Cable CAPP process design and management method

Abstract

The invention discloses a cable CAPP process design and management method, and relates to the technical field of cable production. According to the method, after cable specification and performance requirement data are input, the data are classified according to a continuous type and a discrete type, discrete type data are coded and quantized and then matched with discrete type data of process schemes in a database, to-be-selected schemes are screened out, actual numerical values of the continuous type data serve as evaluation values, and process similarity indexes are obtained through analysis and calculation; processing the process similarity index, if the process similarity index is lower than a preset similarity threshold index, screening out a high-similarity scheme, and determining a production process scheme according to the similarity difference and the application performance value; in the whole process, manual intervention is reduced, data calculation and multiple rounds of screening are utilized, the optimal process scheme with the high matching degree is scientifically selected, and the problem that in the prior art, historical data cannot be combined, and the accuracy of the process scheme is improved is solved. And a better process scheme with a high matching degree is scientifically selected.

Description

Technical Field

[0001] The present invention relates to the technical field of cable production, and in particular to a cable CAPP process design and management method. Background Art

[0002] As market competition continues to intensify, customers' demands for cable products are becoming increasingly diversified, and their requirements for product quality and delivery cycle are becoming more stringent.

[0003] However, the existing technology still has the following deficiencies in process design and management methods in the cable production process: Cable process design relies heavily on manual experience. Designers need to rely on their personal accumulated knowledge and past project experience to plan process solutions, which makes process design efficiency extremely low. When faced with urgent orders or diversified product demands, companies often find it difficult to respond quickly and are unable to combine historical data to scientifically select a process solution with a high degree of matching and better performance. In addition, it is not possible to comprehensively evaluate the production performance of cables during the production process of applying process solutions, thereby providing a basis for optimizing process solutions, and the level of intelligent management is low.

[0004] Therefore, a cable CAPP process design and management method is introduced. Summary of the invention

[0005] The purpose of the present invention is to solve the problems mentioned in the background technology and to propose a cable CAPP process design and management method.

[0006] The object of the present invention can be achieved by the following technical solution: A cable CAPP process design and management method, comprising: S1: Input specification data and performance requirement data of the currently required production cables into the database, and classify the specification data and performance requirement data into continuous data and discrete data; S2: After classification, the application process solutions of each group in the library are matched, and the successfully matched application process solutions are used as candidate solutions; S3: Take each group of data in the continuous data as the evaluation value, each group of evaluation values ​​in the specification data is represented by Tq, and each group of evaluation values ​​in the performance requirement data is represented by Re; substitute the evaluation values ​​Tq and Re into the formula Calculation is performed to obtain the specification matching value P1 and the performance matching value P2 of each group of candidate solutions; Zq and Fe represent the evaluation values ​​of each group of historical specification data and each group of historical performance requirement data corresponding to each group of candidate solutions, respectively; q is the number of each group of evaluation values ​​in the specification data, q=1,2,...,u, u is the total number; e is the number of each group of evaluation values ​​in the performance requirement data, e=1,2,...,y, y is the total number; S4: multiplying the specification matching value P1 and the performance matching value P2 by the corresponding preset weight coefficients respectively, and then summing them up to obtain the process similarity index P3 of each group of candidate solutions; S5: Compare the process similarity index P3 of each group of candidate solutions with a preset similarity threshold index, retain the candidate solutions with an index lower than the similarity threshold index, and select the one with the smallest process similarity index P3 as the production process solution.

[0007] As a preferred implementation of the present invention, the classification is followed by matching with each group of application process solutions in the library, and the successfully matched application process solutions are used as candidate solutions, specifically: For the discrete data in the specification data and performance requirement data, the coding method is used for quantification, and each group of data in the discrete data is set to correspond to a code; If the discrete data codes in a certain set of application process solutions are the same as the discrete data codes of the cables currently required to be produced, it is determined that the match is successful, and the application process solution that is successfully matched is used as a candidate solution.

