Production monitoring method, device and equipment for industrial products and medium

Abstract

The invention provides a production monitoring method and device of an industrial product, electronic equipment and a storage medium. The method comprises the following steps: determining that collected production information of the industrial product is incremental production information; updating intermediate tables corresponding to different production indexes according to the collected incremental production information; calculating the total number of bad weighted indexes of different production factors according to the total data of the intermediate table; wherein the total number of the bad weighting indexes comprises the sum of the bad weighting indexes of the production factors under different detection items, and the bad weighting indexes comprise the reject ratio and the bad similar proportion of the production factors under the corresponding detection items; and based on the total number of the bad weighted indexes, sorting the plurality of production factors to generate a production monitoring result of the industrial product. According to the method, the production information of the industrial products is integrated, so that the efficiency of positioning the bad factors is improved.

Description

Technical Field

[0001] The present application relates to the field of industrial production technology, and more specifically, to a production monitoring method, device, electronic equipment and storage medium for industrial products. Background Art

[0002] With the popularization of industrial Internet, more and more industrial data are collected, and various platforms have also added elements of industrial data analysis. However, there are some defects in the data analysis platforms in related technologies. For example, the lack of unified system management for the entire product R&D line leads to the development progress and quality information being scattered in different systems, making it difficult to share in a timely manner, bringing inconvenience to decision-making. At the same time, the tracing of the abnormal causes of defective products also faces challenges, and it is difficult to quickly and accurately locate the defective factors. These problems limit the effectiveness of the industrial data analysis platform.

[0003] Therefore, how to integrate the production information of industrial products and improve the efficiency of locating bad factors is a technical problem that technicians in this field need to solve. Summary of the invention

[0004] The purpose of the present application is to provide a production monitoring method and device for industrial products, an electronic device and a computer-readable storage medium, which integrate the production information of industrial products and improve the efficiency of locating bad factors.

[0005] To achieve the above objectives, the present application provides a production monitoring method for industrial products, comprising:

[0006] Determine that the collected production information of industrial products is incremental production information;

[0007] Update the intermediate tables corresponding to different production indicators according to the collected incremental production information;

[0008] The total number of defective weighted indexes of different production factors is calculated according to the full amount of data in the intermediate table; wherein the total number of defective weighted indexes includes the sum of the defective weighted indexes of the production factors under different test items, and the defective weighted index includes the defective rate and the proportion of the same type of defective products of the production factors under the corresponding test items;

[0009] Based on the total number of the defective weighted indexes, the plurality of production factors are sorted to generate a production monitoring result of the industrial product.

[0010] The collecting of production information of industrial products includes:

[0011] The processing information of the industrial product is collected through the processing station, and the detection information of the industrial product is collected through the detection station, and the processing information and the detection information are used as the production information of the industrial product.

[0012] Among them, the production monitoring method of industrial products also includes:

[0013] The project information and production process information of the industrial product are obtained, and an intermediate table corresponding to the different production indicators is generated according to the project information, the production process information and the production information collected in real time.

[0014] The calculation of the total number of weighted indexes of different production factors based on the full amount of data in the intermediate table includes:

[0015] Determine multiple production factors according to the full amount of data in the intermediate table, and determine the number of defective products corresponding to the production factors under each test item;

[0016] Calculate the defective rate and the proportion of the same category of the production factor under each test item according to the number of defective products corresponding to the production factor under each test item;

[0017] Calculate the defect weighted index of the production factor under each test item according to the defect rate and similar proportion of the production factor under each test item;

[0018] The bad weighted indexes of the same production factor under different test items are summed to obtain the total number of bad weighted indexes of the different production factors.

[0019] The calculation of the defective rate and the proportion of the same category of the production factor under each test item according to the number of defective products corresponding to the production factor under each test item includes:

[0020] Under each test item, the ratio between the number of defective products of the production factor and the total number of industrial products produced is calculated as the defective rate of the production factor, and the ratio between the number of defective products of the production factor and the total number of defective products is calculated as the same category proportion of the production factor;

[0021] The calculation of the defect weighted index of the production factor under each test item according to the defect rate and the proportion of the same type of the production factor under each test item includes:

[0022] The bad weighted index of the production factor is calculated according to the bad weighted index calculation formula; wherein the bad weighted index calculation formula is:

[0023] Defective weighted index = (2×same category proportion×defective rate) / (same category proportion +defective rate).

