Control method and system of printed circuit board production equipment

Abstract

The invention discloses a control method and system of printed circuit board production equipment. Through the automatic copper-clad plate scanning and image analysis process, qualified batches meeting the cutting standard are screened out, and the manual inspection time and labor force are reduced; meanwhile, after the copper-clad plates in the qualified batch are cut, the cutting quality is analyzed, plate quality evaluation indexes are obtained, the operation state of a cutting machine and the use state of a cutting tool are correspondingly evaluated based on the comparison result of the current copper-clad plate quality evaluation indexes and the analysis result, and the cutting quality of the copper-clad plates is improved. Therefore, when the cutting quality of the copper-clad plate has a problem, the problem can be checked in time, the cutting quality of each subsequent copper-clad plate is ensured, and the problems that time and labor are consumed and the subsequent production progress of a printed circuit board is influenced when the copper-clad plate needs to be manually checked one by one after the current batch of copper-clad plates are cut in the prior art are solved.

Description

Technical Field

[0001] This invention relates to the field of production equipment control technology, and in particular to a control method and system for printed circuit board production equipment. Background Technology

[0002] Printed circuit boards (PCBs) are one of the most important components in the electronics industry. As the electrical connection carrier and support for electronic components, they are widely used in various electronic devices. During the production of PCBs, a cutting machine is needed to cut the original copper-clad laminate into sizes suitable for production line processing. Traditional cutting machines rely heavily on manual operation, which results in problems such as low cutting accuracy, low efficiency, and material waste. Automated control is needed to improve cutting accuracy and production efficiency.

[0003] However, the existing control methods and systems for printed circuit board production equipment still have the following shortcomings in practical applications: The inability to pre-detect defects in the current production batch of copper-clad laminates (CCLs) to screen out qualified batches that meet the cutting standards, and the inability to analyze the cutting quality after each qualified batch of CCLs is cut, and the inability to evaluate the operating status of the cutting machine and the usage status of the cutting tools based on the analysis results, and the inability to promptly inspect, maintain or replace them according to the evaluation results, results in the inability to guarantee the quality of each CCL during the cutting process. It is necessary to manually inspect each CCL after the current batch of CCLs is cut, which is time-consuming and labor-intensive and affects the progress of subsequent printed circuit board production. When production equipment malfunctions, a maintenance worker is usually randomly selected to go to the malfunction point for inspection. Instead of selecting maintenance workers based on the location of the malfunction point, the system is not intelligent enough and the malfunction cannot be resolved in a timely manner.

[0004] To address this, a control method and system for printed circuit board production equipment is proposed. Summary of the Invention

[0005] In view of this, the present invention provides a control method and system for printed circuit board manufacturing equipment to solve the problems mentioned in the background art.

[0006] The objective of this invention can be achieved through the following technical solutions: including: S1: Place the copper-clad laminates of the current production batch in the designated target positions according to their serial numbers. Scan the copper-clad laminates placed at the designated target positions to obtain image and size information of the copper-clad laminates of the current production batch. Use image processing software to identify and mark defective areas in each set of image information. Segment the marked areas of each set of image information and extract the largest remaining complete area after segmentation as the normal area of ​​each copper-clad laminate in the current production batch. Further obtain the size of the copper-clad laminate required for the current printed circuit board and compare it with the normal area of ​​each copper-clad laminate in the current production batch. If the normal area of ​​the copper-clad laminate is larger than the required size and no defects affecting cutting are identified in the normal area, mark the copper-clad laminate as qualified; otherwise, mark it as unqualified. Based on the analysis results, classify the copper-clad laminates of the current production batch into qualified and unqualified batches. S2: After screening the unqualified batches based on step S1, the qualified batches are taken as the processing batches for the current printed circuit board production. The size of the copper-clad laminate required for the current printed circuit board is input. Based on the marking information and required size of each copper-clad laminate in the processing batch, the optimal cutting path of each copper-clad laminate in the processing batch is automatically generated. The optimal cutting path generated for each copper-clad laminate in the processing batch is then confirmed by the administrator. S3: After confirming that there are no errors, the cutting tool of the cutting machine is controlled to cut along the optimal cutting path of each copper-clad laminate in the processing batch through the preset cutting parameters. The running status of the cutting machine is recorded while each copper-clad laminate in the processing batch is being cut. After each copper-clad laminate in the processing batch is cut, the cutting tool is automatically stopped and a completion signal is issued. The cutting quality of the current copper-clad laminate is analyzed to obtain the board quality evaluation index BZP of the current copper-clad laminate. S4: Compare the current copper clad laminate quality evaluation index BZP with the preset machine quality reference threshold index. If it is less than the preset machine quality reference threshold index, no signal is generated, and the next group of copper clad laminates is cut. If it is greater than the preset machine quality reference threshold index, an abnormal signal is generated, the cutting machine is stopped, and the operating status of the cutting machine corresponding to the current copper clad laminate is analyzed to obtain the operating evaluation index YXP of the cutting machine during the cutting process of the current copper clad laminate. S5: Compare the operating evaluation index YXP of the cutting machine during the current cutting of copper-clad laminate with the preset operating reference threshold index. If it is greater than the preset operating reference threshold index, a maintenance signal is generated. The maintenance personnel with the highest maintenance evaluation value WP at the current maintenance signal generation time point are selected to go to the location of the cutting machine for inspection and maintenance. If it is less than the preset operating reference threshold index, an inspection signal is generated. S6: When an inspection signal is generated, the usage status of the cutting tool of the cutting machine at the current inspection signal generation time is analyzed to obtain the damage estimate SG of the cutting tool at the current time. The damage estimate SG of the cutting tool at the current time is compared with the preset damage estimate threshold. If it is greater than the preset damage estimate threshold, the maintenance personnel closest to the cutting machine at the current generation time are selected to go to the location of the cutting machine to replace the cutting tool. If it is less than the preset damage estimate threshold, a normal use signal is generated, and the cutting machine is started to continue cutting the next set of copper-clad laminates.