[0008] As a preferred embodiment of the present invention, the process similarity index P3 of each group of candidate solutions is compared with a preset similarity threshold index, the candidate solutions with a similarity index lower than the similarity threshold index are retained, and the one with the smallest process similarity index P3 is selected as the production process solution, including: The process similarity index P3 of each group of candidate solutions is compared with the preset similarity threshold index, and the candidate solutions with an index lower than the similarity threshold are retained as high-similarity solutions. The high-similarity solutions are sorted from small to large according to the size of the process similarity index P3. The first two groups of high-similarity solutions are selected from left to right and the corresponding process similarity index P3 is extracted to calculate the difference. The calculated difference is marked as the similarity difference. If the similarity difference is higher than the preset reference similarity difference, the high-similarity solution with a smaller process similarity index P3 is selected as the production process solution for the current production cable; If the similarity difference is lower than the preset reference similarity difference, the application performance values ​​of the two groups of high similarity solutions are analyzed; and the high similarity solution with a higher application performance value is selected as the production process solution for the current production cable.

[0009] As a preferred implementation of the present invention, the application performance values ​​of two groups of highly similar solutions are analyzed, specifically: The historical application times of two groups of highly similar solutions and the number of unqualified cables generated in each application process are extracted from the database; the proportion of the number of unqualified cables in each application process in the two groups of highly similar solutions in the total production quantity is calculated, recorded as the unqualified proportion, and the average of the unqualified proportions in each application process is taken, recorded as the unqualified average ratio; Preset the intervals of the number of times in each group and the intervals of the ratios in each group corresponding to the number of historical applications and the average ratio of unqualified applications, and set a familiarity score and a quality score to correspond to the interval of the number of times in each group and the interval of the ratio in each group; The historical application times and unqualified ratios of the two groups of highly similar solutions are converted into familiarity scores and quality scores respectively. After the conversion is completed, they are multiplied with the corresponding preset weight coefficients, and then the sum is obtained to obtain the application performance values ​​of the two groups of highly similar solutions.

[0010] As a preferred embodiment of the present invention, if the process similarity index P3 of each group of candidate solutions is higher than the similarity threshold index, the candidate solution with the smallest process similarity index P3 is selected as the initial solution, and the initial solution is sent to the technician. After the technician receives the initial solution and makes adjustments, the initial solution adjusted by the technician is used as the production process solution for the current required production cable, and is sent to the database for updating.

[0011] As a preferred embodiment of the present invention, it also includes: Production collaboration: The determined production process plan is delivered to the corresponding production workshop for cable production. After production is completed, the quality results of the cables are obtained by scanning the pre-established labels. The quality results are divided into excellent, qualified and unqualified. Quality management: Based on the quality results of the currently required production cables, execute the corresponding steps to generate a comprehensive performance report of the currently required production cables in the application of the production process solution.

[0012] As a preferred implementation of the present invention, based on the quality result of the currently required produced cable, corresponding steps are performed, specifically: Obtain the quality results of the cables currently required to be produced, classify each produced cable according to different quality results, and obtain the number of excellent cables, qualified cables, and unqualified cables; Calculate the proportion of excellent cables, qualified cables and unqualified cables in the total production quantity respectively, and obtain the excellent process ratio, qualified process ratio and poor process ratio, which are recorded as sa, sb and sc; According to the formula Perform weighted calculation to obtain the quality evaluation index G of the currently required production cable in the application production process scheme, where They are the influencing weight factors of excellent process ratio sa, qualified process ratio sb and poor process ratio sc respectively.

[0013] As a preferred implementation of the present invention, a comprehensive performance report of the currently required production cable in the application of the production process solution is generated, specifically: Match the quality assessment index G with three preset index value ranges, each index value range corresponds to a production performance level; the production performance levels include poor performance level, general performance level and excellent performance level; If the production performance level is an excellent performance level, the excellent performance level and the quality assessment index G are filled into the pre-set report template as a comprehensive performance report of the currently required production cable in the application of the production process solution.

