is inferred that the cause of a specific abnormality has occurred in the second inspection process, in which the substrate after the second manufacturing process is inspected, the second countermeasure described above is implemented and the processing from the first manufacturing process is carried out again on a new substrate, thereby making it possible to manufacture a defect-free laminate material.

[0048] (19) In the method for manufacturing a laminate material according to any one of (16) to (18) above, the inspection process includes a third inspection process in which the substrate after the third manufacturing process is inspected is subjected to the inspection, and the process for taking countermeasures includes a third countermeasure process in which the log at the time of forming the superconducting layer is checked and, if there is any abnormality in the log, the manufacturing conditions are changed.

[0049] According to the above method, if it is inferred that the cause of a specific abnormality has occurred in the third inspection process, in which the substrate after the third manufacturing process is inspected, the third countermeasure described above is implemented and the processing from the first manufacturing process is carried out again on a new substrate, thereby making it possible to manufacture a laminate material without defects.

[0050] (20) In any one of the laminate manufacturing methods (16) to (19) above, the inspection process includes a fourth inspection process in which the substrate after the fourth manufacturing process is inspected is the target, and the process of taking countermeasures includes a fourth countermeasure process in which the log at the time of forming the protective layer is checked, and if there is an abnormality in the log, the manufacturing conditions are changed, and the target is polished and cleaned.

[0051] According to the above method, if it is inferred that the cause of a specific abnormality has occurred in the fourth inspection process, in which the substrate after the fourth manufacturing process is inspected, the fourth countermeasure described above is implemented and the processing from the first manufacturing process is carried out again on a new substrate, thereby making it possible to manufacture a laminate material without defects.

[0052] (21) An inspection system for laminated materials according to one embodiment of the present disclosure is an inspection system for inspecting laminated materials manufactured through multiple processes of stacking multiple layers onto a substrate, and includes an imaging device that inspects a substrate that has undergone one of the multiple processes, and acquires a surface image of the inspection object, and an inference device that uses at least the surface image to infer whether a specific abnormality has occurred in the process.

[0053] According to the above configuration, it is possible to detect whether or not a cause of a specific abnormality has occurred by using a surface image of a substrate after one of a plurality of processes.

[0054] [Details of the embodiments of the present disclosure] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In the drawings, the same or corresponding parts are designated by the same reference numerals, and description thereof will not be repeated.

[0055] (First embodiment) The cross-sectional view of superconducting wire 10 shown in Fig. 1 is a plan view of a cut surface of superconducting wire 10 taken along line K1-K2 along the Y-axis direction, viewed from the X-axis direction. Note that in Fig. 1, the X-axis, Y-axis, and Z-axis are perpendicular to one another.

[0056] As shown in FIG. 1 , superconducting wire 10 extends in the X-axis direction (a specific direction). The Z-axis direction is the normal direction to the top surface of superconducting wire 10. Superconducting wire 10 includes substrate 11, intermediate layer 12, superconducting layer 13, protective layer 14, and stabilizing layer 15. Superconducting wire 10 is manufactured through multiple steps of laminating intermediate layer 12, superconducting layer 13, protective layer 14, and stabilizing layer 15 on substrate 11 in this order in the Z-axis direction. Superconducting wire 10 has a width W in the Y-axis direction. Superconducting wire 10 corresponds to a laminated material including substrate 11 and multiple layers. Superconducting wire 10 may be a relatively long superconducting wire having a length long enough to be wound up. Furthermore, the laminated material may be a relatively short superconducting wire or a chip-like device.

[0057] The substrate 11 is a clad material composed of, for example, a stainless steel tape, a copper layer disposed on the tape, and a nickel (Ni) layer disposed on the copper layer. The copper layer and the nickel layer are crystal-oriented. However, the substrate 11 is not limited to this structure and may be made of Hastelloy (registered trademark).

[0058] The intermediate layer 12 is disposed on the substrate 11. More specifically, the intermediate layer 12 is disposed on the nickel layer of the substrate 11. Although the intermediate layer 12 is shown as a single layer in FIG. 1, it may have a three-layer structure formed by sequentially stacking, for example, a layer of yttrium oxide (YO), a layer of stabilized zirconia (YSZ), and a layer of cerium oxide (CeO). As described above, the nickel layer of the substrate 11 is crystal-oriented, and therefore the intermediate layer 12 thereon is also crystal-oriented. The intermediate layer 12 is manufactured, for example, by magnetron sputtering. Note that when the substrate 11 is made of Hastelloy or the like, the crystal-oriented intermediate layer 12 is manufactured, for example, by IBAD (Ion Beam Assisted Deposition).

[0059] The superconducting layer 13 is disposed on the intermediate layer 12. The superconducting layer 13 is made of a copper oxide superconductor (REBCO:REBaCuOy) containing a rare earth element (RE). The rare earth element may be, for example, yttrium (Y), praseodymium (Pr), neodymium (Nd), samarium (Sm), europium (Eu), gadolinium (Gd), holmium (Ho), or ytterbium (Yb). The superconducting layer 13 may be manufactured by, for example, a metal organic decomposition (MOD) method or a pulsed laser deposition (PLD) method. As described above, the intermediate layer 12 is crystal-oriented, and therefore the superconducting layer 13 thereon is also crystal-oriented. More specifically, the c-axes of the REBCO crystal grains constituting the superconducting layer 13 are aligned along the normal direction to the top surface of the superconducting wire 10.