[0007] In some embodiments, the board quality assessment index (BZP) of the currently cut copper-clad laminate is obtained through the following steps: S3-101: After issuing the complete signal, move the cut copper-clad laminate to the detection position. First, measure the dimensions of the cut copper-clad laminate and compare them with the required dimensions. If there is an error between the dimensions of the cut copper-clad laminate and the required dimensions, further compare the error range with the preset error allowable threshold. When the error range is greater than the preset error allowable threshold, directly generate an abnormal signal. When the error range is less than the preset error allowable threshold, analyze the cutting quality of the cut copper-clad laminate in step S3-102. S3-102: Adjust the wavelength and power of the laser scanner, emit a thin laser beam towards the cut surface of the copper-clad laminate and capture the reflected laser, and build a three-dimensional surface model of the cut surface of the copper-clad laminate based on the captured laser. By establishing a three-dimensional model, the average roughness, maximum roughness depth, maximum height of the roughness profile, and total height of the roughness profile of the cut surface of the copper-clad laminate are obtained. The average roughness, maximum roughness depth, maximum height of the roughness profile, and total height of the roughness profile of the cut copper-clad laminate are multiplied by the corresponding preset weight coefficients and then summed to obtain the board quality evaluation index BZP of the cut copper-clad laminate.

[0008] In some embodiments, the operating evaluation index YXP of the cutting machine during the current copper-clad laminate cutting process is obtained through the following steps: S4-101: Obtain the number of vibrations of the cutting machine during the recorded time period from the recorded operating status of the cutting machine and record it as ZD1; S4-102: Obtain the cutting speed values ​​of the cutting tool of the panel saw at each time point within the recorded time period. Extract the maximum and minimum cutting speed values ​​from the cutting speed values ​​at each time point and calculate the difference between them. Use the difference as the cutting speed difference value within the recorded time period. Further calculate the cutting speed values ​​at each time point using the standard deviation formula, and use the calculation result as the cutting speed variation value within the recorded time period. Preset the weighting coefficients corresponding to the cutting speed difference value and the cutting speed variation value. Multiply the cutting speed difference value and the cutting speed variation value by the corresponding weighting coefficients and then sum them to obtain the estimated cutting speed ZD2 of the panel saw within the recorded time period. S4-103: Obtain the temperature and dust concentration values ​​of the surrounding environment of the cutting machine at each time point within the recorded time period; calculate the average temperature and dust concentration values ​​of the surrounding environment of the cutting machine at each time point to obtain the average temperature value and the average dust value; preset the weighting coefficients corresponding to the average temperature value and the average dust value; multiply the average temperature value and the average dust value by the corresponding weighting coefficients respectively and then sum them to obtain the environmental condition value ZD3 of the surrounding environment of the cutting machine within the recorded time period; S4-104: According to the formula The operating evaluation index YXP of the cutting machine during the current copper-clad laminate cutting process is obtained by weighting the vibration number ZD1, the cutting speed estimate ZD2, and the mirror value ZD3; where , as well as These represent the maximum allowed vibration frequency, maximum allowed cutting speed estimate, and maximum allowed mirror value preset for the cutting machine, respectively; fq1, fq2, and fq3 are the preset weighting factors for vibration frequency ZD1, cutting speed estimate ZD2, and mirror value ZD3, respectively.