[0024] The step of ranking the plurality of production factors based on the total number of bad weighted indexes includes:

[0025] Calculate the bad weight percentage of each of the production factors according to the total bad weighted index of each of the production factors and the sum of the total bad weighted index of all the production factors;

[0026] The defective weight percentages of the plurality of production factors are displayed in descending order of the defective weight percentages.

[0027] Among them, the production monitoring method of industrial products also includes:

[0028] The production factor corresponding to the maximum total number of defective weighted indexes is determined as the maximum suspected factor for producing defective industrial products, so as to inspect and repair the maximum suspected factor.

[0029] To achieve the above objectives, the present application provides a production monitoring device for industrial products, comprising:

[0030] A first determination module is used to determine that the collected production information of the industrial product is incremental production information;

[0031] An update module is used to update the intermediate tables corresponding to different production indicators according to the collected incremental production information;

[0032] A calculation module, used to calculate the total number of defective weighted indexes of different production factors according to the full amount of data in the intermediate table; wherein the total number of defective weighted indexes includes the sum of the defective weighted indexes of the production factors under different test items, and the defective weighted index includes the defective rate and the proportion of the same type of defective products of the production factors under the corresponding test items;

[0033] The first generating module is used to sort the plurality of production factors based on the total number of the defective weighted indexes to generate a production monitoring result of the industrial product.

[0034] To achieve the above objectives, the present application provides an electronic device, including:

[0035] Memory for storing computer programs;

[0036] A processor is used to implement the steps of the above-mentioned industrial product production monitoring method when executing the computer program.

[0037] To achieve the above objectives, the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the production monitoring method of the industrial product as described above are implemented.

[0038] It can be seen from the above scheme that the present application provides a production monitoring method for industrial products, including: determining that the collected production information of the industrial products is incremental production information; updating the intermediate table corresponding to different production indicators according to the collected incremental production information; calculating the total number of defective weighted indexes of different production factors according to the full data of the intermediate table; wherein the total number of defective weighted indexes includes the sum of the defective weighted indexes of the production factors under different detection items, and the defective weighted index includes the defective rate and the proportion of defective of the same type of the production factors under the corresponding detection items; based on the total number of defective weighted indexes, sorting multiple production factors to generate the production monitoring results of the industrial products.

[0039] The production monitoring method provided by the present application integrates the data of engineering, production and quality-related systems by collecting the production information of industrial products, so that production managers can monitor and analyze the production process from multiple dimensions. This multi-dimensional data processing provides a more comprehensive perspective and helps to identify potential problems and improvement points in the production process. The intermediate table is updated using incremental production information to ensure the real-time and accuracy of the data. This real-time update mechanism makes production monitoring more sensitive and can quickly respond to changes in production, thereby accelerating the product development process and problem solving. By calculating the total number of bad weighted indexes of different production factors, it can provide important decision-making basis for production managers. The calculation of the bad weighted index combines the bad rate and the bad similar proportion, which helps to more accurately evaluate the impact of each production factor on product quality, thereby guiding production optimization and quality control. By calculating the bad factors and their weight proportions under each detection size, it helps users quickly lock in the cause of the abnormality and speed up the abnormality investigation progress. This rapid response mechanism can reduce production interruption time and improve production continuity and efficiency. The present application also provides a production monitoring device for industrial products, an electronic device and a computer-readable storage medium, which can also achieve the above technical effects.

[0040] It should be understood that the foregoing general description and the following detailed description are exemplary only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. The drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the following specific implementation methods, they are used to explain the present disclosure, but do not constitute a limitation to the present disclosure. In the drawings:

[0042] Figure 1 This is a flow chart of a method for monitoring the production of an industrial product according to an exemplary embodiment;

[0043] Figure 2 is a flow chart of another method for monitoring production of industrial products according to an exemplary embodiment;

[0044] Figure 3 is a structural diagram of a production monitoring device for industrial products according to an exemplary embodiment;

[0045] Figure 4 The figure is a structural diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0046] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application. In addition, in the embodiments of the present application, "first", "second", etc. are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0047] The embodiment of the present application discloses a production monitoring method for industrial products, which integrates the production information of industrial products and improves the efficiency of locating bad factors. The production monitoring method for industrial products of the present application is applied to a production monitoring device for industrial products, and the production monitoring device is a server.