[0060] Protective layer 14 is disposed on the outer periphery of a laminate in which substrate 11, intermediate layer 12, and superconducting layer 13 are laminated in this order. Protective layer 14 is made of silver (Ag). Protective layer 14 may also be made of a silver alloy. Protective layer 14 may be manufactured by, for example, sputtering or plating. Note that FIG. 2 illustrates an example in which protective layer 14 is provided so as to cover the entire periphery of a laminate including substrate 11, intermediate layer 12, and superconducting layer 13. Protective layer 14 does not need to cover the entire periphery of the laminate, but it is sufficient that it is disposed at least on superconducting layer 13.

[0061] The stabilizing layer 15 is disposed on the outer periphery of the protective layer 14. The stabilizing layer 15 is made of copper. The stabilizing layer 15 may also be made of a copper alloy. The stabilizing layer 15 is manufactured by, for example, a plating method. The thickness of the stabilizing layer 15 is, for example, thicker than the thickness of the protective layer 14.

[0062] The number of intermediate layers included in superconducting wire 10 is not limited to one, but may be two or more (for example, three to five). The number of superconducting layers included in superconducting wire 10 is also not limited to one, but may be two or more.

[0063] An outline of the manufacturing process of superconducting wire 10 in the first embodiment will be described with reference to Fig. 2. For convenience of explanation, substrate 11 is also referred to as a laminate.

[0064] As shown in FIG. 2, in step S11, the surface of the substrate 11 (laminated body Lm1) is polished to produce a polished substrate 11 (laminated body Lm2).

[0065] In step S21, the inspection system inspects whether or not there is a cause of a specific abnormality in the substrate 11. If there is a specific abnormality, the process proceeds to step S31. If there is no specific abnormality, the process proceeds to step S12.

[0066] In step S31, a specific first measure is implemented, after which processing of a new substrate 11 starts from step S11.

[0067] Next, in step S12, the intermediate layer 12 is formed on the polished surface of the substrate 11 to produce a laminate Lm3.

[0068] In step S22, the inspection system inspects whether or not there is a specific abnormality in the intermediate layer 12. If there is a specific abnormality, the process proceeds to step S32. If there is no specific abnormality, the process proceeds to step S13.

[0069] In step S32, a specific second measure is implemented, after which the process for a new substrate 11 starts from step S11.

[0070] Next, in step S13, the superconducting layer 13 is formed on the intermediate layer 12 to produce the laminate Lm4.

[0071] In step S23, the inspection system inspects whether or not there is a cause of a specific abnormality in superconducting layer 13. If there is a specific abnormality, the process proceeds to step S33. If there is no specific abnormality, the process proceeds to step S14.

[0072] In step S33, a specific third measure is implemented, after which the process for a new substrate 11 starts from step S11.

[0073] Next, in step S14, a protective layer 14 is formed on the outer periphery of the laminate Lm4, thereby producing a laminate Lm5.

[0074] In step S24, the inspection system inspects whether or not there is a specific abnormality in the protective layer 14. If there is a specific abnormality, the process proceeds to step S34. If there is no specific abnormality, the process proceeds to step S15.

[0075] In step S34, a specific fourth measure is implemented, after which the process for a new substrate 11 starts from step S11.

[0076] Next, in step S15, stabilization layer 15 is formed on the outer periphery of laminate Lm5, thereby completing superconducting wire 10 (laminate Lm6). Note that step S15 does not necessarily have to be included in the manufacturing process of superconducting wire 10.

[0077] An example of the manufacturing system in step S11 will be described with reference to Fig. 3. As shown in Fig. 3, the manufacturing system includes a transport mechanism 310, a rolling roll 71, and a control device 100.

[0078] The configuration of the control device 100 will be described with reference to FIG.

[0079] The control device 100 includes a transport mechanism control unit 2, an imaging unit 6, a user input unit 4, a monitor 5, a storage 7, a learning device 8, an inference device 9, and a manufacturing condition setting device 3. The storage 7 stores learning data 143, a trained model 144, a surface image 145, and manufacturing condition data 146.

[0080] The transport mechanism 310 includes motors 311 and 312 and pulleys 321 and 322. Each of the motors 311 and 312 is rotated by a motor (not shown) around a rotation axis extending in the Y-axis direction. Each of the pulleys 321 and 322 rotates around a rotation axis extending in the Y-axis direction.

[0081] A laminate Lm1 (test object) is wound around the rotating shaft of the motor 311. An end of the laminate Lm1 is fixed to the rotating shaft of the motor 312. As the motors 311 and 312 rotate, the laminate Lm1 wound around the rotating shaft of the motor 311 passes through pulleys 321 and 322 in this order and is wound around the motor 312.