[0009] In some embodiments, the specific steps for obtaining the maintenance assessment value (WP) for each maintenance personnel are as follows: S5-101: Based on the current time point of generating the maintenance signal, draw a circle with the cutting machine as the center and the distance as the radius, obtain each maintenance personnel within the circle as pre-selected personnel, and send a location acquisition instruction to their mobile terminals. After each pre-selected personnel confirms the received location acquisition instruction, calculate the route distance between each pre-selected personnel and the cutting machine, and use it as the distance evaluation value JP1 of each pre-selected personnel. S5-102: Obtain the total number of maintenance sessions and the duration of each maintenance session for each pre-selected personnel; calculate the average duration of each maintenance session for each pre-selected personnel, and use the calculated average duration as the reference duration for each single maintenance session for each pre-selected personnel; match the total number of maintenance sessions and the reference duration for each single maintenance session for each pre-selected personnel with the preset reference ranges for total number of maintenance sessions and reference durations, and set an experience score and a proficiency score for each reference range for total number of maintenance sessions and reference durations, respectively; obtain the experience score and proficiency score for each pre-selected personnel at the current generation time point, accumulate the experience score and proficiency score for each pre-selected personnel, and use the accumulated value as the score JP2 for each pre-selected personnel; S5-103: Calculate the total number of selections for each pre-selected person in the past thirty days corresponding to the current generation time, and use it as the quantitative evaluation value JP3 for each pre-selected person; S5-104: According to the formula The distance rating JP1, sub-rating JP2, and quantitative rating JP3 of each pre-selected person are weighted and calculated to obtain the dimension rating WP of each pre-selected person; where af1, af2, and af3 are the preset weighting factors of the distance rating JP1, sub-rating JP2, and quantitative rating JP3 of each pre-selected person, respectively.

[0010] In some embodiments, the loss estimate SG of the cutting tool of the panel saw at the current time point is obtained through the following steps: S6-101: Obtain the installation time of the cutting tool of the panel saw, calculate the time difference between the two based on the current inspection signal generation time, and obtain the usage time VS1 of the cutting tool; S6-102: Use a wear detection instrument to detect the cutting tool and convert the detected data into numerical values. The numerical values ​​include the tip radius, the cutting edge length, and the total length of the tool. Compare these values ​​with the original values ​​of the cutting tool of this model, calculate the differences between the detected values ​​and the original values, and sum them up as the wear difference value VS2 of the cutting tool. S6-103: Measure the runout of the cutting tool, record the runout data at each time point, and calculate the runout data at each time point using the standard deviation formula, which is used as the runout difference value VS3 of the cutting tool. S6-104: According to the formula The wear value SG of the cutting tool at the current time point is obtained by weighting the used time VS1, wear difference VS2, and runout difference VS3. , as well as These represent the preset maximum reference usage time, maximum reference wear difference, and maximum reference runout difference of the cutting tool of the panel saw, respectively; ty1, ty2, and ty3 are the preset weighting factors of the usage time VS1, wear difference VS2, and runout difference VS3, respectively.

[0011] In some embodiments, a control system for a printed circuit board manufacturing equipment includes: User module: Provides the interface for operators to interact with the system; Data processing module: Receives and processes data from scanning devices and sensors, and performs analysis and calculations; Comparison module: Compares the analysis and calculation results with the corresponding preset thresholds, and performs corresponding measures based on the comparison results; Equipment control module: controls the start, stop, and cutting process of the cutting machine; Communication module: Establishes communication with maintenance personnel's mobile terminals; Database: Stores the parameters required during the calculation and analysis process.

[0012] Compared with the prior art, the beneficial effects of the present invention are: This invention utilizes an automated copper-clad laminate (CCL) scanning and image analysis process to screen out qualified batches that meet cutting standards, reducing the time and labor required for manual inspection. Simultaneously, after each qualified batch of CCLs is cut, the cutting quality is analyzed to obtain a board quality evaluation index. Based on the comparison results of the current CCL board quality evaluation index, the operating status of the cutting machine and the usage status of the cutting tools are evaluated accordingly. This allows for timely troubleshooting when problems arise in the CCL cutting quality, ensuring the cutting quality of subsequent CCLs. This solves the problem of existing technologies requiring manual inspection of each CCL after cutting, which is time-consuming, labor-intensive, and impacts the progress of subsequent printed circuit board production. This invention selects the most suitable maintenance personnel by calculating the dimension rating based on the distance rating, sub-rating rating, and quantity rating of each pre-selected personnel within the screening range when generating maintenance signaling. This solves the problem that in the prior art, a maintenance personnel is usually randomly selected to go to the anomaly point for inspection. It cannot select maintenance personnel within the range based on the location of the current anomaly point, resulting in low intelligence and the anomaly not being resolved in a timely manner. Attached Figure Description

[0013] Further details, features, and advantages of this application are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which: Figure 1 This is a flowchart of the present invention; Figure 2 This is a schematic diagram of the principle of the present invention. Detailed Implementation

[0014] Several embodiments of this application will now be described in more detail with reference to the accompanying drawings to enable those skilled in the art to implement this application. This application may be embodied in many different forms and for various purposes and should not be limited to the embodiments set forth herein. These embodiments are provided to make this application thorough and complete, and to fully convey the scope of this application to those skilled in the art. The embodiments described do not limit this application.