[0048] See also Figure 1 , according to an exemplary embodiment, a flowchart of a method for monitoring the production of an industrial product is shown, such as Figure 1 As shown, the production monitoring method of industrial products includes:

[0049] S101: Determine that the collected production information of industrial products is incremental production information.

[0050] In this step, during the industrial production process, various production information about product production is collected through automated equipment, sensors, etc., which serves as the basis for subsequent industrial product production monitoring.

[0051] As a feasible implementation manner, before step S101, the production monitoring method of industrial products further includes:

[0052] S11: Collect processing information of industrial products through the processing station, and collect detection information of the industrial products through the detection station;

[0053] S12: Using the processing information and the detection information as production information of the industrial product, wherein the processing information includes production factors. Processing stations include CNC (Computer Numerical Control Station) stations, welding stations, anodizing stations, PVD (Physical Vapor Deposition) stations, injection molding stations, etc.

[0054] In the specific implementation, in order to comprehensively monitor the production process of industrial products, the processing information and inspection information of industrial products are collected through various processing stations and inspection stations. Processing information includes production factors of key data such as processing materials, machines, fixtures, processing points, environmental parameters (such as humidity, temperature), processing time, and processing level; while inspection information covers inspection items for industrial products. Inspection items can be the inspection type after industrial products pass through each processing station, or the inspection type after a preset number of processing stations. Inspection items include appearance inspection, performance inspection, etc. Appearance inspection or performance inspection includes inspection location, inspection results, start and end time of inspection, etc. The inspection results of appearance inspection include length, width, height, chamfer, dirt, etc., and the inspection results of performance inspection include waterproofness, airtightness, etc. After the production information is collected, the server synchronizes the production information through the datamews system. The server determines whether the production information is incremental production information. If it is incremental production information, the incremental production information is synchronized to the platform database, ensuring that the platform database can reflect the latest production information in real time.

[0055] As a preferred implementation, before step S12, the production monitoring method of industrial products further includes:

[0056] S13: Obtaining project information and production process information of the industrial product;

[0057] S14: Generate an intermediate table corresponding to the different production indicators according to the project information, the production process information and the production information collected in real time.

[0058] In the specific implementation, in addition to synchronizing the production information to the platform database, the server will also synchronize the system basic information data to the platform database. The system basic information data may include the project information and production process information of industrial products. The project information may include projects, stages, plans, execution orders, etc. The production process information may include the routing node information corresponding to the execution order and the processing basic information of the corresponding processing station, as well as each inspection item and the corresponding associated station information, and the responsible production technician information. The routing node information corresponding to the execution order is used to describe the flow path of the execution order in the production process, and each routing node represents a specific workstation or production step. The processing basic information corresponding to each routing node includes the corresponding information of the processing station and the fixture, which is used to describe the fixture used by the processing station; it also includes the corresponding information of the machine and the responsible production technician, which is used to describe the production technician responsible for maintenance and operation of the machine. The associated station information corresponding to each inspection item is used to describe at which processing station each inspection item is carried out. Through such data integration, the platform database not only has the real-time data collected by all industrial equipment, but also contains basic data information, providing comprehensive data support for subsequent production monitoring, analysis and decision-making.

[0059] After obtaining the project information, production process information, and production information of industrial products, the platform database will generate intermediate tables of different production indicators for monitoring and analysis according to different business categories. The intermediate tables may include:

[0060] 1. Production performance intermediate table: The platform database classifies and summarizes the processing information according to the dimensions of execution order, 2D code, process, work station and date, combined with business logic such as whether to rework, quality status, material status, etc., to generate a production performance intermediate table, including the cumulative performance of each process, plan, good product output, different types of defective products, incoming materials, input, inventory, etc.

[0061] 2. Intermediate table of inbound and outbound records: The platform database calculates the cumulative inbound situation of good and defective products based on the inbound and outbound records in the processing information, and generates an intermediate table of inbound and outbound records;

[0062] 3. Transfer record intermediate table: The platform database calculates the transfer status of good and defective products based on the transfer records in the processing information and generates a transfer record intermediate table;

[0063] 4. Intermediate table of returned material records: The platform database calculates the good products returned from the previous process and the next process based on the returned material records in the processing information, and generates an intermediate table of returned material records.

