Roll-to-roll parameter control system

Abstract

The roll-to-roll parameter control system of the present invention comprises: a deep learning module that receives at least one image from a line scanner that captures a predetermined position of a web and recognizes a cutting line included in the at least one image, based on the identified depth of the cutting line, the identified width of the cutting line, the identified angle formed by the cutting line and the coiled material and the identified interval between the cutting lines, adjusting information related to control parameters used for controlling the reel-to-reel device to work is calculated; and a control unit that generates a correction value of the control parameter on the basis of adjustment information relating to the control parameter, and transmits a control signal generated on the basis of the correction value of the control parameter to the roll-to-roll device, the control parameters comprise the cutting speed of a cutting module included in the roll-to-roll device, the line angle of the cutting module, the moving speed of the coiled material in the roll-to-roll device and the tension of the coiled material.

Description

Technical Field

[0001] This invention relates to a system for controlling control parameters related to the operation of a roll-to-roll (ROLL-TO-ROLL) thin-film solar cell manufacturing apparatus. Specifically, this invention relates to a roll-to-roll (R2R) parameter control system and method that generates control parameter correction values ​​based on the quality of the cutting lines formed on the roll material and transmits the associated control signals to the thin-film solar cell manufacturing apparatus. Background Technology

[0002] The content described in this section is only to provide background information for this embodiment and does not constitute prior art.

[0003] In thin-film solar cells, the scribing line plays a crucial role, significantly impacting the overall performance and efficiency of the solar cell. A thin-film solar cell module consists of multiple small individual cells, each absorbing sunlight and generating current independently. The scribing line electrically isolates each individual cell, enabling them to operate independently while simultaneously connecting them to each other; this is an essential element for the normal operation of the solar cell module.

[0004] These cutting lines are formed using an automated system. This automated system plays a crucial role in the manufacturing process of thin-film solar cells; however, it has limitations in terms of variable control.

[0005] Automated system control requires managing numerous variables. For example, precise synchronization is needed for machine position adjustments such as laser power, roll material movement speed, roll material tension, and the movement line of the cutting module. In such complex systems, perfect control of the interactions between variables is difficult; even minute errors can affect the entire process. Therefore, imperfect hardware and software integration can lead to system malfunctions or errors.

[0006] While automated systems for cutting wires offer many advantages, they also have limitations in controlling numerous variables, and techniques are needed to address these limitations.

[0007] Existing technical documents Patent documents Patent Document 1: Korean Patent Publication No. 10-2277201 (Invention Title: Real-time Roll-to-Roll Process Correction Method Using Multiple Cut Images) Summary of the Invention The problem the invention aims to solve The purpose of this invention is to provide a roll-to-roll parameter control system for the working parameters of an image control roll-to-roll device based on the image capture cutting line.

[0008] Furthermore, another object of the present invention is to provide a roll-to-roll parameter control system and method capable of estimating and controlling one of the depth, width, and linear movement capability of the cutting lines included in an image.

[0009] Furthermore, another object of the present invention is to provide a roll-to-roll parameter control system and method that generates a correction value based on one of the following: the depth, width, and linear movement capability of the cutting line, and the cutting speed, line angle of the cutting module, web movement speed, web tension, and jump speed.

[0010] The objectives of this invention are not limited to those mentioned above. Other objectives and advantages not mentioned in the invention can be understood through the following description and further clarified through the embodiments of the invention. Furthermore, it is obvious that the objectives and advantages of this invention can be achieved through devices and combinations thereof within the scope of the claims.

[0011] means for solving problems An embodiment of the roll-to-roll parameter control system of the present invention is used to control a roll-to-roll (R2R) device, comprising: a deep learning module that receives at least one image from a line scanner at a predetermined position on a web and identifies cutting lines included in the at least one image; calculates adjustment information related to control parameters for controlling the operation of the roll-to-roll device based on the depth of the identified cutting lines, the width of the cutting lines, the angle formed by the cutting lines and the web, and the interval between the cutting lines; and a control unit that generates correction values ​​for the control parameters based on the adjustment information related to the control parameters, and transmits control signals generated based on the correction values ​​of the control parameters to the roll-to-roll device. The control parameters may include the cutting speed of the cutting module included in the roll-to-roll device, the line angle of the cutting module, the moving speed of the web within the roll-to-roll device, and the tension of the web.