[0014] As a preferred embodiment of the present invention, generating a comprehensive performance report of the currently required production cable in the application of the production process solution also includes: If the production performance level is a poor performance level or a general performance level, the equipment data in the application process plan and the actual equipment production data in the production workshop are extracted for matching. If the matching result shows that there is a failure in the matching of group E data, it is determined that the reason for the poor performance level or the general performance level of the production performance level is abnormal equipment in the production workshop; E is a preset data threshold; if the matching result shows that the matching is successful or the matching failure data is lower than E, it is determined that the reason for the poor performance level or the general performance level of the production performance level is a defect in the application of the production process plan; The poor performance level or general performance level, the quality assessment index G and the reasons leading to the poor performance level or general performance level of the production are filled into the pre-set report template as a comprehensive performance report of the currently required production cable in the application of the production process solution.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. After inputting the cable specification and performance requirement data, the present invention classifies them into continuous and discrete types, encodes and quantizes the discrete data, matches them with the discrete data of the process scheme in the database, and screens out the selected schemes. The actual value of the continuous data is used as the evaluation value, and is substituted into the formula to calculate the specification matching value and the performance matching value, thereby obtaining the process similarity index. The process similarity index is processed. If it is lower than the preset similarity threshold index, a high similarity scheme is screened out, and the production process scheme is determined according to the similarity difference and the application performance value; if both are higher than the threshold index, the minimum index scheme is selected and the scheme is determined after adjustment by the technician. The whole process reduces manual intervention, uses data calculation and multiple rounds of screening, and scientifically selects a process scheme with a high matching degree and a better quality, thereby solving the problem that the prior art cannot scientifically select a process scheme with a high matching degree and a better quality by combining historical data; 2. The present invention obtains the cable quality results after production is completed, classifies and counts the number of excellent, qualified and unqualified cables, calculates the process excellent ratio, qualified ratio and poor ratio, and obtains the quality evaluation index according to the weighted formula, which will be matched with the preset index range to determine the production performance level. If the level does not reach excellent, the equipment data in the application process plan and the actual equipment production data in the production workshop are compared to determine whether the problem is caused by equipment abnormality or process plan defects, and generate a comprehensive performance report. This report comprehensively presents the quality results of the process plan in actual production, and provides data support and direction guidance for process plan optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0017] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0018] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] See also Figure 1 As shown, a cable CAPP process design and management method includes: Process design: Input the specification data and performance requirement data of the currently required production cables into the pre-built database; specification data such as the number of wire cores, wire diameter, cable outer diameter, etc., performance requirement data such as electrical performance (rated voltage, insulation resistance, dielectric constant, etc.), mechanical properties (tensile strength, bending performance, etc.) and environmental resistance (temperature resistance, moisture resistance, acid and alkali resistance, etc.); the database stores each group of application process plans, and each group of application process plans corresponds to different historical specification data and historical performance requirement data; the database conducts a similarity assessment on the specification data and performance requirement data of the currently required production cables and the historical specification data and historical performance requirement data pre-stored in the database, and executes corresponding steps according to the results of the similarity assessment to determine the production process plan for the currently required production cables; It should be noted that various types of process knowledge, experience data and actual production data in the cable production process are collected to construct the corresponding production process plan, and these data are stored in a structured form in the database to establish a complete cable process database.