[0064] 5. Intermediate table of output-input ratio: Based on processing information, the platform database calculates the normal input of the first process, special incoming materials of non-first processes, transferred inputs and outputs, and the output of the last process according to dimensions such as projects, stages, plans and execution orders, so as to derive the output-input ratio and generate an intermediate table of output-input ratio.

[0065] 6. Process yield status intermediate table: The platform database generates a process yield status intermediate table containing 2D code, quality status, station, machine, fixture, floor, time, type, and part information based on the inspection information and production process information of each process (which may include the corresponding information between each processing station and fixture under the process, and the corresponding information between the machine and the responsible production technician).

[0066] 7. Inspection details intermediate table: The platform database generates an inspection details intermediate table based on the inspection information. The inspection details intermediate table may include 2D code, time, inspection items, item quality status, machine, fixture, production technician, day and night shift, parts, defective type and other information.

[0067] 8. Process dimension status intermediate table: The platform database generates a process dimension status intermediate table based on the detection information. The process dimension status intermediate table can include information such as projects, stages, plans, parts, Config, execution orders, 2D codes, time, detection results, workstations, machines, fixtures, production technicians, and detection dimension defects.

[0068] 9. UMP (Ultra-Precision Measurement Inspection) dimensional status intermediate table: The platform database generates the UMP intermediate table based on the UMP inspection information and processing information in the inspection information. The UMP intermediate table can contain information such as 2D code, execution order, Config, inspection station, inspection time, inspection point, measured value, upper and lower limits, and inspection results.

[0069] 10. Intermediate table of various performance quality conditions, such as waterproof, stress mark, resistance, pre-torque, pre-thrust, impact force, thrust, tension, shear force, etc., is generated according to the test information of performance quality, including project, stage, plan, Config, execution order, 2D code, work station, test time, test item, test item result and other columns.

[0070] All intermediate tables are synchronized to the display library through DATAX (Data Exchange) tools or ETL (Extract-Transform-Load) tools to achieve read-write separation and ensure the immediacy and accuracy of data. As a preferred implementation, after the platform database generates each intermediate table, it can also provide a report display function. For example, if you need to display the change trend of process size (Process Capability Index, CPK) over time, query the process size intermediate table through SQL (Structured Query Language) statements to obtain all the inspection 2D codes of the current project, stage, plan, Config, execution order, and inspection size. These 2D codes will be used as sample data for calculating process size. For each day's data, the standard deviation of each day is calculated based on the current inspection size standard (upper specification limit and lower specification limit). The standard deviation is a statistic that measures the degree of data dispersion, which reflects the degree of deviation between the data value and the average value. The process size of each day is calculated by combining the standard deviation, upper specification limit and lower specification limit of each day through the process size calculation formula. Based on the number of days with data, the calculated process dimensions are displayed on the trend chart at the front end. Through the trend chart, you can intuitively see the changes in process capacity over time (days).

[0071] S102: Update the intermediate table corresponding to different production indicators according to the collected incremental production information.

[0072] In this step, the platform database updates the intermediate table corresponding to different production indicators every first preset time period according to the incremental production information collected within the first preset time period, and ensures that the platform database is updated and processes the latest production information in a timely manner through incremental synchronization.

[0073] Taking the update of the process dimension status intermediate table as an example, the platform database synchronizes and processes the incremental production information every hour, and screens and cleans the incremental production information according to the maintained key dimension list to ensure that only the key information related to the process dimension is processed. Then, according to the correlation information between the detection dimension and the processing station in the production process information, the machine and fixture information is extracted from the binding code. At the same time, the relevant information of the current production technician is obtained through the information of the responsible production technician corresponding to the machine in the production process information. According to the machine and fixture information and the relevant information of the current production technician, the information related to the process dimension in the incremental production information is stored in the corresponding position in the intermediate table of the process dimension status to realize the update of the intermediate table of the process dimension status.

[0074] S103: Calculate the total number of defective weighted indexes of different production factors based on the full data of the intermediate table; wherein the total number of defective weighted indexes includes the sum of the defective weighted indexes of the production factors under different inspection items, and the defective weighted index includes the defective rate and the proportion of the same type of defects of the production factors under the corresponding inspection items.