[0012] Furthermore, the line scanner includes at least one camera for capturing images at a specified location on the roll material, and the camera can generate the image including the cutting line.

[0013] Furthermore, the control parameters also include jump speed, which can be the speed at which the cutting module moves from the first position to the second position to form a cutting line and then returns from the second position to the first position.

[0014] Furthermore, the control unit can generate a first control signal based on a correction value related to the cutting speed of the cutting module, the line angle of the cutting module, and the jump speed, so as to adjust the position of the cutting module by adjusting the cutting coordinates and angle of the cutting module.

[0015] Furthermore, the control unit can generate a second control signal based on a correction value related to the moving speed and tension of the roll material, in order to adjust the rotational speed of the multiple rollers included in the roll-to-roll device.

[0016] Furthermore, the deep learning module can calculate adjustment information related to at least one of the cutting speed of the cutting module, the moving speed of the roll, the tension of the roll, and the jumping speed based on at least one of the depth and width of the cutting line.

[0017] Furthermore, the deep learning module can calculate adjustment information related to at least one of the following: the cutting speed of the cutting module, the line angle of the cutting module, the moving speed of the roll material, the tension of the roll material, and the jumping speed, based on the angle of the cutting line.

[0018] Furthermore, the deep learning module can calculate adjustment information related to at least one of the following: the moving speed of the roll material, the cutting speed of the cutting module, and the jumping speed, based on the interval between the cutting lines.

[0019] Furthermore, the deep learning module calculates the quality score of the cutting line based on the depth of the cutting line, the width of the cutting line, the angle formed by the cutting line and the roll material, and the interval between the cutting lines, and can determine whether to stop the roll-to-roll device based on the quality score.

[0020] Furthermore, the control unit can generate control signals related to the cessation of operation of the roll-to-roll device based on whether the operation is stopped.

[0021] Invention Effects The roll-to-roll parameter control system and method of the present invention can estimate one of the depth, width and linear movement capability of the cutting line based on the image of the cutting line captured by the deep learning module, thus making it easy to analyze the quality of the cutting line.

[0022] Furthermore, the present invention can control the interaction between various control parameters related to the operation of the roll-to-roll device based on one of the depth, width and linear movement capability of the cutting line.

[0023] Furthermore, the present invention can control the interaction between various control parameters, thus correcting operational errors caused by differences between hardware and software.

[0024] In addition to the above content, the specific effects of the present invention will be explained below in conjunction with specific embodiments used to implement the present invention. Attached Figure Description

[0025] Figure 1A conceptual diagram of a roll-to-roll parameter control system according to an embodiment of the present invention is provided for illustrative purposes.

[0026] Figure 2 and Figure 3 For illustrative purposes Figure 1 The diagram shows an example of the structure of the line scanner and roll-to-roll device.

[0027] Figure 4 For brevity Figure 1 The diagram shown is a block diagram of the roll-to-roll parameter control system.

[0028] Figures 5 to 10 This is an illustrative diagram illustrating the operation of a roll-to-roll parameter control system according to an embodiment of the present invention.

[0029] Figure 11 This is a flowchart illustrating a roll-to-roll parameter control method according to an embodiment of the present invention. Detailed Implementation

[0030] In this specification and the scope of the invention claims, the terms or words used should not be limited to their ordinary or dictionary meanings. Based on the principle that inventors can define terms or words to best describe their invention, they should be interpreted according to their meanings and concepts consistent with the technical concept of the invention. Furthermore, it should be understood that the embodiments described in this specification and the structures shown in the accompanying drawings are merely one embodiment of the invention and do not represent the entirety of the technical concept. Therefore, at the time of this application, there may be equivalent technical solutions and variations that can replace them.