[0020] Specifically: Step 1: Classify the specification data and performance requirement data of the cables currently required for production into continuous data and discrete data; continuous data include wire diameter and insulation resistance, and discrete data include conductor material, insulation material type, etc.; for the discrete data in the specification data and performance requirement data, quantify them by coding, and set each group of data in the discrete data to correspond to a code; for example, copper is 1, aluminum is 2; polyethylene insulation is 3, polyvinyl chloride insulation is 4, etc.; After the classification is completed, the discrete data in the specification data and performance requirement data are extracted and matched with the discrete data of each group of application process solutions in the database. If the discrete data code in a group of application process solutions is the same as the discrete data code of the currently required production cable, it is determined to be a successful match, and the successfully matched application process solution is used as a candidate solution; Step 2: For the continuous data in the current required production cable specification data and performance requirement data, the specific values ​​of each group of data in the continuous data are used as evaluation values, and each group of evaluation values ​​in the specification data is represented by Tq; where q represents the number of each group of evaluation values ​​in the specification data, q=1,2,...,u, and u is the total number of evaluation values ​​in the specification data; Each group of evaluation values ​​in the performance requirement data is represented by Re; wherein e represents the number of each group of evaluation values ​​in the performance requirement data, e=1,2,...,y, y is the total number of evaluation values ​​in the specification data; Step 3: Substitute the estimated values ​​Tq and Re of the current required production cable specification data and performance requirement data into the formula Calculation is performed to obtain the specification matching value P1 and the performance matching value P2 corresponding to each group of candidate solutions; wherein Zq and Fe represent the evaluation values ​​of each group of historical specification data and each group of historical performance requirement data corresponding to each group of candidate solutions, respectively; Step 4: Multiply the specification matching value P1 and the performance matching value P2 of each group of candidate solutions by the corresponding preset weight coefficients respectively; the weight coefficient of the specification matching value P1 is higher than the weight coefficient of the performance matching value P2; then sum them up to obtain the process similarity index P3 of each group of candidate solutions; It should be noted that by encoding and matching discrete data, it is possible to quickly screen out candidate solutions that fully match discrete data from a large number of application process solutions in the database. For example, a quick comparison can be made on key discrete data such as conductor material and insulation material type, which greatly reduces the amount of data to be processed later, avoids comprehensive evaluation of all solutions, saves time and computing resources, and speeds up the process of determining the process solution. Continuous data directly uses measured values ​​as evaluation values, and calculates specification matching values, performance matching values ​​and process similarity index through formulas. The entire process is highly automated. This automated processing avoids the tedious manual evaluation and calculation, improves evaluation efficiency, and enables companies to respond to market demands more quickly, shortening the product design to production cycle.

[0021] The process similarity index P3 of each group of candidate solutions is compared with the preset similarity threshold index, and the candidate solutions with an index lower than the similarity threshold are retained as high-similarity solutions. The high-similarity solutions are sorted from small to large according to the size of the process similarity index P3. The first two groups of high-similarity solutions are selected from left to right and the corresponding process similarity index P3 is extracted to calculate the difference. The calculated difference is marked as the similarity difference. If the similarity difference is higher than the preset reference similarity difference, the high-similarity solution with a smaller process similarity index P3 is selected as the production process solution for the current production cable; If the similarity difference is lower than the preset reference similarity difference, the historical application times of the two groups of highly similar solutions and the number of unqualified cables generated in each application process are extracted from the database; the proportion of the number of unqualified cables in each application process in the two groups of highly similar solutions in the total production quantity is calculated, recorded as the unqualified proportion, and the average of the unqualified proportions of each application process is taken, recorded as the unqualified average ratio; The intervals of the number of times in each group and the intervals of the ratios in each group corresponding to the number of historical applications and the average ratio of unqualified results are preset, and each interval of the number of times in each group and each interval of the ratio in each group are set to correspond to a familiarity score and a quality score respectively; the familiarity score and the quality score range are both set to 1-10, the higher the number of historical applications, the higher the familiarity score of the corresponding match, and the lower the average ratio of unqualified results, the higher the quality score of the corresponding match; The historical application times and unqualified average ratios of the two groups of highly similar solutions are converted into familiarity scores and quality scores respectively. After the conversion is completed, they are multiplied by the corresponding preset weight coefficients, and then the application performance values ​​of the two groups of highly similar solutions are obtained by summing them up; the highly similar solution with the higher application performance value is selected as the production process solution for the current production of cables; the historical application times of the highly similar solution are increased by one; It should be noted that by comparing the process similarity index with the preset similarity threshold index and screening out highly similar solutions, it is possible to accurately locate solutions that have a high degree of match with current needs, avoid adopting solutions with too large differences, and ensure the stability of the production process; When the similarity difference is lower than the preset reference similarity difference, historical data such as the number of historical applications and the number of unqualified cables are introduced. By calculating the percentage and average of unqualified products, the quality performance of the solution in past production can be directly reflected; the number of historical applications and the average ratio of unqualified products are converted into familiarity scores and quality scores, which comprehensively considers the application proficiency and product quality of the solution, fully taps the value of historical data, and provides a more comprehensive basis for decision-making; Setting weights for the familiarity score and the quality score and calculating the application performance value balances the relationship between production proficiency and product quality. Selecting a solution with a higher application performance value helps improve production efficiency and reduce production delays caused by unfamiliar processes. At the same time, it ensures product quality and reduces the failure rate, thereby improving the company's production efficiency and enhancing its market competitiveness. The entire process goes through multiple rounds of screening and comprehensive evaluation, making the selection of process solutions more scientific. It not only takes into account the similarity between current cable parameters and historical solutions, but also combines historical application conditions to adapt to different production scenarios and needs.