[0075] In this step, the total number of defective weighted indexes of different production factors is calculated based on the full data in the intermediate table. This step is to conduct a comprehensive analysis of the full data in the intermediate table to determine the different production factors. Production factors refer to various factors that may affect product quality, such as machines, fixtures, production technicians, etc. in each processing station. The total number of defective weighted indexes of each production factor is calculated by comprehensive analysis of the full data in the intermediate table. The total number of defective weighted indexes refers to the sum of the defective weighted indexes of each production factor under different inspection items. Inspection items may include UMP inspection (for example, dimensional inspection of length, width, height, chamfer, groove, T-stage, etc. after CNC machining), visual inspection, etc. The total number of defective weighted indexes combines the defective rate (the proportion of defective products to the total number of products) and the proportion of defective products of the same type (the proportion of a specific problem in unqualified products). By calculating the total number of defective weighted indexes, quality control and risk assessment of production factors in the production process can be carried out.

[0076] S104: sorting a plurality of production factors based on the total number of defective weighted indexes to generate a production monitoring result of the industrial product.

[0077] In this step, multiple production factors are ranked based on the total number of defective weighted indices to generate production monitoring results for industrial products. This step is to determine the relative importance of their impact on product quality by comparing the total number of defective weighted indices of different production factors, and rank these factors according to the degree of impact. The final production monitoring results can help production managers identify and prioritize those issues that have the greatest impact on product quality.

[0078] As a feasible implementation, the S104 ranks multiple production factors based on the total number of bad weighted indexes, including:

[0079] S1041: Calculate the bad weight percentage of each production factor according to the total bad weighted index of each production factor and the sum of the total bad weighted index of all production factors;

[0080] S1042: Displaying the defective weight percentages of the plurality of production factors in descending order of the defective weight percentages.

[0081] In the specific implementation, the total number of defective weighted indexes of each production factor is first calculated, and then the defective weight percentage of each production factor is determined based on the total number of these indexes and the sum of the total number of defective weighted indexes of all production factors. This percentage reflects the proportion of each production factor in all defective factors. Finally, the production factors are sorted in order from large to small according to the defective weight percentage, so as to give priority to the production factors that have the greatest impact on product quality, providing an intuitive reference for production management and quality control. Of course, other sorting methods can also be used, such as in order from small to large according to the defective weight percentage, which is not limited here.

[0082] As a feasible implementation manner, after step 104, the production monitoring method of industrial products further includes:

[0083] S105: Determine the production factor corresponding to the maximum total number of defective weighted indexes as the maximum suspected factor for producing defective industrial products, so as to inspect and repair the maximum suspected factor.

[0084] In specific implementation, the production factor with the highest total number of defective weighted indexes is identified as the most suspected factor causing industrial product defects, and can be targeted for in-depth inspection and repair. This method allows production managers to quickly locate the key factors that may cause quality problems and take corresponding improvement measures to reduce the generation of defective products and improve production efficiency and product quality.

[0085] The production monitoring method provided by the embodiment of the present application integrates the data of engineering, production and quality-related systems by collecting the production information of industrial products, so that production managers can monitor and analyze the production process from multiple dimensions. This multi-dimensional data processing provides a more comprehensive perspective and helps to identify potential problems and improvement points in the production process. The intermediate table is updated using incremental production information to ensure the real-time and accuracy of the data. This real-time update mechanism makes production monitoring more sensitive and can quickly respond to changes in production, thereby accelerating the product development process and problem solving. By calculating the total number of bad weighted indexes of different production factors, it can provide important decision-making basis for production managers. The calculation of the bad weighted index combines the bad rate and the bad similar proportion, which helps to more accurately evaluate the impact of each production factor on product quality, thereby guiding production optimization and quality control. By calculating the bad factors and their weight proportions under each detection size, it helps users quickly lock in the cause of the abnormality and speed up the abnormal investigation progress. This quick response mechanism can reduce production interruption time and improve production continuity and efficiency.

[0086] The embodiment of the present application discloses a production monitoring method for industrial products. Compared with the previous embodiment, this embodiment further explains and optimizes the technical solution. Specifically:

[0087] See also Figure 2 , a flowchart of another method for monitoring production of industrial products according to an exemplary embodiment is shown, such as Figure 2 As shown, the production monitoring method of industrial products includes:

[0088] S201: Determine that the collected production information of the industrial product is incremental production information;

[0089] S202: Acquire the project information and production process information of the industrial product, and generate an intermediate table corresponding to the different production indicators according to the project information, the production process information and the production information collected in real time;

[0090] In the specific implementation, the project information and production process information of industrial products are obtained in advance and synchronized to the platform database. During the production process of industrial products, the production information of industrial products, including processing information and testing information, is collected in real time and synchronized to the platform database. The platform database generates an intermediate table of different production indicators for monitoring and analysis based on the project information, production process information and the full amount of production information collected of industrial products.