[0031] In this specification and the scope of the invention claims, the terms "first," "second," "A," "B," etc., are used to describe various structural elements, and the structural elements are not limited to the terms used. These terms are used only to distinguish one structural element from another. For example, without departing from the scope of the invention claims, a first structural element may be named a second structural element, and similarly, a second structural element may be named a first structural element. The term "and / or" includes a combination of multiple related descriptions or one of multiple related descriptions.

[0032] In this specification and the scope of the invention claims, the terminology used is for illustrative purposes only and does not limit the invention. Unless the context clearly indicates otherwise, singular expressions include plural expressions. It should be understood in this application that terms such as "comprising" or "having" do not preclude the presence or addition of features, numbers, steps, operations, structural elements, components, or combinations thereof described in the specification.

[0033] Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0034] Terms defined in commonly used dictionaries should be interpreted as having the same meaning as they have in the context of the relevant technology, and should not be interpreted as having an idealized or overly formal meaning unless explicitly defined in this application.

[0035] Furthermore, the various structures, processes, procedures, or methods included in the various embodiments of the present invention can be shared within a scope that is not contradictory at the technical level.

[0036] The following is for reference Figures 1 to 11 This invention provides a detailed description of the roll-to-roll parameter control system and method according to embodiments of the present invention.

[0037] First, refer to Figures 1 to 10 Explain the roll-to-roll parameter control system.

[0038] Figure 1 To briefly illustrate a conceptual diagram of a roll-to-roll parameter control system according to an embodiment of the present invention, Figure 2 and Figure 3 For illustrative purposes Figure 1 The diagram shown is an example of the structure of the line scanner and roll-to-roll device. Figure 4 For brevity Figure 1 The block diagram shown is for a roll-to-roll parameter control system. Figures 5 to 10 This is an illustrative diagram illustrating the operation of a roll-to-roll parameter control system according to an embodiment of the present invention.

[0039] Reference Figures 1 to 3 The roll-to-roll parameter control system 100, required to control the roll-to-roll (R2R) thin-film solar cell manufacturing apparatus 300, receives at least one image of the web 10, captured by a line scanner 200 at a predetermined position of the web 10 moving within the roll-to-roll apparatus 300. Furthermore, based on the at least one web image, it calculates roll-to-roll quality parameters related to the quality of the thin-film solar cells produced by the roll-to-roll apparatus 300, and generates correction values ​​based on these quality parameters for control parameters used to control the operation of the roll-to-roll apparatus. Then, it generates control signals based on the correction values ​​of the control parameters and transmits them to the roll-to-roll apparatus 300.

[0040] The line scanner 200 may include multiple cameras 210, and at least one camera 210 may be provided in each process step of the roll-to-roll apparatus 300. In each process step, the camera 210 may capture a predetermined portion of the roll 10 to generate a roll image. In this case, the roll image may at least include a predetermined portion formed on the cutting lines of the roll 10.

[0041] Furthermore, web-based materials are flexible, therefore, such as Figure 2 As shown, multiple rollers 310 of the roll-to-roll assembly 300 can move to form multiple cut lines on the roll material. The roll material, used as a substrate in the manufacturing process of thin-film solar cells, refers to the base material for all layers of the vapor-deposited thin-film solar cell and can be made of various materials such as plastic (PET), metal (stainless steel, aluminum), and glass. Continuous manufacturing methods such as roll-to-roll processes can be primarily used.

[0042] In order to perform the work described above, the roll-to-roll parameter control system 100 may include a deep learning module 110 and a control unit 120.

[0043] The deep learning module 110 receives at least one image of the roll material from the camera 210 and can identify at least one cutting line included in the image. Furthermore, by analyzing one or more of the depth, width, and linear movement capability of the identified cutting line, it can calculate roll-to-roll quality parameters. The linear movement capability indicates whether the cutting line is orthogonal to one side of the roll material 10.