[0015] Unless otherwise defined, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It will be further understood that terms such as those defined in commonly used dictionaries shall be interpreted as having a meaning consistent with their meaning in the relevant field and / or the context of this specification, and shall not be interpreted in an idealized or overly formal sense unless expressly defined herein. Example 1

[0016] Please see Figure 1 As shown, a control method for printed circuit board manufacturing equipment includes: S1: Place the copper-clad laminates of the current production batch in the designated target positions according to their serial numbers, and scan the copper-clad laminates placed at the designated target positions to obtain image and size information of the copper-clad laminates of the current production batch. Analyze the scanned image information; based on the analysis results, classify the current production batch of copper-clad laminates into qualified and unqualified batches; specifically: S1-101: Use image processing software to identify and mark defective areas in each group of image information, such as scratches, dents, and holes; segment the marked areas of each group of image information, extract the largest remaining complete area after segmentation, and use it as the normal area of ​​each copper-clad laminate in the current production batch; further obtain the size of the copper-clad laminate required for the current printed circuit board and compare it with the normal area of ​​each copper-clad laminate in the current production batch; if the normal area of ​​the copper-clad laminate is larger than the required size, and no defects affecting cutting are identified in the normal area; defects in image cutting, such as dents or holes in the middle of the normal area, are marked as qualified; otherwise, they are marked as unqualified. It should be noted that the automated copper-clad laminate scanning and image analysis process greatly reduces the time and labor required for manual inspection, thereby improving the production efficiency of printed circuit boards. By using image processing software to automatically identify and mark defective areas, potential problems can be identified more accurately, ensuring that only qualified copper-clad laminates are used in subsequent printed circuit board production processes. By comparing the normal area of ​​the copper clad laminate with the required size, we can ensure the maximum utilization of materials and reduce material waste caused by defects.

[0017] S2: After screening the unqualified batches based on step S1, the qualified batches are taken as the processing batches for the current printed circuit board production. The size of the copper-clad laminate required for the current printed circuit board is input. Based on the marking information and required size of each copper-clad laminate in the processing batch, the optimal cutting path of each copper-clad laminate in the processing batch is automatically generated. The optimal cutting path generated for each copper-clad laminate in the processing batch is then confirmed by the administrator. S3: After confirmation, the cutting tool of the cutting machine is controlled to cut along the optimal cutting path of each copper-clad laminate in the processing batch according to the preset cutting parameters. The operating status of the cutting machine is recorded while each copper-clad laminate in the processing batch is being cut. After each copper-clad laminate in the processing batch is cut, the cutting tool automatically stops and a completion signal is issued. The cutting quality of the currently cut copper-clad laminate is analyzed to obtain the board quality evaluation index (BZP) of the currently cut copper-clad laminate; specifically: S3-101: After issuing the complete signal, move the cut copper-clad laminate to the detection position. First, measure the dimensions of the cut copper-clad laminate and compare them with the required dimensions. If there is an error between the dimensions of the cut copper-clad laminate and the required dimensions, further compare the error range with the preset error allowable threshold. When the error range is greater than the preset error allowable threshold, directly generate an abnormal signal. When the error range is less than the preset error allowable threshold, analyze the cutting quality of the cut copper-clad laminate in step S3-102. S3-102: Adjust the wavelength and power of the laser scanner, emit a thin laser beam towards the cut surface of the copper-clad laminate and capture the reflected laser, establish a three-dimensional surface model of the cut surface of the copper-clad laminate based on the captured laser; convert the captured reflected signal into an electrical signal, and convert these signals into digital data through a data acquisition card; By establishing a three-dimensional model, the average roughness, maximum roughness depth, maximum height of the roughness profile, and total height of the roughness profile of the cut surface of the copper-clad laminate are obtained. A specific algorithm, such as the algorithm in the ISO standard, is used to obtain these parameters. The average roughness, maximum roughness depth, maximum height of the roughness profile, and total height of the roughness profile of the cut copper-clad laminate are multiplied by the corresponding preset weight coefficients and then summed to obtain the board quality evaluation index BZP of the current cut copper-clad laminate. It should be noted that the cutting tool automatically stops and sends a completion signal after the cutting is completed, and the cut copper-clad board is analyzed in real time to reflect the current working status of the cutting machine and ensure the quality of subsequent cutting work.