[0082] 4 controls the motors 311 and 312. The transport mechanism control unit 2 is controlled by a processor that executes a control program for controlling the motors 311 and 312, and a memory (neither of which is shown).

[0083] For example, the substrate 11 is polished by a mirror roll method. In the mirror roll method, after the substrate 11 is cleaned, the substrate 11 is rolled using a mill roll 71 whose roll surface has been mirror-finished, thereby transferring the mirror surface of the mill roll 71 to the surface of the substrate 11 and flattening the surface of the substrate 11.

[0084] The manufacturing condition setting device 3 in FIG. 4 refers to the manufacturing condition data 146 and controls the reduction rolls 71 and the like.

[0085] An example of the manufacturing system in step S12 will be described with reference to Fig. 5. As shown in Fig. 5, the manufacturing system includes a transfer mechanism 310, a chamber 21, a target 22, a cathode 23, a bias power supply 24, and a control device 100.

[0086] A target 22 and a cathode 23 are provided on the side of the chamber 21. The cathode 23 is connected to a bias power supply 24. The target 22 contains a material that constitutes the intermediate layer 12. The bias power supply 24 is configured to apply a bias voltage Vb2 to the cathode 23, thereby generating plasma in a space near the target 22 and sputtering constituent particles of the target 22.

[0087] The manufacturing condition setting device 3 in FIG. 4 refers to the manufacturing condition data 146 to control the target 22, the bias voltage Vb2, and the like.

[0088] An example of the manufacturing system in step S13 will be described with reference to Fig. 6. As shown in Fig. 6, the manufacturing system includes a transfer mechanism 310, a chamber 31, a target 32, a target holder 33 that holds the target 32, an exhaust unit 35, a laser light source 34, a heating device 36, and a control device 100.

[0089] The heating device 36 heats the laminate Lm3 to a desired temperature. The target 32 ​​contains a material that constitutes the superconducting layer 13. After the exhaust unit 35 exhausts the gas inside the chamber 31 to reduce the pressure in the chamber 31 to a desired pressure, the laser light source 34 irradiates the target 32 ​​with a pulsed laser beam. When the surface of the target 32 ​​is irradiated with a focused pulsed laser beam, constituent particles on the surface of the target 32 ​​are knocked out or evaporated, generating a jet of constituent particles from the target 32, and the desired particles can be deposited on the laminate Lm3.

[0090] The manufacturing condition setting device 3 in FIG. 4 refers to the manufacturing condition data 146 to control the target 22, the laser light source 34, the heating device 36, and the like.

[0091] An example of the manufacturing system in step S14 will be described with reference to Fig. 7. As shown in Fig. 7, the manufacturing system includes a transfer mechanism 310, a chamber 41, a target 42, and a control device 100.

[0092] A target 42 and a cathode 43 are provided on the side of the chamber 41. The cathode 43 is connected to a bias power supply 44. The target 42 contains a material that constitutes the protective layer 14. The bias power supply 44 is configured to apply a bias voltage Vb4 to the cathode 43, thereby generating plasma in a space near the target 42 and sputtering constituent particles of the target 42.

[0093] The manufacturing condition setting device 3 refers to the manufacturing condition data 146 to control the target 42, the bias voltage Vb4, and the like.

[0094] An example of the manufacturing system in step S15 will be described with reference to Fig. 8. As shown in Fig. 8, the manufacturing system includes a transfer mechanism 310, a chamber 51, a target 52, and a control device 100.

[0095] A target 52 and a cathode 53 are provided on the side of the chamber 51. The cathode 53 is connected to a bias power supply 54. The target 52 contains a material that constitutes the stabilization layer 15. The bias power supply 54 is configured to apply a bias voltage Vb5 to the cathode 53, thereby generating plasma in a space near the target 52 and sputtering constituent particles of the target 52.

[0096] The manufacturing condition setting device 3 refers to the manufacturing condition data 146 to control the target 52, the bias voltage Vb5, and the like.

[0097] An example of an inspection system in steps S21, S22, S23, and S24 will be described with reference to Fig. 9. As shown in Fig. 9, the inspection system includes a conveying mechanism 310, a camera 121 (imaging device), an illumination device 122, and a control device 100.

[0098] The lighting device 122 illuminates an imaging position Pim located between the pulleys 321 and 322. The camera 121 captures an image of visible light reflected from the surface of the stack Lm, which is moving in the X-axis direction, at the imaging position Pim.

[0099] The image captured by the camera 121 may be a color image or a grayscale image. By moving the stack Lm in the X-axis direction by the motor 311, multiple surface images at different positions on the stack Lm can be automatically and continuously captured.

[0100] 4 controls the camera 121 and the lighting device 122. The imaging unit 6 includes a processor that executes a control program for controlling the camera 121 and the lighting device 122, and a memory (neither of which is shown).

[0101] The monitor 5 displays a GUI for receiving user operations and settings for the inspection system, and displays the inference results.

[0102] The user input unit 4 accepts input from an operator who is a user.

[0103] The storage 7 is a non-volatile storage device, and includes, for example, a solid state drive (SSD) and / or a hard disk drive (HDD).