[0044] The roll-to-roll quality parameters may include one or more of the following: the quality fraction of the cutting line, whether to stop the roll-to-roll device 300, and adjustment information of the control parameters. Furthermore, the control parameters may include one or more of the following: the cutting speed of the cutting module included in the roll-to-roll device 300; the scanning line angle of the cutting module; the web speed; the web tension; and the jump speed.

[0045] Specifically, the deep learning module 110 generates fragment images of roll material images through a fragment image generation model. Based on the fragment images, the cutting line analysis model can estimate one or more of the cutting line depth, width, and straight-line movement capability to calculate roll-to-roll quality parameters.

[0046] The fragment image generation model is formed as a U-net structure, which can generate fragment images related to at least one cutting line included in the roll image through machine learning. The cutting line analysis model infers one or more of the cutting line's depth, width, and straight-line movement capability based on the fragment image. Thus, roll-to-roll quality parameters can be calculated through machine learning.

[0047] The normal cutting line should be a straight line relative to one side of the roll 10, with the depth and width set to predetermined values. The deep learning module 10 can calculate roll-to-roll quality parameters based on the conditions described above.

[0048] In the roll-to-roll quality parameters, the quality score of the cutting line is a value that reflects the depth, width and straight-line movement capability of the cutting line. If the depth and width of the cutting line deviate from the preset value, the score will decrease. If the angle formed by the cutting line and one side of the roll material 10 deviates from a right angle, the score will decrease.

[0049] Furthermore, whether to stop the operation of the roll-to-roll device 300 can be determined based on the quality fraction of the cutting line. For example, if the quality fraction of the cutting line is below a specified value, it can be determined that the operation of the roll-to-roll device 300 should be temporarily stopped.

[0050] Next, refer to Figures 5 to 10 This describes the process of generating adjustment information related to control parameters.

[0051] First, refer to Figure 5 Briefly, the process of forming the cutting line involves the cutting module 320 moving laterally from one side of the roll 10 to the other along a predetermined moving line 321. A laser is irradiated onto the roll 10, and the cutting line 11 is formed by laser etching of the uppermost layer of the roll 10. In this case, the roll 10 can be moved by the first roller 310-1 and the second roller 310-2. The roll 10 moves along the moving line 321, which is formed by the cutting module 320 at a speed corresponding to the moving speed of the roll 10, according to the power of the first roller 310-1 and the second roller 310-2. Thus, a cutting line 11 perpendicular to one side of the roll 10 can be formed.

[0052] To form a high-quality fractional cutting line 11, that is, to ensure that the cutting line 11 is formed as a straight line perpendicular to one side of the roll material 10 and has a preset depth and width, it is necessary to minimize the errors between the various control parameters. To this end, the deep learning module 110 can calculate the adjustment information of each control parameter to simultaneously satisfy the conditions of each control parameter.

[0053] The following is for reference Figures 6 to 10 This example illustrates the process of generating adjustment information related to the cutting speed of the cutting module, the line angle of the cutting module, the web movement speed, the web tension, and the jump speed, which are used as control parameters.

[0054] Although the cutting line is formed as a straight line, if the depth or width of the cutting line is greater than a preset value, the laser irradiation time of the roll 10 may increase due to a decrease in the cutting speed of the cutting module and the roll movement speed. Therefore, adjustment information can be generated to increase the cutting speed of the cutting module and the roll movement speed.

[0055] And, as Figure 6 and Figure 7As shown, if the cutting line 11 is formed as an oblique line, the roll material moving speed and the cutting speed of the cutting module 320 will not correspond, or the line angle of the cutting module may be incorrect. Therefore, adjustment information related to the roll material moving speed, the cutting speed of the cutting module, and the line angle of the cutting module can be generated.