[0022] Step 5: If the process similarity index P3 of each group of candidate solutions is higher than the similarity threshold index, the candidate solution with the smallest process similarity index P3 is selected as the initial solution, and the initial solution is sent to the technician. After the technician receives the initial solution and makes adjustments, the initial solution adjusted by the technician is used as the production process solution for the current production cable, and is sent to the database for updating; It should be noted that when the process similarity index P3 of all candidate solutions is higher than the similarity threshold index, it means that there is no solution that fully meets the ideal similarity level; at this time, the candidate solution with the smallest process similarity index P3 is selected as the initial solution, because it is the most different from the current demand and is most likely to need adjustment. Handing it over to the technicians for adjustment can give full play to the professional knowledge and experience of the technicians, and make targeted modifications to the solution according to the special specifications and performance requirements of the current cable production, so as to meet the unique needs that may exist in actual production, and ensure the flexibility and customizability of the production process solution; Sending the initial plan adjusted by the technicians to the database for updating can continuously enrich and improve the process plan content in the database; with the addition of new adjustment plans, the data in the database is more comprehensive and accurate, providing more reference and reference for subsequent process design; the next time a similar or related production demand is encountered, a more suitable plan can be found from the updated database to improve the efficiency and accuracy of process design.

[0023] Production collaboration: The production process plan determined by the current production cables is delivered to the corresponding production workshop, and the cables are produced according to the process plan. During the production process, a unique label is created for each cable, and the established label is used to store the entire process data and quality results from production and processing to finished product inspection. After production is completed, the quality results of the cables are obtained by scanning the labels, and the quality results are divided into excellent, qualified and unqualified. After the production is completed, professional workers are arranged to conduct a comprehensive inspection of the cables. According to the relevant quality standards and inspection specifications, the workers use appropriate inspection tools and methods to check the performance indicators of the cables one by one, and add the quality results of the cables to the labels according to the inspection results; Quality management: Based on the quality results of the currently required production cables, execute the corresponding steps to generate a comprehensive performance report of the currently required production cables in the application of the production process solution; Specifically: Step 1: Obtain the quality results of the cables currently required to be produced, classify each produced cable according to different quality results, and obtain the number of excellent cables, the number of qualified cables, and the number of unqualified cables; Calculate the proportion of excellent cables, qualified cables and unqualified cables in the total production quantity respectively, and obtain the excellent process ratio, qualified process ratio and poor process ratio, which are recorded as sa, sb and sc; According to the formula Perform weighted calculation to obtain the quality evaluation index G of the currently required production cable in the application production process scheme, where They are the influencing weight factors of excellent process ratio sa, qualified process ratio sb and poor process ratio sc respectively; Step 2: Match the quality assessment index G with the three preset index value ranges, each of which corresponds to a production performance level; the production performance levels include poor performance level, general performance level and excellent performance level; the higher the quality assessment index G, the higher the possibility of matching the excellent performance level; If the production performance level is an excellent performance level, the excellent performance level and the quality evaluation index G are filled into the pre-set report template as a comprehensive performance report of the currently required production cable in the application of the production process solution; Step 3: If the production performance level is a poor performance level or a general performance level, extract the equipment data in the application process plan and the actual equipment production data in the production workshop for matching. If the matching result shows that there is a failure in the matching of group E data, it is determined that the reason for the poor performance level or the general performance level of the production performance level is the abnormality of the production workshop equipment; E is the preset data threshold; if the matching result shows that the matching is successful or the matching failure data is lower than E, it is determined that the reason for the poor performance level or the general performance level of the production performance level is the defect of the application production process plan; Fill the poor performance level or average performance level, quality assessment index G and the reasons for the poor performance level or average performance level into the pre-set report template as a comprehensive performance report of the currently required production cable in the application of the production process solution; It should be noted that by carefully classifying the cable quality results, and deeply calculating the process excellent ratio, qualified ratio and poor ratio, and then accurately deriving the quality evaluation index G based on the weighted formula, the quality effect of the current production process scheme in actual production can be comprehensively, objectively and quantitatively evaluated; this evaluation method comprehensively considers the proportion of cables of different quality grades and their corresponding weights, avoids the one-sidedness of single-dimensional evaluation, and provides a scientific and reliable basis for the optimization of process schemes; When the production performance level does not reach excellent, by rigorously comparing the equipment data in the application process plan and the actual equipment production data in the production workshop, it is possible to accurately determine whether the problem stems from equipment abnormality or process plan defects; this precise problem location mechanism can effectively avoid blind troubleshooting, save time and resources, and improve the efficiency of problem solving.

