Industrial intelligent module manufacturing production process intelligent management system

Abstract

The invention discloses an intelligent management system for an industrial intelligent module manufacturing process, and belongs to the technical field of industrial production management. The method and the device are used for solving the technical problem of poor accuracy and reliability of production abnormity targeted optimization management in different aspects of different industrial manufacturing production modules in an existing scheme. According to the method, abnormal production data of different aspects corresponding to different production modules of industrial manufacturing are periodically supervised, processed and classified, abnormal production processing data corresponding to different production modules in a supervision period are obtained, and different abnormal classification data in the abnormal production processing data corresponding to the production modules are processed and analyzed; the production states of the production module in different aspects are obtained, the abnormal production states in different aspects are subjected to management validity verification, and a targeted production abnormality management scheme is implemented for the different abnormal production states of the production module according to verification results.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial production management, and particularly relates to an intelligent management system for the manufacturing production process of industrial intelligent modules. Background Art

[0002] The management of the manufacturing production process of industrial intelligent modules refers to the use of intelligent technologies and systems to plan, control, and optimize the entire production process during industrial production and manufacturing. Its core goal is to enhance the competitiveness of enterprises by improving production efficiency, reducing production costs, ensuring product quality, and enhancing production flexibility.

[0003] When implementing the existing management solutions for the manufacturing production process of industrial intelligent modules, most of them still stay at the monitoring, statistics, processing, and analysis of production data of different production modules in industrial manufacturing, and directly conduct production management on the affiliated production modules based on the results of processing and analysis. They cannot perform multi-dimensional processing and classification on the abnormal data existing in the production modules, nor implement diversified production anomaly management solutions for abnormal data in different dimensions after processing and classification, resulting in poor accuracy and reliability of targeted optimization management for production anomalies in different aspects of different production modules in industrial manufacturing. Summary of the Invention

[0004] The purpose of the present invention is to provide an intelligent management system for the manufacturing production process of industrial intelligent modules, which is used to solve the technical problem of poor accuracy and reliability of targeted optimization management for production anomalies in different aspects of different production modules in the existing solutions.

[0005] The purpose of the present invention can be achieved through the following technical solutions: An intelligent management system for the manufacturing production process of industrial intelligent modules includes an abnormal supervision module for industrial manufacturing production modules, which is used to obtain the abnormal production data corresponding to different production modules in industrial manufacturing according to a preset supervision period, process and classify the abnormal production data of different production modules within the supervision period, and obtain the abnormal production processing data corresponding to different production modules; the abnormal production processing data includes first abnormal classification data, second abnormal classification data, and third abnormal classification data; An abnormal management module for industrial manufacturing production modules, which is used to process and analyze different abnormal classification data in the abnormal production processing data corresponding to the production modules respectively, obtain the production statuses of different aspects corresponding to the production modules, and conduct a verification of management effectiveness on the abnormal production statuses of different aspects. According to the verification results, implement targeted production anomaly management solutions for different abnormal production statuses of the production modules; Among them, for the abnormal production statuses of different aspects of the production modules, a first management effectiveness verification scheme or a second management effectiveness verification scheme is dynamically implemented.

[0006] Preferably, when classifying and processing the abnormal production data of different production modules within a supervision period, the total number of self-production anomalies, the total number of passive production anomalies, and the total number of collaborative production anomalies of the production module within the supervision period are counted, and the self-production anomaly rate, passive production anomaly rate, and collaborative production anomaly rate of the production module within the supervision period are calculated respectively based on the obtained total number of self-production anomalies, total number of passive production anomalies, and total number of collaborative production anomalies.

[0007] Preferably, the productivity of the production module within the supervision period is obtained, and the productivity of the production module is sorted and combined with the self-production anomaly rate, passive production anomaly rate, and collaborative production anomaly rate respectively to obtain the first anomaly classification data, second anomaly classification data, and third anomaly classification data corresponding to the production module.

[0008] Preferably, different anomaly classification data in the abnormal production processing data corresponding to the production module are obtained, and the different anomaly classification data are analyzed through a production status recognition function to output the production status recognition value ZSk corresponding to the production module; Among them, the expression of the production status recognition function is ; in the formula, SS0 is the productivity corresponding to the production module; k is 1, 2, 3, SSk is SS1, SS2, SS3, which are the self-production anomaly rate, passive production anomaly rate, and collaborative production anomaly rate corresponding to the production module respectively; SS´0 is the standard productivity corresponding to the production module; SS´k is SS´1, SS´2, SS´3, which are the self-production standard anomaly rate, passive production standard anomaly rate, and collaborative production standard anomaly rate corresponding to the production module respectively.