[0056] like Figure 6 As shown, when the cutting line 11 is formed as an oblique line, if the angle θ1 formed by the cutting line 11 and one side of the roll material 10 is an acute angle, then the cutting speed of the cutting module 320 is greater than the moving speed of the roll material 10, or the moving speed of the roll material 10 can be less than the cutting speed of the cutting module 320. Furthermore, in Figure 7 In such cases, errors may occur in the line angle θ2 of the moving line 321 of the cutting module 320 and the moving speed of the roll material 10. For example... Figure 7 As shown, if the line angle θ2 is less than the line angle corresponding to the moving speed of the roll 10, the cutting line 11 can be formed as an oblique line forming an acute angle θ1 with one side of the roll 10.

[0057] Conversely, such as Figure 7 As shown, when the cutting line 11 is formed as an oblique line, if the angle θ1 formed by the cutting line 11 and one side of the roll material 10 is an obtuse angle, then the cutting speed of the cutting module 320 is less than the moving speed of the roll material 10, or the moving speed of the roll material 10 may be greater than the cutting speed of the cutting module 320. Furthermore, this may also cause errors in the line angle θ2 relative to the moving line 321 of the cutting module 320 and the moving speed of the roll material 10. Figure 8 As shown, if the line angle θ2 is less than the line angle corresponding to the moving speed of the roll 10, the cutting line 11 can be formed as an obtuse angle θ1 with one side of the roll 10.

[0058] Therefore, as Figure 6 and Figure 7 As shown, when the cutting line 11 is formed as an oblique line, adjustment information related to one or more of the following can be generated: the roll material moving speed, the cutting speed of the cutting module, and the line angle of the cutting module.

[0059] Furthermore, if the depth or width of the cutting line is not constant, or if the cutting line is segmented in certain sections, the resulting weakening of the roll material tension may lead to bending or shaking of the roll material. Therefore, information for adjusting the roll material tension can be generated. For example... Figure 8 As shown, if the roll 10 bends or shakes due to weakened tension, the width of a specific portion of the cut line 11 can be widened, or, as... Figure 9As shown, the cutting line 11 may be segmented. Additionally, the deep learning module 110 can estimate the tension of the roll 10 through machine learning, and can estimate the tension information of the roll 10 through images captured by the camera 210, thereby generating roll tension adjustment information.

[0060] And, as Figure 10 As shown, when the roll material 10 forms multiple cutting lines 11, adjustment information related to one or more of the following—the moving speed of the roll material 10, the cutting speed of the cutting module 320, and the jump speed—can be generated based on the interval 12 between the first cutting line 11-1 and the second cutting line 11-2. The jump speed refers to the speed at which the cutting module 320 forms a cutting line 11 and returns to its original position. The cutting module 320 moves along the moving line 321 and forms the cutting line 11. The cutting module 320 moves from the first position 322 to the second position 323, and the jump speed refers to the speed at which it returns from the second position 323 to the first position 322.

[0061] If the interval 12-1 between the first cutting line 11-1 and the second cutting line 11-2 is greater than a preset interval, the moving speed of the roll 10 and the cutting speed of the cutting module 320 may slow down or the jumping speed may slow down. If the second cutting line 11-2 is formed on the roll 10 with the first cutting line 11-1, the interval 12-1 between the first cutting line 11-1 and the second cutting line 11-2 may become relatively wider due to the slower moving speed of the roll 10 and the cutting speed of the cutting module 320.

[0062] Conversely, if the interval 12-2 between the first cutting line 11-1 and the second cutting line 11-2 is less than a preset interval, the moving speed of the roll 10 and the cutting speed of the cutting module 320 may increase, or the jumping speed may increase. If the second cutting line 11-2 is formed, the interval 12-1 between the first cutting line 11-1 and the second cutting line 11-2 may become relatively narrower due to the increased moving speed of the roll 10 and the cutting speed of the cutting module 320. Furthermore, as the jumping speed increases, the roll quickly returns from the second position 323 to the first position 322, thus the interval 12-2 can become narrower.