[0104] The manufacturing condition data 146 includes manufacturing condition data for polishing the substrate 11 in step S11, manufacturing condition data for forming the intermediate layer 12 in step S12, manufacturing condition data for forming the superconducting layer 13 in step S13, manufacturing condition data for forming the protective layer 14 in step S14, and manufacturing condition data for forming the stabilizing layer 15 in step S15.

[0105] The learning device 8 uses the learning data 143 to create a trained model 144. The learning device 8 includes a processor that executes a learning program and a memory.

[0106] In steps S21, S22, S23, and S24, the inference device 9 performs inference on whether or not a cause of a specific abnormality exists from the input data using the trained model 144. The inference device 9 includes a processor and a memory that executes an inference program.

[0107] An example of the trained model 144 will be described with reference to FIG.

[0108] The trained model 144 is configured, for example, by a neural network. Predetermined data is input to the neural network, and the neural network outputs the presence or absence of the cause of a specific abnormality. The trained model may be generated by deep learning.

[0109] The trained model 144(1) used in step S21 will be described with reference to Figure 11. In step S21, the inference device 9 uses the trained model 144(1) to infer, from the surface image data of the substrate 11, whether or not there is at least one cause among insufficient drying of the polishing liquid, insufficient drying of the cleaning liquid, scratches on the rolling roll 71, and transfer of dirt from the rolling roll 71.

[0110] The inspection method in step S21 will be described with reference to FIG.

[0111] In step S201, the inference device 9 acquires data of the surface image of the substrate 11.

[0112] In step S202, the inference device 9 uses the trained model 144(1) to infer, from the surface image data of the substrate 11 acquired in step S201, whether or not there is at least one cause among insufficient drying of the polishing liquid, insufficient drying of the cleaning liquid, scratches on the rolling roll 71, and transfer of dirt from the rolling roll 71.

[0113] The trained model 144(2) used in step S22 will be described with reference to Figure 13. In step S22, the inference device 9 uses the trained model 144(2) to infer whether or not there is a cause of abnormal discharge during the manufacturing (deposition) of the intermediate layer 12 from the data of the surface image of the intermediate layer 12 and the data of the manufacturing conditions of the intermediate layer 12.

[0114] The manufacturing condition data includes the bias voltage Vb2 applied to the target 22, the gas pressure in the chamber 21, and the temperature in the chamber 21. The input data may further include data of a surface image of the substrate 11.

[0115] The inspection method in step S22 will be described with reference to FIG.

[0116] In step S301, the inference device 9 acquires data on the surface image of the intermediate layer 12 and data on the manufacturing conditions of the intermediate layer 12.

[0117] In step S302, the inference device 9 uses the learned model 144(2) to infer whether or not there is a cause for abnormal discharge during the manufacturing (deposition) of the intermediate layer 12 from the data on the surface image of the intermediate layer 12 acquired in step S301 and the data on the manufacturing conditions of the intermediate layer 12.

[0118] The trained model 144(3) used in step S23 will be described with reference to Figure 15. In step S23, inference device 9 uses trained model 144(3) to infer whether or not there is a cause for poor manufacturing conditions during the manufacturing (deposition) of superconducting layer 13, from data on the surface image of superconducting layer 13 and data on the manufacturing conditions of superconducting layer 13.

[0119] The manufacturing condition data includes the heating temperature by the heating device 36, the partial pressure of various gases in the chamber 31, the humidity in the chamber 31, the amount of material applied to the target 32, the input energy of the laser light source 34, the laser power and frequency of the laser light source 34, etc.

[0120] The inspection method in step S23 will be described with reference to FIG.

[0121] In step S401, inference device 9 acquires data on the surface image of superconducting layer 13 and data on the manufacturing conditions of superconducting layer 13.

[0122] In step S402, the inference device 9 uses the trained model 144(3) to infer whether or not there is a cause for poor manufacturing conditions during the manufacturing (deposition) of the superconducting layer 13 from the data on the surface image of the superconducting layer 13 acquired in step S401 and the data on the manufacturing conditions of the superconducting layer 13.

[0123] The trained model 144(4) used in step S24 will be described with reference to Figure 17. In step S24, the inference device 9 uses the trained model 144(4) to infer whether or not there is a cause for poor manufacturing conditions during the manufacturing (deposition) of the protective layer from the data of the surface image of the protective layer 14 and the data of the manufacturing conditions of the protective layer 14.

[0124] The manufacturing conditions include the bias voltage Vb4 applied to the target 42, the pressure and temperature of the gas in the chamber 41, and the like.

[0125] The inspection method in step S24 will be described with reference to FIG.

[0126] In step S501, the inference device 9 acquires data on the surface image of the protective layer 14 and data on the manufacturing conditions of the protective layer 14.

[0127] In step S502, the inference device 9 uses the trained model 144(4) to infer whether or not there is a cause for poor manufacturing conditions during the manufacturing (deposition) of the protective layer 14 from the data on the surface image of the protective layer 14 acquired in step S501 and the data on the manufacturing conditions of the protective layer 14.

[0128] The first measure taken in step S31 will be described with reference to FIG.