[0009] Preferably, data analysis is performed on the production status recognition value obtained by processing the production module; If the production status recognition value is 0, it is prompted that the production status of the cycle quantity of the production module is normal and the production statuses in different aspects are all normal; If the production status recognition value is 1, it is prompted that the production status of the cycle quantity of the production module is abnormal and the production statuses in different aspects are all normal; If the production status recognition value is 2, it is prompted that the production status of the cycle quantity of the production module is abnormal and the production statuses in different aspects are abnormal.

[0010] Preferably, when verifying the management effectiveness of different abnormal production statuses of the production module according to the production status recognition value of 1 or 2, if the abnormal production status history of the production module has been processed, the first management effectiveness verification plan is implemented for the abnormal production status; if the abnormal production status history of the production module has not been processed, the second management effectiveness verification plan is implemented for the abnormal production status.

[0011] Preferably, when implementing the first management effectiveness verification scheme, mark the abnormal production status that has been processed historically as the first abnormal production status, and calculate and obtain the processing verification effectiveness value CHi corresponding to the first abnormal production status through the formula CHi = SSi - SS´´i; in the formula, i is 0, 1, 2, or 3; SSi is SS0, SS1, SS2, or SS3; SS´´i is SS´´0, SS´´1, SS´´2, or SS´´3, which are the productivity, self-production abnormality rate, passive production abnormality rate, or collaborative production abnormality rate of the production module corresponding to the previous supervision cycle.

[0012] Preferably, perform data analysis on the calculated processing verification effectiveness value; If the processing verification effectiveness value is less than 0, associate the processing verification effective label with the first abnormal production status to which it belongs, and implement the existing production process management scheme for the first abnormal production status according to the processing verification effective label; Conversely, associate the processing verification invalid label with the first abnormal production status to which it belongs, update the mark of the first abnormal production status to the second abnormal production status, and implement the unfamiliar production process management scheme for the second abnormal production status.

[0013] Preferably, when implementing the second management effectiveness verification scheme, mark the abnormal production status that has not been processed historically as the third abnormal production status, and implement the unfamiliar production process management scheme for the third abnormal production.

[0014] Preferably, when implementing the unfamiliar production process management scheme, use the preset N management sub-cycles to process and calculate the periodic production abnormality rates corresponding to the second abnormal production status and the third abnormal production status of the production module, and perform data analysis on the N periodic production abnormality rates corresponding to the second abnormal production status and the third abnormal production status; N is an odd number greater than 1; If there are no less than regular periodic production abnormality rates, it is determined that the production process management of the corresponding unfamiliar production process management scheme is effective and a prompt is given; j is a positive integer; Conversely, it is determined that the production process management of the corresponding unfamiliar production process management scheme is ineffective and a prompt is given.

[0015] Compared with the existing scheme, the beneficial effects achieved by the present invention: By periodically supervising and processing and classifying the abnormal production data corresponding to different aspects of different production modules in industrial manufacturing, the present invention obtains the abnormal production processing data corresponding to different production modules in the supervision cycle, which can not only realize diversified processing of production abnormalities of different production modules, but also provide reliable data support for subsequent targeted production optimization analysis and management corresponding to different aspects of production modules.

[0016] By separately processing and analyzing different abnormal classification data in the abnormal production processing data corresponding to the production module, the present invention obtains the production status of different aspects corresponding to the production module, verifies the management effectiveness of different aspects of the abnormal production status, and implements targeted production anomaly management plans for different abnormal production statuses of the production module according to the verification results. It realizes targeted supervision, processing, verification and analysis of different abnormal production statuses of different production modules, and thus can diversely manage different abnormal production statuses of different production modules, improving the accuracy and reliability of targeted optimization management of production anomalies in different aspects of different production modules in industrial manufacturing. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention will be further described below with reference to the accompanying drawings.

[0018] Figure 1 It is a flow block diagram of the operation of an intelligent management system for the production process of industrial intelligent module manufacturing of the present invention.

[0019] Figure 2 It is a flow block diagram for data analysis of the production status identification values obtained by processing the production module in the present invention.