[0091] S203: updating the intermediate table corresponding to different production indicators at every first preset time period according to the incremental production information collected in the first preset time period;

[0092] In a specific implementation, the platform database updates the intermediate table corresponding to different production indicators every first preset time period according to the incremental production information collected within the first preset time period. Such an incremental synchronization method ensures timely update and processing of data.

[0093] S204: every second preset time period, calculating the total number of defective weighted indexes of different production factors according to the full amount of data in the intermediate table; wherein the total number of defective weighted indexes includes the sum of the defective weighted indexes of the production factors under different detection items, and the defective weighted index includes the defective rate and the proportion of the same type of defective products of the production factors under the corresponding detection items;

[0094] In the specific implementation, the platform database calculates the total number of defective weighted indexes of different production factors based on the full data in the intermediate table every second preset time period. That is, it conducts a comprehensive analysis of the full data in the intermediate table, comprehensively analyzes the defective rate and the proportion of the same type of defects under different inspection items, and calculates the total number of defective weighted indexes of each production factor.

[0095] As a feasible implementation, in step S204, the total number of bad weighted indexes of different production factors is calculated according to the full amount of data in the intermediate table, including:

[0096] S2041: Determine multiple production factors according to the full amount of data in the intermediate table, and determine the number of defective products corresponding to the production factors under each inspection item;

[0097] S2042: Calculate the defective rate and the proportion of the same type of the production factor under each test item according to the number of defective products corresponding to the production factor under each test item;

[0098] S2043: Calculating a defect weighted index of the production factor under each inspection item according to the defect rate and similar proportion of the production factor under each inspection item;

[0099] S2044: summing up the defect weighted indexes of the same production factor under different detection items to obtain the total number of defect weighted indexes of the different production factors.

[0100] In the specific implementation, first, all relevant production factors are extracted from the intermediate table. Production factors refer to various factors that may affect product quality. For each production factor, the number of defective products under each test item is counted. The test items may include UMP test, visual inspection, etc. Next, the defective rate of each production factor under each test item is calculated based on the number of defective products under each test item and the total number of processed products of each production factor under each test item, and the proportion of the same category of each production factor under each test item is calculated based on the total number of defective products under each test item. Then, combining the defective rate and the proportion of the same category, the defective weighted index of each production factor under each test item is calculated. Finally, the defective weighted index of the same production factor under different test items is added to obtain the total number of defective weighted indexes of the production factor. This total number can reflect the overall situation of the impact of the production factor on product quality and provide a basis for production monitoring and quality improvement.

[0101] As a feasible implementation method, the defective rate and similar proportion of the production factor under each inspection item are calculated according to the number of defective products corresponding to the production factor under each inspection item, including: under each inspection item, calculating the ratio between the number of defective products of the production factor and the total number of industrial products produced as the defective rate of the production factor, and calculating the ratio between the number of defective products of the production factor and the total number of defective products as the similar proportion of the production factor.

[0102] In specific implementation, in each test item, the total number of industrial products produced by each production factor and the number of defective products caused by each production factor are counted, and the ratio of the number of defective products of the production factor to the total number of industrial products produced is used as the defective rate of the production factor. Then, the total number of defective products caused by all production factors is counted, and the ratio of the number of defective products of the production factor to the total number of defective products is used as the same category proportion of the production factor.

[0103] For example, for the production factor "machine", in each test item, the total number of industrial products produced by the "machine" and the number of defective products caused by the "machine" are counted, and the ratio of the number of defective products caused by the "machine" to the total number of industrial products produced by the "machine" is used as the defect rate of the production factor "machine". Then, the total number of defective products caused by all production factors (including machines, fixtures, production technicians, etc.) in each test item is counted, and the ratio of the number of defective products caused by the "machine" to the total number of defective products is used as the same category ratio of the production factor "machine".