[0024] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A cable CAPP process design and management method, characterized in that: include: S1: Input specification data and performance requirement data of the currently required production cables into the database, and classify the specification data and performance requirement data into continuous data and discrete data; S2: After classification, the application process solutions of each group in the library are matched, and the successfully matched application process solutions are used as candidate solutions; S3: Take each group of data in the continuous data as the evaluation value, each group of evaluation values ​​in the specification data is represented by Tq, and each group of evaluation values ​​in the performance requirement data is represented by Re; substitute the evaluation values ​​Tq and Re into the formula Calculation is performed to obtain the specification matching value P1 and the performance matching value P2 of each group of candidate solutions; Zq and Fe represent the evaluation values ​​of each group of historical specification data and each group of historical performance requirement data corresponding to each group of candidate solutions, respectively; q is the number of each group of evaluation values ​​in the specification data, q=1,2,...,u, u is the total number; e is the number of each group of evaluation values ​​in the performance requirement data, e=1,2,...,y, y is the total number; S4: multiplying the specification matching value P1 and the performance matching value P2 by the corresponding preset weight coefficients respectively, and then summing them up to obtain the process similarity index P3 of each group of candidate solutions; S5: Compare the process similarity index P3 of each group of candidate solutions with a preset similarity threshold index, retain the candidate solutions with an index lower than the similarity threshold index, and select the one with the smallest process similarity index P3 as the production process solution.

2. A cable CAPP process design and management method according to claim 1, characterized in that: After the classification, the application process solutions of each group in the library are matched, and the successfully matched application process solutions are used as the candidate solutions, which are specifically: For the discrete data in the specification data and performance requirement data, the coding method is used for quantification, and each group of data in the discrete data is set to correspond to a code; If the discrete data codes in a certain set of application process solutions are the same as the discrete data codes of the cables currently required to be produced, it is determined that the match is successful, and the application process solution that is successfully matched is used as a candidate solution.

3. A cable CAPP process design and management method according to claim 2, characterized in that: The process similarity index P3 of each group of candidate solutions is compared with a preset similarity threshold index, the candidate solutions with an index lower than the similarity threshold index are retained, and the solution with the smallest process similarity index P3 is selected as the production process solution, including: The process similarity index P3 of each group of candidate solutions is compared with the preset similarity threshold index, and the candidate solutions with a similarity index lower than the similarity threshold index are retained as high-similarity solutions. The high-similarity solutions are sorted from small to large according to the size of the process similarity index P3. The first two groups of high-similarity solutions are selected from left to right and the corresponding process similarity index P3 is extracted to calculate the difference. The calculated difference is marked as the similarity difference. If the similarity difference is higher than the preset reference similarity difference, the high-similarity solution with a smaller process similarity index P3 is selected as the production process solution for the current production cable; If the similarity difference is lower than the preset reference similarity difference, the application performance values ​​of the two groups of high similarity solutions are analyzed; and the high similarity solution with a higher application performance value is selected as the production process solution for the current production cable.