[0020] Figure 3 It is a module block diagram of an intelligent management system for the production process of industrial intelligent module manufacturing of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0022] As Figure 1 、 Figure 3 shown, the present invention is an intelligent management system for the production process of industrial intelligent module manufacturing, including an abnormal supervision module for industrial manufacturing production modules and an abnormal management module for industrial manufacturing production modules; The abnormal supervision module for industrial manufacturing production modules is used to obtain the abnormal production data corresponding to different industrial manufacturing production modules according to a preset supervision period, process and classify the abnormal production data of different production modules within the supervision period, and obtain the abnormal production processing data corresponding to different production modules; the abnormal production processing data includes first abnormal classification data, second abnormal classification data and third abnormal classification data; including: Among them, the preset supervision period can be determined according to the production duration of the product or the quantity of the product produced. The specific value is not limited and can be customized according to the application requirements of the actual application scenario; In addition, the division of different production modules in industrial manufacturing can be carried out according to production equipment or production processes. The specific division requirements are not limited and can also be customized according to the application requirements of the actual application scenario. Different production modules can be numbered according to the production sequence; When processing and classifying the abnormal production data of different production modules within the supervision period, count the total number of self-production abnormalities, the total number of passive production abnormalities, and the total number of collaborative production abnormalities of the production module within the supervision period, and calculate and obtain the self-production abnormality rate, passive production abnormality rate, and collaborative production abnormality rate of the production module within the supervision period respectively based on the obtained total number of self-production abnormalities, the total number of passive production abnormalities, and the total number of collaborative production abnormalities; It should be noted that self-production abnormality refers to the production abnormality of the product caused by the production module itself; Passive production abnormality refers to the production abnormality of the product caused by the production abnormality of the previous production module of the production module; Collaborative production abnormality refers to the production abnormality of the product jointly caused by the production abnormality of the production module itself and the previous production module; The division and marking of production abnormalities in different aspects can be reviewed and determined by professional technical personnel in the field according to work experience and work requirements; The calculation of the production abnormality rate of the production module corresponding to different aspects is obtained by calculating the ratio of the total number of production abnormalities in different aspects to the total number of products produced by the production module within the supervision period; And, obtain the production rate of the production module within the supervision period, and sort and combine the production rate of the production module with the self-production abnormality rate, passive production abnormality rate, and collaborative production abnormality rate respectively to obtain the first abnormal classification data, second abnormal classification data, and third abnormal classification data corresponding to the production module; In the embodiment of the present invention, by periodically supervising, processing, and classifying the abnormal production data corresponding to different aspects of different production modules in industrial manufacturing, the abnormal production processing data corresponding to different production modules within the supervision period is obtained, which can not only realize diversified processing of production abnormalities of different production modules, but also provide reliable data support for subsequent targeted production optimization analysis and management of different aspects corresponding to the production module.