[0104] As a feasible implementation method, the defect weighted index of the production factor under each inspection item is calculated according to the defect rate and similar proportion of the production factor under each inspection item, including: calculating the defect weighted index of the production factor according to the defect weighted index calculation formula; wherein the defect weighted index calculation formula is: defect weighted index = (2×same proportion×defective rate) / (same proportion+defective rate).

[0105] In the specific implementation, in each test item, the defect weighted index calculation formula "defect weighted index = (2 × similar proportion × defect rate) / (same proportion + defect rate)" is used to calculate the defect weighted index of each production factor. This formula takes into account the defect rate and similar proportion, and obtains a comprehensive indicator reflecting the impact of production factor quality through weighted average, thereby providing data support for production monitoring and quality improvement.

[0106] Taking the production factor "machine" as an example, after calculating the defective weighted index of the "machine" under each test item according to the defective weighted index calculation formula, add up the defective weighted index of the "machine" under all test items to get the total defective weighted index of the production factor "machine".

[0107] S205: Calculating the bad weight percentage of each of the production factors according to the total bad weighted index of each of the production factors and the sum of the total bad weighted index of all the production factors;

[0108] S206: Displaying the defective weight percentages of the plurality of production factors in descending order of the defective weight percentages;

[0109] In the specific implementation, the total number of defective weighted indexes of each production factor is first calculated, and then the defective weight percentage of each production factor is determined based on the total number of these indexes and the sum of the total number of defective weighted indexes of all production factors. This percentage reflects the proportion of each production factor in all defective factors. Finally, the production factors are sorted in descending order according to the defective weight percentage, so as to give priority to the production factors that have the greatest impact on product quality, providing an intuitive reference for production management and quality control.

[0110] S207: Determine the production factor corresponding to the maximum total number of defective weighted indexes as the maximum suspected factor for producing defective industrial products, so as to inspect and repair the maximum suspected factor.

[0111] In specific implementation, the production factor with the highest total number of defective weighted indexes is identified as the most suspected factor causing industrial product defects, and can be targeted for in-depth inspection and repair. This method allows production managers to quickly locate the key factors that may cause quality problems and take corresponding improvement measures to reduce the generation of defective products and improve production efficiency and product quality.

[0112] It can be seen that this embodiment realizes the parallel calculation of production data, combines partitioning and indexing technology to shorten the calculation time of the intermediate table, and provides strong support for production analysis and decision-making. By calculating the bad factors and corresponding weight ratios under each detection size, it helps users quickly identify the cause of the abnormality, speeds up the abnormality investigation progress, and improves production efficiency.

[0113] The following is an introduction to a production monitoring device for an industrial product provided in an embodiment of the present application. The production monitoring device for an industrial product described below and the production monitoring method for an industrial product described above can be referenced to each other.

[0114] See also Figure 3 , according to an exemplary embodiment, a structural diagram of a production monitoring device for an industrial product is shown, such as Figure 3 As shown, including:

[0115] A first determination module 100 is used to determine whether the collected production information of the industrial product is incremental production information;

[0116] An updating module 200 is used to update the intermediate tables corresponding to different production indicators according to the collected incremental production information;

[0117] The calculation module 300 is used to calculate the total number of defective weighted indexes of different production factors according to the full amount of data in the intermediate table; wherein the total number of defective weighted indexes includes the sum of the defective weighted indexes of the production factors under different test items, and the defective weighted index includes the defective rate and the proportion of the same type of defective products of the production factors under the corresponding test items;

[0118] The first generating module 400 is used to sort the plurality of production factors based on the total number of defect weighted indexes to generate a production monitoring result of the industrial product.

[0119] The production monitoring device provided in the embodiment of the present application integrates the data of engineering, production and quality-related systems by collecting the production information of industrial products, so that production managers can monitor and analyze the production process from multiple dimensions. This multi-dimensional data processing provides a more comprehensive perspective and helps to identify potential problems and improvement points in the production process. The intermediate table is updated using incremental production information to ensure the real-time and accuracy of the data. This real-time update mechanism makes production monitoring more sensitive and can quickly respond to changes in production, thereby accelerating the product development process and problem solving. By calculating the total number of bad weighted indexes of different production factors, it can provide important decision-making basis for production managers. The calculation of the bad weighted index combines the bad rate and the bad similar proportion, which helps to more accurately evaluate the impact of each production factor on product quality, thereby guiding production optimization and quality control. By calculating the bad factors and their weight proportions under each detection size, it helps users quickly lock in the cause of the abnormality and speed up the abnormal investigation progress. This quick response mechanism can reduce production interruption time and improve production continuity and efficiency.