[0018] S4: Compare the current copper-clad laminate quality evaluation index (BZP) with the preset machine quality reference threshold index. If it is less than the preset machine quality reference threshold index, no signal is generated, and the next batch of copper-clad laminates is cut. If it is greater than the preset machine quality reference threshold index, an abnormal signal is generated, the cutting machine stops cutting, and the operating status of the cutting machine corresponding to the current copper-clad laminate is analyzed to obtain the operating evaluation index (YXP) of the cutting machine during the cutting process of the current copper-clad laminate. Specifically: S4-101: Obtain the number of vibrations of the cutting machine during the recorded time period from the recorded operating status of the cutting machine and record it as ZD1; S4-102: Obtain the cutting speed values ​​of the cutting tool of the panel saw at each time point within the recorded time period. Extract the maximum and minimum cutting speed values ​​from the cutting speed values ​​at each time point and calculate the difference between them. Use the difference as the cutting speed difference value within the recorded time period. Further calculate the cutting speed values ​​at each time point using the standard deviation formula, and use the calculation result as the cutting speed variation value within the recorded time period. Preset the weighting coefficients corresponding to the cutting speed difference value and the cutting speed variation value. Multiply the cutting speed difference value and the cutting speed variation value by the corresponding weighting coefficients and then sum them to obtain the estimated cutting speed ZD2 of the panel saw within the recorded time period. S4-103: Obtain the temperature and dust concentration values ​​of the surrounding environment of the cutting machine at each time point within the recorded time period; calculate the average temperature and dust concentration values ​​of the surrounding environment of the cutting machine at each time point to obtain the average temperature value and the average dust value; preset the weighting coefficients corresponding to the average temperature value and the average dust value; multiply the average temperature value and the average dust value by the corresponding weighting coefficients respectively and then sum them to obtain the environmental condition value ZD3 of the surrounding environment of the cutting machine within the recorded time period; S4-104: According to the formula The operating evaluation index YXP of the cutting machine during the current copper-clad laminate cutting process is obtained by weighting the vibration number ZD1, the cutting speed estimate ZD2, and the mirror value ZD3; where , as well as These represent the maximum allowable vibration frequency ZD1, the maximum allowable cutting speed estimate ZD2, and the maximum allowable mirror image value preset for the cutting machine, respectively; fq1, fq2, and fq3 are the preset weighting factors for the vibration frequency ZD1, the cutting speed estimate ZD2, and the mirror image value ZD3, respectively, and their values ​​are set to 1.137, 1.146, and 1.132, respectively. It should be noted that by analyzing parameters such as the vibration frequency of the cutting machine, changes in cutting speed, ambient temperature, and dust concentration, a comprehensive operational evaluation index (YXP) can be obtained, thus more accurately identifying the problem. Furthermore, when the board quality evaluation index (BZP) exceeds the preset threshold, the system generates an abnormal signal and stops the cutting operation, which helps prevent quality loss in subsequent copper-clad laminate cutting and damage to the cutting machine.

[0019] S5: Compare the operating evaluation index YXP of the cutting machine during the current cutting of copper-clad laminate with the preset operating reference threshold index. If it is greater than the preset operating reference threshold index, a maintenance signal is generated. The maintenance personnel with the highest maintenance evaluation value WP at the current maintenance signal generation time point are selected to go to the location of the cutting machine for inspection and maintenance. If it is less than the preset operating reference threshold index, an inspection signal is generated. The specific steps to obtain the maintenance assessment value (WP) for each maintenance personnel are as follows: S5-101: Based on the current time point of the maintenance signal generation, draw a circle with the cutting machine as the center and the distance as the radius, obtain each maintenance personnel within the circle as pre-selected personnel, and send a location acquisition instruction to their mobile terminals. After each pre-selected personnel confirms the received location acquisition instruction, calculate the route distance between each pre-selected personnel and the cutting machine, which is used as the distance rating JP1 of each pre-selected personnel; the unit is km. The shorter the route distance, the faster maintenance personnel can reach the site for maintenance, avoiding excessive delays that could affect production efficiency. S5-102: Obtain the total number of maintenance sessions and the duration of each maintenance session for each pre-selected personnel; the maintenance duration is calculated from the arrival at the fault point of the cutting machine and ends when the fault is resolved; calculate the average duration of each maintenance session for each pre-selected personnel, and use the calculated average of each group as the reference duration for each single maintenance session for each pre-selected personnel; match the total number of maintenance sessions and the reference duration for each single maintenance session for each pre-selected personnel with the preset reference ranges for the total number of maintenance sessions and the reference duration, and set each reference range for the total number of maintenance sessions and the reference duration to correspond to an experience score and a proficiency score, respectively; the range of proficiency score and experience score is between 1 and 10, and is a positive integer; obtain the experience score and proficiency score for each pre-selected personnel at the current generation time point, accumulate the experience score and proficiency score for each pre-selected personnel, and use the accumulated value as the score JP2 for each pre-selected personnel; The higher the experience score and proficiency score, the higher the maintenance efficiency and experience of the person. S5-103: Calculate the total number of selections for each pre-selected person in the past thirty days corresponding to the current generation time, and use it as the quantitative evaluation value JP3 for each pre-selected person; A higher total number of selections in the past 30 days indicates that the person has a heavier workload and needs rest. S5-104: According to the formula The distance rating JP1, sub-rating JP2, and quantitative rating JP3 of each candidate are weighted and calculated to obtain the dimension rating WP of each candidate; where af1, af2, and af3 are the preset weighting factors of the distance rating JP1, sub-rating JP2, and quantitative rating JP3 of each candidate, and their values ​​are set to 1.257, 1.294, and 1.243, respectively. It should be noted that when the operation evaluation index YXP exceeds the preset operation reference threshold index, the system automatically generates maintenance signaling to ensure timely response to potential equipment problems and reduce the impact of equipment failure on subsequent printed circuit board production. Based on the distance, experience and workload of each person within the screening range, the maintenance evaluation value WP is calculated to select the most suitable maintenance personnel, thereby further improving maintenance efficiency and production continuity.