[0129] The first measure involves changing the method of drying the substrate 11 after cleaning, and polishing and cleaning the rolling roll 71.

[0130] The second measure taken in step S32 will be described with reference to FIG.

[0131] The second measure involves checking the data on the manufacturing conditions during the manufacturing (deposition) of the intermediate layer 12, changing the manufacturing conditions if there is any abnormality in the manufacturing conditions, and polishing and cleaning the target 22.

[0132] The third measure implemented in step S33 will be described with reference to FIG.

[0133] The third measure involves checking the data on the manufacturing conditions during the manufacturing (deposition) of superconducting layer 13, and changing the manufacturing conditions if any abnormality is found in the manufacturing conditions.

[0134] The fourth measure implemented in step S34 will be described with reference to FIG.

[0135] The fourth measure involves checking the data on the manufacturing conditions during the manufacturing (deposition) of the protective layer 14, changing the manufacturing conditions if there is any abnormality in the manufacturing conditions, and polishing and cleaning the target 42.

[0136] (Second embodiment) An outline of the manufacturing process of superconducting wire 10 in the second embodiment will be described with reference to Fig. 23. The flowchart in Fig. 23 differs from the flowchart in Fig. 2 in that the flowchart in Fig. 23 includes step S20A before step S11, step S25A after step S15, and steps S21A, S22A, S23A, and S24A instead of steps S21, S22, S23, and S24.

[0137] In step S20A, the inspection system inspects the substrate 11 for specific anomaly causes before polishing. If specific anomalies are present, processing begins again with step S20A for a new substrate 11.

[0138] In step S25A, the inspection system inspects whether the stabilization layer 15 is the cause of the specific anomaly. If the specific anomaly is present, the process proceeds to step S35. If the specific anomaly is not present, the process ends.

[0139] In step S35, a specific fifth measure is implemented, after which processing for a new substrate 11 begins from step S20A.

[0140] The trained model used in steps S21A, S22A, S23A, and S24A is different from the trained model used in steps S21, S22, S23, and S24.

[0141] The trained model 144(0) used in step S20A will be described with reference to Figure 24. In step S20A, the inference device 9 uses the trained model 144(0) to infer whether or not there is a cause for the abnormality of foreign matter adhesion on the substrate 11 from the data of the surface image of the substrate 11 before polishing.

[0142] A surface image of the substrate 11 before polishing can be acquired by the camera 121. If the surface image is normal, it will be a uniform image, but if it is abnormal, it will be dotted or linear. Abnormal foreign matter adhesion can be caused by insufficient water flow during the substrate cleaning process, insufficient cleaning of the cleaning tank, or foreign matter getting into the cleaning tank.

[0143] The trained model 144(1) used in step S21A will be described with reference to Figure 25. In step S21A, the inference device 9 uses the trained model 144(1) to infer, from the data of the surface image of the substrate 11 after polishing, whether or not there is a cause for insufficient polishing in the polishing process of the substrate 11.

[0144] The surface image of the substrate 11 after polishing can be acquired by the camera 121.

[0145] Referring to FIG. 26, the trained model 144(2) used in step S22A will be described. In step S22A, the inference device 9 uses the trained model 144(2) to determine whether there is a cause of abnormal discharge in the film formation process of the intermediate layer 12 from the data of the surface image of the intermediate layer 12, the crystal orientation of the intermediate layer 12, the surface temperature of the intermediate layer 12, the manufacturing temperature of the intermediate layer 12, the manufacturing humidity of the intermediate layer 12, and the set temperature of the film formation process of the intermediate layer 12.

[0146] The surface image of the intermediate layer 12 can be acquired by the camera 121. The crystal orientation of the intermediate layer 12 can be detected by the reflection high-energy electron diffraction (RHEED) method or the X-ray diffraction method. The surface temperature of the intermediate layer 12 can be detected by contacting a thermometer with the surface of the intermediate layer 12 in the chamber 21 of FIG. 5. The manufacturing temperature of the intermediate layer 12 can be measured by a thermometer in the chamber 21 of FIG. 5. The manufacturing humidity of the intermediate layer 12 can be measured by a hygrometer in the chamber 21 of FIG. 5. The set temperature of the film formation process of the intermediate layer 12 can be the one included in the manufacturing condition data 146 of FIG. 4.

[0147] For the crystal orientation, in the normal case, Δχ is 4° or more and the peak intensity ratio is 95% or more, and in the abnormal case, Δχ is less than 4° and the peak intensity ratio is less than 95%. Here, Δχ refers to an index representing the half-width at half maximum of the peak in the χ direction in degrees when X-rays are incident on the measurement object from the θ direction along the long direction and forming a predetermined angle θ with the long direction, and the diffracted X-rays are detected by a two-dimensional detector. Here, the χ direction refers to the direction perpendicular to the θ direction. The causes of abnormal crystal orientation are abnormal gas flow rate, abnormal vacuum degree, or abnormal discharge. For the surface temperature t1, in the normal case, for example, 780°C < t1 < 820°C, and in the abnormal case, 820°C ≤ t1 or t1 ≤ 780°C. The causes of abnormal surface temperature are heater failure or thermocouple failure. For the set temperature t2, in the normal case, for example, 780°C < t2 < 820°C, and in the abnormal case, 820°C ≤ t2 or t2 ≤ 780°C. The cause of abnormal set temperature is human setting error.