[0063] Therefore, adjustment information related to one or more of the following—the moving speed of the roll 10, the cutting speed of the cutting module 320, and the jumping speed—can be generated based on the interval 12 between the first cutting line 11-1 and the second cutting line 11-2.

[0064] As described above, the adjustment information of the control parameters is not related to the specified phenomenon or any single control parameter, but can be related to all control parameters of the specified phenomenon. Therefore, the deep learning module 110 can generate adjustment information related to one or more of the following: the cutting speed of the cutting module, the line angle of the cutting module, the web movement speed, the web tension, and the jump speed.

[0065] The control unit 120 generates correction values ​​related to the control parameters controlling the operation of the roll-to-roll device 300 based on the roll-to-roll quality parameters generated by the deep learning module 110. It can generate control signals based on the control parameter correction values ​​and transmit them to the roll-to-roll device 300. In this case, the control unit 120 can calculate the correction values ​​of each control parameter based on the control parameter values ​​currently set in the roll-to-roll device 300.

[0066] Specifically, the control unit 120 can generate and transmit a control signal related to stopping the operation of the roll-to-roll device 300 based on whether the roll-to-roll quality parameters include whether to stop the operation of the roll-to-roll device 300.

[0067] Furthermore, the control unit 120 can generate a first control signal based on the correction values ​​of various control parameters to adjust the position of the cutting module 320 by adjusting the cutting coordinates and angle of the cutting module 320. In this case, the control unit 120 can generate the first control signal based on a correction value related to one or more of the cutting speed, the line angle of the cutting module, and the jump speed of the cutting module.

[0068] Furthermore, the control unit 120 can generate a second control signal based on the correction value of the control parameters to adjust the rotational speed of the plurality of rollers 310 included in the roll-to-roll device 300. In this case, the control unit 120 can generate the second control signal based on one or more correction values ​​related to the web travel speed and the web tension.

[0069] Refer again Figure 1 and Figure 3 The line scanner 200 may include a plurality of cameras 210, each camera 210 being capable of generating at least one image relating to a predetermined position of a web 10 moving via a plurality of rollers 310 of the roll-to-roll apparatus 300. Each camera 210 is capable of capturing a predetermined position of the web 10 in a manner that includes a cut line 11 formed on the web 10, thereby generating an image including the cut line 11.

[0070] After the processes of forming P1 cutting line 11-1, P2 cutting line 11-2, and P3 cutting line 11-3, cameras 210 can be installed to photograph a portion of the roll 10 including the cutting lines 11. Figure 3As shown, there may be two cameras 210 to capture the two ends of the cutting line 11, or there may be one camera to capture the entire cutting line 11, but it is not limited to this. Additionally, the line scanner 200 may be included within the parameter control system 100.

[0071] Therefore, the roll-to-roll parameter control system 100 can generate correction values ​​for control parameters for each process forming the cutting lines, and transmit the corresponding control signals to the roll-to-roll device 300, thereby adjusting the control parameters of each process step.

[0072] Figure 11 This is a flowchart illustrating a roll-to-roll parameter control method according to an embodiment of the present invention.

[0073] The following is for reference Figure 1 , Figure 2 and Figure 11 This paper describes a roll-to-roll parameter control method using a roll-to-roll parameter control system 100. In the roll-to-roll parameter control method S100, at least one image related to a specified position of the web is received from a line scanner (step S110), and roll-to-roll quality parameters are calculated based on the at least one image (step S120). Furthermore, a correction value related to control parameters controlling the operation of the roll-to-roll device 300 can be generated based on the roll-to-roll quality parameters (step S130), and a control signal generated based on the correction value of the control parameters can be transmitted to the roll-to-roll device 300 (step S140).

[0074] The line scanner 200 may include multiple cameras 210, with at least one camera 210 provided in each process step of the roll-to-roll apparatus 300. In each process step, the camera 210 can capture images of a defined portion of the roll 10 to generate an image. The image may at least include a defined portion formed along the cut lines of the roll 10. The roll (web) has flexibility, such as... Figure 3 As shown, multiple rollers 310 of the roll-to-roll device 300 can move to form multiple cut lines 11 on the roll material.