[0020] S6: When an inspection signal is generated, the usage status of the cutting tool of the cutting machine at the current inspection signal generation time is analyzed to obtain the damage estimate SG of the cutting tool at the current time. The damage estimate SG of the cutting tool at the current time is compared with the preset damage estimate threshold. If it is greater than the preset damage estimate threshold, the maintenance personnel closest to the cutting machine at the current generation time are selected to go to the location of the cutting machine to replace the cutting tool. If it is less than the preset damage estimate threshold, a normal use signal is generated and the cutting machine is started to continue cutting the next set of copper-clad laminates. It should be noted that, based on steps S5-S6, if a normal use signal is generated, the next group of copper-clad laminates will continue to be cut. If the board quality evaluation index BZP of the next group of copper-clad laminates is still greater than the preset machine quality reference threshold index, and a normal use signal is still generated based on steps S5-S6, a maintenance signal will be directly generated, and the maintenance personnel with the highest maintenance evaluation value WP will be selected to go to the location of the cutting machine for inspection.

[0021] The specific steps to obtain the estimated loss SG of the cutting tool of the panel saw at the current time point are as follows: S6-101: Obtain the installation time of the cutting tool of the panel saw, calculate the time difference between the two based on the current inspection signal generation time, and obtain the usage time VS1 of the cutting tool; S6-102: Use wear detection instruments to detect cutting tools, such as tool wear measuring instruments; convert the detected data into numerical values, including the tip radius, cutting edge length and total tool length; compare them with the original values ​​of the cutting tool of this model, calculate the differences between the detected values ​​and the original values, and sum them up as the wear difference value VS2 of the cutting tool. S6-103: Measure the runout of the cutting tool; specifically, rotate the cutting tool to its operating speed, align the measuring instrument with the tool, record the runout data measured at each time point, and calculate the runout data measured at each time point using the standard deviation formula, which is taken as the runout difference value VS3 of the cutting tool. S6-104: According to the formula The wear value SG of the cutting tool at the current time point is obtained by weighting the used time VS1, wear difference VS2, and runout difference VS3. , as well as These represent the preset maximum reference usage time, maximum reference wear difference, and maximum reference runout difference of the cutting tool of the panel saw, respectively; ty1, ty2, and ty3 are the preset weighting factors of the usage time VS1, wear difference VS2, and runout difference VS3, respectively, and their values ​​are set to 1.384, 1.407, and 1.403, respectively. It should be noted that the damage estimate SG obtained through analysis can reflect the usage status of the cutting tool, avoiding abnormal tool wear from affecting the cutting quality of copper-clad laminates. At the same time, when the damage estimate SG exceeds the preset damage estimate threshold, the nearest maintenance personnel will be immediately selected to replace the tool, thereby avoiding processing quality problems caused by excessive tool wear. When the tool wear does not exceed the threshold, a normal use signal will be generated, allowing the cutting machine to continue processing, thereby reducing unnecessary downtime and improving production efficiency.

[0022] Example 2 Please see Figure 2 As shown, based on the control method for printed circuit board production equipment provided in Embodiment 1 of this application, Embodiment 2 of this application proposes a control system for printed circuit board production equipment. Embodiment 2 is merely a preferred embodiment of Embodiment 1, and the implementation of Embodiment 2 will not affect the individual implementation of Embodiment 1.

[0023] Specifically, the control system for a printed circuit board production equipment provided in Embodiment 2 of this application differs in that it includes a user module, a data processing module, a comparison module, an equipment control module, a communication module, and a database. The user module provides an interface for operators to interact with the system; it allows input of information such as the size of the copper-clad laminate and the cutting path; and displays the analysis results. The data processing module is used to receive, process, analyze, and calculate data from the scanning device and sensors; The comparison module is used to compare the results of analysis and calculation with the corresponding preset thresholds, and to take appropriate measures based on the comparison results. The equipment control module is used to control the start-up, stop, and cutting process of the cutting machine; and to control other testing equipment. The communication module is used to establish communication with the mobile terminal of maintenance personnel; Databases are used to store parameters required during calculations and analysis.