[0023] An industrial manufacturing production module anomaly management module is used to separately process and analyze different anomaly classification data in the corresponding anomaly production processing data of the production module, obtain the production status of different aspects corresponding to the production module, and conduct a management effectiveness verification on the anomaly production status of different aspects. According to the verification results, a targeted production anomaly management plan is implemented for different anomaly production statuses of the production module; it includes: Obtain different anomaly classification data in the corresponding anomaly production processing data of the production module, namely the first anomaly classification data, the second anomaly classification data, and the third anomaly classification data, and perform data analysis on the different anomaly classification data through a production status recognition function to output the production status recognition value ZSk corresponding to the production module; Among them, the expression of the production status recognition function is ; in the formula, SS0 is the production rate corresponding to the production module; k is 1, 2, 3, and SSk is SS1, SS2, SS3, which are the self-production anomaly rate, passive production anomaly rate, and collaborative production anomaly rate corresponding to the production module respectively; SS´0 is the standard production rate corresponding to the production module; SS´k is SS´1, SS´2, SS´3, which are the self-production standard anomaly rate, passive production standard anomaly rate, and collaborative production standard anomaly rate corresponding to the production module respectively. Among them, the specific values of the self-production standard anomaly rate, passive production standard anomaly rate, and collaborative production standard anomaly rate corresponding to the production module are not limited and can be determined according to the existing production design requirement data corresponding to the production module, or can be determined according to the historical production anomaly data of different aspects corresponding to the production module. For example, set the median of all self-production anomaly rates that occurred in different supervision periods of the production module history as the corresponding self-production standard anomaly rate; It should be noted that the production status recognition value is used to process and match the supervision data of different aspects of the production module in the early stage to digitally represent the production status of different aspects of it; In addition, by performing data analysis on the production status recognition values of different aspects of the production module, not only can the production status of different aspects corresponding to the production module be obtained, but also reliable data support can be provided for the subsequent production optimization analysis and management of different aspects of the production module; Such as Figure 2 shown, perform data analysis on the production status recognition value obtained by processing the production module; If the production status recognition value is 0, it indicates that the production status of the cycle quantity of the production module is normal and the production statuses of different aspects are all normal; If the production status recognition value is 1, it indicates that the production status of the cycle quantity of the production module is abnormal and the production statuses of different aspects are all normal; If the production status recognition value is 2, it is prompted that there are abnormalities in the cycle quantity production status of the production module and the production status in different aspects. There are abnormalities in the production status in different aspects, including abnormalities in the self-production status, passive production status, and / or collaborative production status of the production module; Moreover, when verifying the management effectiveness of different abnormal production statuses of the production module to which it belongs according to the production status recognition value of 1 or 2, if the historical abnormal production status of the production module has been processed, the first management effectiveness verification plan is implemented for the abnormal production status to which it belongs, and the abnormal production status that has been processed historically is marked as the first abnormal production status, and the processing verification effectiveness value CHi corresponding to the first abnormal production status is calculated through the formula CHi = SSi - SS´´i; in the formula, i is 0, 1, 2, or 3; SSi is SS0, SS1, SS2, or SS3; SS´´i is SS´´0, SS´´1, SS´´2, or SS´´3, which are the productivity, self-production abnormality rate, passive production abnormality rate, or collaborative production abnormality rate of the production module corresponding to the previous supervision cycle; Perform data analysis on the calculated processing verification effectiveness value; If the processing verification effectiveness value is less than 0, the first abnormal production status to which it belongs is associated with a processing verification effective label, and the existing production process management plan is implemented for the first abnormal production status according to the processing verification effective label; Otherwise, the first abnormal production status to which it belongs is associated with a processing verification invalid label, the label of the first abnormal production status is updated to the second abnormal production status, and an unfamiliar production process management plan is implemented for the second abnormal production status; Among them, the unfamiliar production process management plan can be an alternative production process management plan that has not been implemented for the first abnormal production status; the specific content of implementing the existing production process management plan and the unfamiliar production process management plan for the first abnormal production status is not limited and can be determined by professional technical personnel in the field according to the actual application scenario; It should be noted that different from the existing technical solution that does not supervise and analyze whether the historical abnormal production status of the production module has been processed, but directly implements a fixed production process management plan for the production module with abnormal production obtained by analysis; In the embodiment of the present invention, by supervising and analyzing whether the historical abnormal production status of the production module has been processed and dynamically implementing the first management effectiveness verification plan or the second management effectiveness verification plan, the accuracy and reliability of the optimized management of abnormal production in different aspects corresponding to the production module can be effectively improved; If the historical record of the abnormal production status of the production module has not been processed, then implement the second management effectiveness verification plan for the abnormal production status to which it belongs, mark the unprocessed abnormal production status in history as the third abnormal production status, and implement the unfamiliar production process management plan for the third abnormal production; It can be understood that if the historical record of the abnormal production status of the production module has not been processed, then there is no historical processing data for this abnormal production status for processing and analysis, and the first management effectiveness verification plan cannot be implemented. Therefore, the second management effectiveness verification plan is adopted to implement the unfamiliar production process management plan for the marked third abnormal production status and conduct regulatory analysis of the periodic optimization management effect; When implementing the unfamiliar production process management plan, use the preset N management sub-cycles to process and calculate the periodic production abnormality rates corresponding to the second abnormal production status and the third abnormal production status of the production module. The periodic production abnormality rate is obtained by calculating the ratio between the total number of abnormal productions corresponding to the second abnormal production status and the third abnormal production status and the total number of product productions within the management sub-cycle, and conduct data analysis on the N periodic production abnormality rates corresponding to the second abnormal production status and the third abnormal production status; N is an odd number greater than 1, and N can take the value of 3; If there are no less than regular periodic production abnormality rates, then determine that the production process management of the corresponding unfamiliar production process management plan is effective and give a prompt; j is a positive integer, and the value of j is less than or equal to N, and j can take the value of 1; is the floor function; On the contrary, if not, then determine that the production process management of the corresponding unfamiliar production process management plan is ineffective and give a prompt, and notify the administrator to actively conduct operation and maintenance management on the implemented unfamiliar production process management plan. Active operation and maintenance management includes, but is not limited to, adding, deleting, and modifying the content of the implemented unfamiliar production process management plan; Among them, the steps for obtaining the regular periodic production abnormality rate include: Compare and judge the calculated periodic production abnormality rate with the standard periodic production abnormality rate processed in the corresponding management sub-cycle; the specific value of the standard periodic production abnormality rate can be determined according to the production verification design requirements of the corresponding production module, or can be determined according to the management design requirements of the implemented unfamiliar production process management plan, and the specific value is not limited; If the periodic production abnormality rate is less than the corresponding standard periodic production abnormality rate, then mark this periodic production abnormality rate as the regular periodic production abnormality rate; On the contrary, if not, then mark this periodic production abnormality rate as the special periodic production abnormality rate.