[0148] The trained model 144(3) used in step S23A will be described with reference to Figure 27. In step S23A, inference device 9 uses trained model 144(3) to infer whether or not there is a cause of defect in the concentration of oxygen gas abnormality in the film formation process of superconducting layer 13, from data on the surface image of superconducting layer 13, the crystal orientation of superconducting layer 13, the surface temperature of superconducting layer 13, the manufacturing temperature of superconducting layer 13, the manufacturing humidity of superconducting layer 13, and the set temperature in the film formation process of superconducting layer 13.

[0149] A surface image of superconducting layer 13 can be acquired by camera 121. The crystal orientation of superconducting layer 13 can be detected by reflection high-energy electron diffraction (RHEED) or X-ray diffraction. The surface temperature of superconducting layer 13 can be detected by contacting a thermometer with the surface of superconducting layer 13 in chamber 31 of FIG. 6. The manufacturing temperature of superconducting layer 13 can be measured by the thermometer in chamber 31 of FIG. 6. The manufacturing humidity of superconducting layer 13 can be measured by the hygrometer in chamber 31 of FIG. 6. The set temperature of superconducting layer 13 can be one included in manufacturing condition data 146 of FIG. 4.

[0150] The trained model 144(4) used in step S24A will be described with reference to Figure 28. In step S24A, the inference device 9 uses the trained model 144(4) to infer whether or not there is an abnormal discharge or transportation damage during the process of forming the protective layer 14, from data on the surface image of the protective layer 14, the surface temperature of the protective layer 14, and the magnitude of the critical current.

[0151] A surface image of the protective layer 14 can be acquired by the camera 121. The surface temperature of the protective layer 14 can be detected by contacting a thermometer with the surface of the protective layer 14 in the chamber 41 of FIG. 7. The critical current is the maximum value of current that can be passed through the laminate Lm5 at the critical temperature at which the resistance of the laminate Lm5 becomes zero. The critical current can be detected by a known induction method or current flow method.

[0152] The trained model 144(5) used in step S25A will be described with reference to Figure 29. In step S25A, the inference device 9 uses trained model 144(5) to infer whether or not a temperature anomaly exists in the film-forming process of the stabilization layer 15 from the surface image of the stabilization layer 15, the manufacturing temperature of the stabilization layer 15, the set temperature in the film-forming process of the stabilization layer 15, and critical current data.

[0153] A surface image of the stabilization layer 15 can be acquired by a camera 121. The manufacturing humidity of the stabilization layer 15 can be measured by a hygrometer in the chamber 31 in FIG. 6. The set temperature in the film formation process of the stabilization layer 15 can be one included in the manufacturing condition data 146 in FIG. 4. The critical current is the maximum value of the current that can be passed through the laminate Lm6 at the critical temperature at which the resistance of the laminate Lm6 becomes zero. The critical current can be detected by a known induction method or current flow method.

[0154] The fourth measure taken in step S35 will be described with reference to FIG.

[0155] The fifth measure involves checking the data on the manufacturing conditions during the manufacturing (deposition) of the stabilization layer 15, changing the manufacturing conditions if there is any abnormality in the manufacturing conditions, and polishing and cleaning the target 52.

[0156] (Third embodiment) 31, a defect DfA detected by the surface image occurs in a portion of the laminate Lm between X11 and X12 in the X-axis direction. The amount of decrease in the critical current from the normal value Ic0 in that portion is equal to or greater than the reference value TH. A defect DfB detected by the surface image occurs in a portion of the laminate Lm between X13 and X14 in the X-axis direction. The amount of decrease in the critical current from the normal value Ic0 in that portion is equal to or greater than the reference value TH. A defect DfC detected by the surface image occurs in a portion of the laminate Lm between X15 and X16 in the X-axis direction. The amount of decrease in the critical current from the normal value Ic0 in that portion is equal to or greater than the reference value TH.

[0157] The defect location based on the surface image can be the position of a pixel having an outlier pixel value in the histogram of the surface image.

[0158] In steps S21A, S22A, S23A, S24A, and S25A, the inference device 9 uses the rule base to perform inference from the input data as to whether or not a specific cause of an abnormality exists.

[0159] The rule base RB(1) used in step S21A will be described with reference to Fig. 32. In step S21A, the inference device 9 uses the rule base RB(1) to infer that the cause of the defect is insufficient drying of the polishing liquid, insufficient drying of the cleaning liquid, scratches on the rolling roll 71, or transfer of dirt from the rolling roll 71 when a defect location based on the surface image of the substrate 11 after polishing coincides with a location (decreased location) where the amount of decrease in the critical current of the laminate Lm2 from the normal value Ic0 is equal to or greater than a reference value.