[0024] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A control method for printed circuit board manufacturing equipment, characterized in that, include: S1: Place the copper-clad laminates of the current production batch in the designated target position according to the order of their numbers, and scan the copper-clad laminates placed at the designated target position to obtain the image information and size information of the copper-clad laminates of the current production batch. Use image processing software to identify and mark the defective areas in each group of image information. The marked areas of each group of image information are segmented, and the largest remaining complete area after segmentation of each group of image information is extracted as the normal area of ​​each copper-clad laminate in the current production batch. The size of the copper-clad laminate required for the current printed circuit board is further obtained and compared with the normal area of ​​each copper-clad laminate in the current production batch. If the normal area of ​​the copper-clad laminate is larger than the required size and no defects affecting cutting are identified in the normal area. The copper-clad laminate is marked as qualified, and otherwise marked as unqualified; based on the analysis results, the current batch of copper-clad laminates is divided into qualified batches and unqualified batches; S2: After screening the unqualified batches based on step S1, the qualified batches are taken as the processing batches for the current printed circuit board production. The size of the copper-clad laminate required for the current printed circuit board is input. Based on the marking information and required size of each copper-clad laminate in the processing batch, the optimal cutting path of each copper-clad laminate in the processing batch is automatically generated. The optimal cutting path generated for each copper-clad laminate in the processing batch is then confirmed by the administrator. S3: After confirming that there are no errors, the cutting tool of the cutting machine is controlled to cut along the optimal cutting path of each copper-clad laminate in the processing batch through the preset cutting parameters. The running status of the cutting machine is recorded while each copper-clad laminate in the processing batch is being cut. After each copper-clad laminate in the processing batch is cut, the cutting tool is automatically stopped and a completion signal is issued. The cutting quality of the current copper-clad laminate is analyzed to obtain the board quality evaluation index BZP of the current copper-clad laminate. S4: Compare the current copper clad laminate quality evaluation index BZP with the preset machine quality reference threshold index. If it is less than the preset machine quality reference threshold index, no signal is generated, and the next group of copper clad laminates is cut. If it is greater than the preset machine quality reference threshold index, an abnormal signal is generated, the cutting machine is stopped, and the operating status of the cutting machine corresponding to the current copper clad laminate is analyzed to obtain the operating evaluation index YXP of the cutting machine during the cutting process of the current copper clad laminate. S5: Compare the operating evaluation index YXP of the cutting machine during the current cutting of copper-clad laminate with the preset operating reference threshold index. If it is greater than the preset operating reference threshold index, a maintenance signal is generated. The maintenance personnel with the highest maintenance evaluation value WP at the current maintenance signal generation time point are selected to go to the location of the cutting machine for inspection and maintenance. If it is less than the preset operating reference threshold index, an inspection signal is generated. S6: When an inspection signal is generated, the usage status of the cutting tool of the cutting machine at the current inspection signal generation time is analyzed to obtain the damage estimate SG of the cutting tool at the current time. The damage estimate SG of the cutting tool at the current time is compared with the preset damage estimate threshold. If it is greater than the preset damage estimate threshold, the maintenance personnel closest to the cutting machine at the current generation time are selected to go to the location of the cutting machine to replace the cutting tool. If it is less than the preset damage estimate threshold, a normal use signal is generated, and the cutting machine is started to continue cutting the next set of copper-clad laminates.

2. The control method for a printed circuit board production equipment according to claim 1, characterized in that, The specific steps to obtain the board quality assessment index (BZP) of the current cut copper-clad laminate are as follows: S3-101: After issuing the complete signal, move the cut copper-clad laminate to the detection position. First, measure the dimensions of the cut copper-clad laminate and compare them with the required dimensions. If there is an error between the dimensions of the cut copper-clad laminate and the required dimensions, further compare the error range with the preset error allowable threshold. When the error range is greater than the preset error allowable threshold, directly generate an abnormal signal. When the error range is less than the preset error allowable threshold, analyze the cutting quality of the cut copper-clad laminate in step S3-102. S3-102: Adjust the wavelength and power of the laser scanner, emit a thin laser beam towards the cut surface of the copper-clad laminate and capture the reflected laser, and build a three-dimensional surface model of the cut surface of the copper-clad laminate based on the captured laser. By establishing a three-dimensional model, the average roughness, maximum roughness depth, maximum height of the roughness profile, and total height of the roughness profile of the cut surface of the copper-clad laminate are obtained. The average roughness, maximum roughness depth, maximum height of the roughness profile, and total height of the roughness profile of the cut copper-clad laminate are multiplied by the corresponding preset weight coefficients and then summed to obtain the board quality evaluation index BZP of the cut copper-clad laminate.