4. A cable CAPP process design and management method according to claim 3, characterized in that: Analyze the application performance values ​​of two groups of highly similar solutions, specifically: The historical application times of two groups of highly similar solutions and the number of unqualified cables generated in each application process are extracted from the database; the proportion of the number of unqualified cables in each application process in the two groups of highly similar solutions in the total production quantity is calculated, recorded as the unqualified proportion, and the average of the unqualified proportions in each application process is taken, recorded as the unqualified average ratio; Preset the intervals of the number of times in each group and the intervals of the ratios in each group corresponding to the number of historical applications and the average ratio of unqualified applications, and set a familiarity score and a quality score to correspond to the interval of the number of times in each group and the interval of the ratio in each group; The historical application times and unqualified ratios of the two groups of highly similar solutions are converted into familiarity scores and quality scores respectively. After the conversion is completed, they are multiplied with the corresponding preset weight coefficients, and then the sum is obtained to obtain the application performance values ​​of the two groups of highly similar solutions.

5. A cable CAPP process design and management method according to claim 4, characterized in that: If the process similarity index P3 of each group of candidate solutions is higher than the similarity threshold index, the candidate solution with the smallest process similarity index P3 is selected as the initial solution, and the initial solution is sent to the technician. After the technician receives the initial solution and makes adjustments, the initial solution adjusted by the technician is used as the production process solution for the current required cable production and is sent to the database for updating.

6. A cable CAPP process design and management method according to claim 5, characterized in that: Also includes: Production collaboration: The determined production process plan is delivered to the corresponding production workshop for cable production. After production is completed, the quality results of the cables are obtained by scanning the pre-established labels. The quality results are divided into excellent, qualified and unqualified. Quality management: Based on the quality results of the currently required production cables, execute the corresponding steps to generate a comprehensive performance report of the currently required production cables in the application of the production process solution.

7. A cable CAPP process design and management method according to claim 6, characterized in that: Based on the quality results of the cables currently required to be produced, perform the corresponding steps, specifically: Obtain the quality results of the cables currently required to be produced, classify each produced cable according to different quality results, and obtain the number of excellent cables, qualified cables, and unqualified cables; Calculate the proportion of excellent cables, qualified cables and unqualified cables in the total production quantity respectively, and obtain the excellent process ratio, qualified process ratio and poor process ratio, which are recorded as sa, sb and sc; According to the formula Perform weighted calculation to obtain the quality evaluation index G of the currently required production cable in the application production process scheme, where They are the influencing weight factors of excellent process ratio sa, qualified process ratio sb and poor process ratio sc respectively.

8. A cable CAPP process design and management method according to claim 7, characterized in that: Generate a comprehensive performance report of the currently required production cables in the application production process solution, specifically: Match the quality assessment index G with three preset index value ranges, each index value range corresponds to a production performance level; the production performance levels include poor performance level, general performance level and excellent performance level; If the production performance level is an excellent performance level, the excellent performance level and the quality assessment index G are filled into the pre-set report template as a comprehensive performance report of the currently required production cable in the application of the production process solution.

9. A cable CAPP process design and management method according to claim 8, characterized in that: Generate a comprehensive report on the performance of the current production cable in the application production process solution, including: If the production performance level is a poor performance level or a general performance level, the equipment data in the application process plan and the actual equipment production data in the production workshop are extracted for matching. If the matching result shows that there is a failure in the matching of group E data, it is determined that the reason for the poor performance level or the general performance level of the production performance is abnormal equipment in the production workshop; E is a preset data threshold; if the matching result shows that the matching is successful or the matching failure data is lower than E, it is determined that the reason for the poor performance level or the general performance level of the production performance is a defect in the application of the production process plan; The poor performance level or general performance level, the quality assessment index G and the reasons leading to the poor performance level or general performance level of the production are filled into the pre-set report template as a comprehensive performance report of the currently required production cable in the application of the production process solution.

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