[0160] The rule base RB(2) used in step S22A will be described with reference to Fig. 33. In step S22A, the inference device 9 uses the rule base RB(2) to infer that there is a cause of abnormal discharge during the manufacturing (deposition) of the intermediate layer 12 when a defect location based on the surface image of the intermediate layer 12 coincides with a location (decreasing location) where the amount of decrease in the critical current of the laminate Lm3 from the normal value Ic0 is equal to or greater than a reference value.

[0161] The rule base RB(3) used in step S23A will be described with reference to Fig. 34. In step S23A, inference device 9 uses rule base RB(3) for inferring that there is a cause of poor manufacturing conditions during the manufacturing (deposition) of superconducting layer 13 when a defect location based on the surface image of superconducting layer 13 coincides with a location (decreasing location) where the amount of decrease in the critical current of laminate Lm4 from the normal value Ic0 is equal to or greater than a reference value.

[0162] The rule base RB(4) used in step S24A will be described with reference to Fig. 35. In step S24A, the inference device 9 uses the rule base RB(4) to infer that there is a cause of poor manufacturing conditions during manufacturing (deposition) of the protective layer when a defect location based on the surface image of the protective layer 14 coincides with a location (decreasing location) where the amount of decrease in the critical current of the laminate Lm5 from the normal value Ic0 is equal to or greater than a reference value.

[0163] The rule base RB(5) used in step S25A will be described with reference to Fig. 36. In step S25A, the inference device 9 uses the rule base RB(5) to infer that there is a cause of poor manufacturing conditions during manufacturing (deposition) of the stabilization layer when a defect location based on the surface image of the stabilization layer 15 coincides with a location (decreasing location) where the amount of decrease in the critical current of the laminate Lm6 from the normal value Ic0 is equal to or greater than a reference value.

[0164] In the first and second embodiments, the inference device 9 uses a trained model to infer whether or not a specific cause of an abnormality exists from the input data, but the present invention is not limited to this. The inference device may also use a rule base to infer whether or not a specific cause of an abnormality exists from the input data.

[0165] In the above embodiment, the control device 100 is configured to include the learning device 8, the inference device 9, and the storage 7, but this is not limiting. The learning device 8, the inference device 9, and the storage 7 may be configured to be provided in an external server different from the control device 100.

[0166] The embodiments disclosed herein are illustrative in all respects and should not be considered limiting. The scope of the present invention is defined by the claims rather than the above-described embodiments, and it is intended to include any modifications within the scope of the claims and meanings equivalent to the claims. [Explanation of symbols]

[0167] 2. Transport mechanism control unit 3 Manufacturing condition setting device 4 User Input Section 5 monitors 6. Imaging unit 7. Storage 8 Learning Device 9 Reasoning device 10 Superconducting wire 11 Circuit Board 12 Middle Class 13 Superconducting layer 14 Protective layer 15 Stabilization Layer 21, 31, 41, 51 Chambers 22, 32, 42, 52 targets 23,43,53 cathode 24, 44, 54 Bias power supply 33 Target holder 34 Laser light source 35 Exhaust section 36 Heating device 71 Rolling Mill 100 control device 121 Camera 122 Lighting equipment 143 training data 144 trained models 145 Surface Image 146 Manufacturing Condition Data 310 Conveying mechanism 311,312 Motor 321,322 Pulley Lm, Lm1, LM2, Lm3, Lm4, Lm5, Lm6 laminate.

Claims

1. 1. A method for inspecting a laminate manufactured by a plurality of steps of laminating a plurality of layers onto a substrate, comprising: an imaging device capturing an image of a surface of the inspection target, the substrate having undergone one of the plurality of processes; and a step in which a control device uses at least the surface image to infer whether a particular cause of an anomaly has occurred in the process.

2. 2. The method for inspecting a laminated material according to claim 1, wherein the laminated material is manufactured by laminating the substrate, intermediate layer, superconducting layer, protective layer, and stabilizing layer in this order.

3. The laminate inspection method of claim 2, wherein the inferring step includes a step in which the control device infers from the surface image of the substrate after the polishing process whether or not at least one of the following causes has occurred: poor drying of the polishing liquid, poor drying of the cleaning liquid, scratches on the rolling roll, and transfer of dirt from the rolling roll.

4. The laminate inspection method of claim 2, wherein the inferring step includes a step in which the control device infers whether or not a cause of abnormal discharge has occurred during the deposition of the intermediate layer from a surface image of the intermediate layer and data on the manufacturing conditions of the intermediate layer after the process of depositing the intermediate layer on the substrate has been performed.

5. 3. The laminate inspection method according to claim 2, wherein the inferring step includes a step in which the control device infers whether or not a cause of a defect in the manufacturing conditions of the superconducting layer has occurred from a surface image of the superconducting layer and data on the manufacturing conditions of the superconducting layer after the process of forming the superconducting layer on the substrate has been performed.

6. The laminate inspection method of claim 2, wherein the inferring step includes a step in which the control device infers whether or not a cause of abnormal discharge has occurred during the formation of the protective layer from a surface image of the protective layer and data on the manufacturing conditions of the protective layer after the process of forming the protective layer on the substrate has been performed.

7. 3. The laminate inspection method according to claim 2, wherein the inferring step includes a step in which the control device infers whether or not a cause of foreign matter adhesion exists on the substrate from a surface image of the substrate before polishing.