[0024] It should be noted that the historical data of abnormal production status in the production module has not been processed before. By dynamically implementing a targeted second management effectiveness verification plan and conducting a regulatory analysis of the periodic optimization management effect, the pertinence and reliability of the production module for optimizing management implementation of the second and third abnormal production statuses have been improved.

[0025] In the embodiments of the present invention, by separately processing and analyzing different abnormal classification data in the abnormal production processing data corresponding to the production module, the production statuses of different aspects of the production module are obtained, and the management effectiveness of different aspects of the abnormal production status is verified. According to the verification results, a targeted production anomaly management plan is implemented for different abnormal production statuses of the production module, realizing targeted supervision, processing, verification, and analysis of different abnormal production statuses of different production modules. Furthermore, diversified management of different abnormal production statuses of different production modules can be carried out, improving the accuracy and reliability of targeted optimization management of production anomalies in different aspects of different production modules in industrial manufacturing.

[0026] In several embodiments provided by the present invention, it should be understood that the disclosed system can be implemented in other ways. For example, the above-described embodiments of the invention are merely illustrative. For example, the division of modules is only a logical function division, and there can be other division methods in actual implementation.

[0027] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules. They can be located in one place or distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0028] In addition, in each embodiment of the present invention, the functional modules can be integrated into one processing module, or each module can exist physically alone, or two or more modules can be integrated into one module. The above-mentioned integrated modules can be implemented in the form of hardware or in the form of a combination of hardware and software functional modules.

[0029] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above-mentioned exemplary embodiments, and without departing from the basic characteristics of the present invention, the present invention can be implemented in other specific forms.

[0030] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An intelligent management system for the manufacturing production process of industrial intelligent modules, characterized in that, It includes an abnormal supervision module for industrial manufacturing production modules, which is used to obtain abnormal production data corresponding to different production modules in industrial manufacturing according to a preset supervision cycle, process and classify the abnormal production data of different production modules within the supervision cycle, and obtain abnormal production processing data corresponding to different production modules; the abnormal production processing data includes first abnormal classification data, second abnormal classification data, and third abnormal classification data; An abnormal management module for industrial manufacturing production modules, which is used to process and analyze different abnormal classification data in the abnormal production processing data corresponding to the production modules, obtain the production status of different aspects corresponding to the production modules, and conduct a management effectiveness verification on the abnormal production status of different aspects. According to the verification results, implement a targeted production abnormality management plan for different abnormal production statuses of the production modules; Among them, for the abnormal production status of different aspects of the production module, a first management effectiveness verification plan or a second management effectiveness verification plan is dynamically implemented.

2. An intelligent management system for the manufacturing production process of an industrial intelligent module according to claim 1, characterized in that, When processing and classifying the abnormal production data of different production modules within the supervision cycle, count the total number of self-production abnormalities, the total number of passive production abnormalities, and the total number of collaborative production abnormalities of the production module within the supervision cycle, and calculate and obtain the self-production abnormality rate, passive production abnormality rate, and collaborative production abnormality rate of the production module within the supervision cycle respectively according to the obtained total number of self-production abnormalities, total number of passive production abnormalities, and total number of collaborative production abnormalities.