3. The control method for printed circuit board production equipment according to claim 2, characterized in that, The specific steps to obtain the operating evaluation index YXP of the cutting machine during the current copper-clad laminate cutting process are as follows: S4-101: Obtain the number of vibrations of the cutting machine during the recorded time period from the recorded operating status of the cutting machine and record it as ZD1; S4-102: Obtain the cutting speed values ​​of the cutting tool of the panel saw at each time point within the recorded time period. Extract the maximum and minimum cutting speed values ​​from the cutting speed values ​​at each time point and calculate the difference between them. Use the difference as the cutting speed difference value within the recorded time period. Further calculate the cutting speed values ​​at each time point using the standard deviation formula, and use the calculation result as the cutting speed variation value within the recorded time period. Preset the weighting coefficients corresponding to the cutting speed difference value and the cutting speed variation value. Multiply the cutting speed difference value and the cutting speed variation value by the corresponding weighting coefficients and then sum them to obtain the estimated cutting speed ZD2 of the panel saw within the recorded time period. S4-103: Obtain the temperature and dust concentration values ​​of the surrounding environment of the cutting machine at each time point within the recorded time period; calculate the average temperature and dust concentration values ​​of the surrounding environment of the cutting machine at each time point to obtain the average temperature value and the average dust value; preset the weighting coefficients corresponding to the average temperature value and the average dust value; multiply the average temperature value and the average dust value by the corresponding weighting coefficients respectively and then sum them to obtain the environmental condition value ZD3 of the surrounding environment of the cutting machine within the recorded time period; S4-104: According to the formula The operating evaluation index YXP of the cutting machine during the current copper-clad laminate cutting process is obtained by weighting the vibration number ZD1, the cutting speed estimate ZD2, and the mirror value ZD3; where , as well as These represent the maximum allowed vibration frequency, maximum allowed cutting speed estimate, and maximum allowed mirror value preset for the cutting machine, respectively; fq1, fq2, and fq3 are the preset weighting factors for vibration frequency ZD1, cutting speed estimate ZD2, and mirror value ZD3, respectively.

4. The control method for a printed circuit board production equipment according to claim 3, characterized in that, The specific steps to obtain the maintenance assessment value (WP) for each maintenance personnel are as follows: S5-101: Based on the current time point of generating the maintenance signal, draw a circle with the cutting machine as the center and the distance as the radius, obtain each maintenance personnel within the circle as pre-selected personnel, and send a location acquisition instruction to their mobile terminals. After each pre-selected personnel confirms the received location acquisition instruction, calculate the route distance between each pre-selected personnel and the cutting machine, and use it as the distance evaluation value JP1 of each pre-selected personnel. S5-102: Obtain the total number of maintenance sessions and the duration of each maintenance session for each pre-selected personnel; calculate the average duration of each maintenance session for each pre-selected personnel, and use the calculated average duration of each group as the reference duration of each single maintenance session for each pre-selected personnel; The total number of maintenance attempts and the reference duration for each maintenance attempt of each pre-selected personnel are matched with the preset reference ranges for total number of maintenance attempts and reference durations, respectively. Each reference range for total number of maintenance attempts and each reference duration range is set to correspond to an experience score and a proficiency score, respectively. Obtain the experience score and proficiency score of each candidate at the current generation time. Add up the experience score and proficiency score of each candidate and use the sum as the score JP2 of each candidate. S5-103: Calculate the total number of selections for each pre-selected person in the past thirty days corresponding to the current generation time, and use it as the quantitative evaluation value JP3 for each pre-selected person; S5-104: According to the formula The distance rating JP1, sub-rating JP2, and quantitative rating JP3 of each pre-selected person are weighted and calculated to obtain the dimension rating WP of each pre-selected person; where af1, af2, and af3 are the preset weighting factors of the distance rating JP1, sub-rating JP2, and quantitative rating JP3 of each pre-selected person, respectively.

5. The control method for a printed circuit board production equipment according to claim 4, characterized in that, The specific steps to obtain the estimated loss SG of the cutting tool of the panel saw at the current time point are as follows: S6-101: Obtain the installation time of the cutting tool of the panel saw, calculate the time difference between the two based on the current inspection signal generation time, and obtain the usage time VS1 of the cutting tool; S6-102: Use a wear detection instrument to detect the cutting tool and convert the detected data into numerical values. The numerical values ​​include the tip radius, the cutting edge length, and the total length of the tool. Compare these values ​​with the original values ​​of the cutting tool of this model, calculate the differences between the detected values ​​and the original values, and sum them up as the wear difference value VS2 of the cutting tool. S6-103: Measure the runout of the cutting tool, record the runout data at each time point, and calculate the runout data at each time point using the standard deviation formula, which is used as the runout difference value VS3 of the cutting tool. S6-104: According to the formula The wear value SG of the cutting tool at the current time point is obtained by weighting the used time VS1, wear difference VS2, and runout difference VS3. , as well as These represent the preset maximum reference usage time, maximum reference wear difference, and maximum reference runout difference of the cutting tool of the panel saw, respectively; ty1, ty2, and ty3 are the preset weighting factors of the usage time VS1, wear difference VS2, and runout difference VS3, respectively.

6. A control system for a printed circuit board (PCB) manufacturing equipment, applied to the control method of the PCB manufacturing equipment according to any one of claims 1 to 5, characterized in that, include: User module: Provides the interface for operators to interact with the system; Data processing module: Receives and processes data from scanning devices and sensors, and performs analysis and calculations; Comparison module: Compares the analysis and calculation results with the corresponding preset thresholds, and performs corresponding measures based on the comparison results; Equipment control module: controls the start, stop, and cutting process of the cutting machine; Communication module: Establishes communication with maintenance personnel's mobile terminals; Database: Stores the parameters required during the calculation and analysis process.

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