[0075] Furthermore, the roll-to-roll quality parameters may include one or more of the following: the quality fraction of the cutting line, whether to stop the operation of the roll-to-roll device 300, and adjustment information of the control parameters. The control parameters may include one or more of the following: the cutting speed of the cutting module included in the roll-to-roll device 300, the line angle of the cutting module, the web travel speed, the web tension, and the jump speed.

[0076] The above description is merely illustrative of the technical concept of this embodiment. Those skilled in the art can make various modifications and variations without departing from the essential characteristics of this embodiment. Therefore, this embodiment is for illustrative purposes only and is not intended to limit the technical concept of this embodiment. Such embodiments do not limit the scope of the technical concept of this embodiment. The protection scope of this embodiment should be interpreted based on the following claims, and all technical concepts within the equivalent scope of these claims fall within the protection scope of this embodiment.

Claims

1. A roll-to-roll parameter control system for controlling a roll-to-roll device, characterized in that, include: A deep learning module receives at least one image from a line scanner at a specified location on the roll material and identifies cutting lines included in the at least one image. Based on the depth of the identified cutting lines, the width of the cutting lines, the angle formed by the cutting lines and the roll material, and the interval between the cutting lines, it calculates adjustment information related to control parameters for controlling the operation of the roll-to-roll device. The control unit generates a correction value for the control parameters based on adjustment information related to the control parameters, and transmits a control signal generated based on the correction value of the control parameters to the roll-to-roll device. The control parameters include the cutting speed of the cutting module included in the roll-to-roll device, the line angle of the cutting module, the moving speed of the roll material within the roll-to-roll device, and the tension of the roll material.

2. The roll-to-roll parameter control system according to claim 1, characterized in that, The line scanner includes at least one camera for capturing images of a specified location on the roll material. The camera generates the image including the cutting line.

3. The roll-to-roll parameter control system according to claim 1, characterized in that, The control parameters also include jump speed. The jump speed is the speed at which the cutting module moves from the first position to the second position to form a cutting line and then returns from the second position to the first position.

4. The roll-to-roll parameter control system of claim 3, wherein, The control unit generates a first control signal based on a correction value related to the cutting speed of the cutting module, the line angle of the cutting module, and the jump speed, in order to adjust the position of the cutting module by adjusting the cutting coordinates and angle of the cutting module.

5. The roll-to-roll parameter control system of claim 3, wherein, The control unit generates a second control signal based on a correction value related to the moving speed and tension of the roll material, to adjust the rotational speed of the multiple rollers included in the roll-to-roll device.

6. The roll-to-roll parameter control system of claim 3, wherein, The deep learning module calculates adjustment information related to at least one of the cutting speed of the cutting module, the moving speed of the roll, the tension of the roll, and the jumping speed based on at least one of the depth and width of the cutting line.

7. The roll-to-roll parameter control system according to claim 3, characterized in that, The deep learning module calculates adjustment information based on the angle of the cutting line and related to at least one of the following: the cutting speed of the cutting module, the line angle of the cutting module, the moving speed of the roll material, the tension of the roll material, and the jumping speed.

8. The roll-to-roll parameter control system according to claim 3, characterized in that, The deep learning module calculates adjustment information related to at least one of the following: the moving speed of the roll material, the cutting speed of the cutting module, and the jumping speed, based on the interval between the cutting lines.

9. The roll-to-roll parameter control system according to claim 1, characterized in that, The deep learning module calculates the quality score of the cutting line based on the depth of the cutting line, the width of the cutting line, the angle formed by the cutting line and the roll material, and the interval between the cutting lines, and determines whether to stop the roll-to-roll device based on the quality score.

10. The roll-to-roll parameter control system according to claim 9, characterized in that, The control unit generates control signals related to the cessation of operation of the roll-to-roll device based on whether the operation is stopped.

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