3. An intelligent management system for the manufacturing production process of an industrial intelligent module according to claim 2, characterized in that, Obtain the production rate of the production module within the supervision cycle, sort and combine the production rate of the production module with the self-production abnormality rate, passive production abnormality rate, and collaborative production abnormality rate respectively, and obtain the first abnormal classification data, second abnormal classification data, and third abnormal classification data corresponding to the production module.

4. An intelligent management system for the manufacturing production process of an industrial intelligent module according to claim 3, characterized in that Obtain different abnormal classification data in the abnormal production processing data corresponding to the production module, and perform data analysis on the different abnormal classification data through a production status recognition function to output a production status recognition value ZSk corresponding to the production module; Among them, the expression of the production status recognition function is ; in the formula, SS0 is the productivity corresponding to the production module; k is 1, 2, 3, and SSk is SS1, SS2, SS3, which are the self-production abnormal rate, passive production abnormal rate, and collaborative production abnormal rate corresponding to the production module respectively; SS´0 is the standard productivity corresponding to the production module; SS´k is SS´1, SS´2, SS´3, which are the self-production standard abnormal rate, passive production standard abnormal rate, and collaborative production standard abnormal rate corresponding to the production module respectively.

5. An intelligent management system for the manufacturing production process of an industrial intelligent module according to claim 3, characterized in that, Perform data analysis on the production status recognition value obtained by processing the production module; If the production status recognition value is 0, it is prompted that the production status of the production module in terms of the number of cycles is normal and the production statuses of different aspects are all normal; If the production status recognition value is 1, it is prompted that the production status of the production module in terms of the number of cycles is abnormal and the production statuses of different aspects are all normal; If the production status recognition value is 2, it is prompted that the production status of the production module in terms of the number of cycles is abnormal and the production statuses of different aspects are abnormal.

6. The intelligent management system for the manufacturing production process of an industrial intelligent module according to claim 5, wherein When conducting a management effectiveness verification on different abnormal production statuses of the production module to which it belongs according to the production status recognition value of 1 or 2, if the abnormal production status history of the production module has been processed, implement a first management effectiveness verification plan for the abnormal production status to which it belongs; if the abnormal production status history of the production module has not been processed, implement a second management effectiveness verification plan for the abnormal production status to which it belongs.

7. An intelligent management system for the manufacturing production process of an industrial intelligent module according to claim 6, characterized in that, When implementing the first management effectiveness verification plan, mark the abnormal production status that has been processed historically as the first abnormal production status, and calculate and obtain the processing verification effectiveness value CHi corresponding to the first abnormal production status through the formula CHi = SSi - SS´´i; where i is 0, 1, 2, or 3; SSi is SS0, SS1, SS2, or SS3; SS´´i is SS´´0, SS´´1, SS´´2, or SS´´3, which are the productivity, self-production abnormal rate, passive production abnormal rate, or collaborative production abnormal rate of the production module corresponding to the previous supervision period.

8. An intelligent management system for the manufacturing production process of an industrial intelligent module according to claim 7, characterized in that, Conduct data analysis on the calculated processing verification effectiveness value. If the processing verification effectiveness value is less than 0, associate the processing verification valid label with the corresponding first abnormal production status, and implement the existing production process management plan for the first abnormal production status according to the processing verification valid label. Otherwise, associate the processing verification invalid label with the corresponding first abnormal production status, update the mark of the first abnormal production status to the second abnormal production status, and implement an unfamiliar production process management plan for the second abnormal production status.

9. An intelligent management system for the manufacturing production process of an industrial intelligent module according to claim 6, characterized in that, When implementing the second management effectiveness verification plan, mark the abnormal production status that has not been processed historically as the third abnormal production status, and implement an unfamiliar production process management plan for the third abnormal production status.

10. An intelligent management system for the manufacturing production process of an industrial intelligent module according to claim 8 or 9, characterized in that, When implementing the unfamiliar production process management plan, use the preset N management sub-cycles to process and calculate the periodic production abnormal rates corresponding to the second abnormal production status and the third abnormal production status of the production module, and conduct data analysis on the N periodic production abnormal rates corresponding to the second abnormal production status and the third abnormal production status; N is an odd number greater than 1. If there are no less than production abnormal rates in a regular cycle, it is determined that the production process management of the corresponding unfamiliar production process management plan is effective and a prompt is given; j is a positive integer; Otherwise, determine that the production process management corresponding to the unfamiliar production process management plan is ineffective and give a prompt.

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