8. The laminate inspection method of claim 2, wherein the inferring step includes a step in which the control device infers whether or not there is a cause for insufficient polishing in the substrate polishing process from a surface image of the substrate after the substrate polishing process has been performed.

9. The laminate inspection method of claim 2, wherein the inferring step includes a step in which the control device infers whether or not there is a cause of abnormal discharge during the process of forming the intermediate layer from a surface image of the intermediate layer, the crystalline orientation of the intermediate layer, the surface temperature of the intermediate layer, the manufacturing temperature of the intermediate layer, the manufacturing humidity of the intermediate layer, and the set temperature during the process of forming the intermediate layer, after the process of forming the intermediate layer on the substrate has been performed.

10. 3. The laminate inspection method according to claim 2, wherein the inferring step includes a step in which the control device infers, after the step of forming a superconducting layer on the substrate, whether or not a cause of the defect exists in the concentration of oxygen gas abnormality during the step of forming the superconducting layer, from a surface image of the superconducting layer, the crystalline orientation of the superconducting layer, the surface temperature of the superconducting layer, the manufacturing temperature of the superconducting layer, the manufacturing humidity of the superconducting layer, and the set temperature during the step of forming the superconducting layer.

11. The laminate inspection method of claim 2, wherein the inferring step includes a step in which the control device infers whether or not there is a cause of abnormal discharge or transportation damage during the process of forming the protective layer from a surface image of the protective layer, the surface temperature of the protective layer, and the magnitude of the critical current after the process of forming the protective layer on the substrate has been performed.

12. The laminate inspection method of claim 2, wherein the inferring step includes a step in which the control device infers whether or not there is a cause of temperature abnormality in the process of forming the stabilization layer from a surface image of the stabilization layer, the manufacturing temperature of the stabilization layer, the set temperature in the process of forming the stabilization layer, and the magnitude of the critical current after the process of forming the stabilization layer on the substrate has been performed.

13. 3. A laminate inspection method as described in claim 2, wherein the inferring step includes a step in which the control device infers that a specific cause of an abnormality has occurred in the process when a defect location based on the surface image coincides with a location where the decrease in critical current from the normal value is equal to or greater than a reference value.

14. The method for inspecting a laminated material according to claim 3 , wherein the inferring step comprises a step of performing the inference using a trained model.

15. A method for manufacturing a laminate, comprising: a first manufacturing step of polishing a substrate; a second manufacturing step of depositing an intermediate layer on the substrate after the first manufacturing step; a third manufacturing step of forming a superconducting layer on the intermediate layer after the second manufacturing step; a fourth manufacturing step of forming a protective layer on the superconducting layer after the third manufacturing step; a fifth manufacturing step of forming a stabilizing layer on the protective layer after the fourth manufacturing step; An inspection step of inspecting the laminated material, The inspection step includes: a step of inspecting the substrate after at least one of the first manufacturing process, the second manufacturing process, the third manufacturing process, and the fourth manufacturing process has been performed, and acquiring a surface image of the inspection object by an imaging device; and a control device using at least the surface image to infer whether a particular cause of anomaly has occurred.

16. a step of implementing a predetermined countermeasure when it is inferred that a specific cause of an abnormality has occurred in the inspection step; 16. The method of claim 15, further comprising the step of: repeating the process from the first manufacturing step on a new substrate.

17. the inspection step includes a first inspection step in which the substrate after the first manufacturing step is subjected to inspection, The method for manufacturing a laminated material according to claim 16, wherein the step of implementing the measures includes a first step of implementing a change in the drying method after cleaning of the substrate and polishing and cleaning of the rolling rolls.

18. the inspection step includes a second inspection step in which the substrate after the second manufacturing step is subjected to inspection, The method for manufacturing a laminated material according to claim 16, wherein the step of implementing the countermeasures includes a second countermeasure step of checking the manufacturing conditions when forming the intermediate layer, changing the manufacturing conditions if there is an abnormality in the manufacturing conditions, and polishing and cleaning the target.

19. the inspection step includes a third inspection step in which the substrate after the third manufacturing step is subjected to inspection, The method for manufacturing a laminated material according to claim 16, wherein the step of implementing the measures includes a third step of checking the manufacturing conditions when the superconducting layer is formed and, if any abnormality is found in the manufacturing conditions, changing the manufacturing conditions.

20. the inspection step includes a fourth inspection step in which the substrate after the fourth manufacturing step is subjected to inspection, The method for manufacturing a laminated material described in claim 16, wherein the step of implementing the countermeasures includes a fourth countermeasure step of checking the manufacturing conditions when the protective layer is formed, changing the manufacturing conditions if there is an abnormality in the manufacturing conditions, and polishing and cleaning the target.

21. 1. An inspection system for inspecting a laminate manufactured by a plurality of steps of laminating a plurality of layers onto a substrate, comprising: an imaging device for capturing an image of a surface of the substrate that has undergone one of the plurality of processes as an inspection object; and an inference device that uses at least the surface image to infer whether a cause of a specific abnormality has occurred in the process.

Images