[0120] Based on the above embodiment, as a preferred implementation, the production monitoring device for industrial products further includes:

[0121] The collection module is used to collect the processing information of the industrial products by each processing station and the detection information of the industrial products by the detection station, and determine the processing information and the detection information as the production information of the industrial products.

[0122] Based on the above embodiment, as a preferred implementation, the production monitoring device for industrial products further includes:

[0123] The second generation module is used to obtain the project information and production process information of the industrial product, and generate an intermediate table corresponding to the different production indicators according to the project information, the production process information and the production information collected in real time.

[0124] On the basis of the above embodiments, as a preferred implementation mode, the calculation module 300 is specifically used for: determining multiple production factors according to the full data of the intermediate table, and determining the number of defective products corresponding to the production factors under each inspection item; calculating the defective rate and the proportion of the same type of the production factors under each inspection item according to the number of defective products corresponding to the production factors under each inspection item; calculating the defective weighted index of the production factor under each inspection item according to the defective rate and the proportion of the same type of the production factors under each inspection item; summing the defective weighted indexes of the same production factor under different inspection items to obtain the total number of defective weighted indexes of the different production factors.

[0125] On the basis of the above embodiments, as a preferred implementation mode, the calculation module 300 is specifically used for: under each detection item, calculating the ratio between the number of defective products of the production factor and the total number of industrial products produced as the defective rate of the production factor, calculating the ratio between the number of defective products of the production factor and the total number of defective products as the same category proportion of the production factor; calculating the defective weighted index of the production factor according to the defective weighted index calculation formula; wherein the defective weighted index calculation formula is: defective weighted index = (2×same category proportion×defective rate) / (same category proportion + defective rate).

[0126] On the basis of the above embodiment, as a preferred implementation mode, the first generation module 400 is specifically used to: calculate the bad weight percentage of each of the production factors according to the total bad weighted index of each of the production factors and the sum of the total bad weighted index of all the production factors; and display the bad weight percentages of multiple production factors in order from large to small.

[0127] Based on the above embodiment, as a preferred implementation, the production monitoring device for industrial products further includes:

[0128] The second determination module is used to determine the production factor corresponding to the maximum total number of defective weighted indexes as the maximum suspected factor for producing defective industrial products, so as to inspect and repair the maximum suspected factor.

[0129] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0130] Based on the hardware implementation of the above program module, and in order to implement the method of the embodiment of the present application, the embodiment of the present application also provides an electronic device, Figure 4 FIG. 1 is a structural diagram of an electronic device according to an exemplary embodiment. Figure 4 As shown, the electronic equipment includes:

[0131] Communication interface 1, capable of exchanging information with other devices such as network devices;

[0132] The processor 2 is connected to the communication interface 1 to realize information exchange with other devices, and is used to execute the production monitoring method of industrial products provided by one or more technical solutions when running a computer program. The computer program is stored in the memory 3.

[0133] Of course, in actual application, the various components in the electronic device are coupled together through the bus system 4. It can be understood that the bus system 4 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 4 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, Figure 4 Various buses are labeled as bus system 4.

[0134] The memory 3 in the embodiment of the present application is used to store various types of data to support the operation of the electronic device. Examples of such data include: any computer program used to operate on the electronic device.

[0135] It can be understood that the memory 3 can be a volatile memory or a non-volatile memory, and can also include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM, SyncLink Dynamic Random Access Memory), and direct RAMbus random access memory (DRRAM, Direct Rambus Random Access Memory).The memory 3 described in the embodiments of the present application is intended to include but is not limited to these and any other suitable types of memories.

[0136] The method disclosed in the above embodiment of the present application can be applied to the processor 2, or implemented by the processor 2. The processor 2 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit in the processor 2 or the instruction in the form of software. The above processor 2 may be a general-purpose processor, a DSP, or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor 2 can implement or execute the methods, steps and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor may be a microprocessor or any conventional processor, etc. In combination with the steps of the method disclosed in the embodiment of the present application, it can be directly embodied as a hardware decoding processor to execute, or it can be executed by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium, which is located in the memory 3, and the processor 2 reads the program in the memory 3 and completes the steps of the above method in combination with its hardware.

[0137] When the processor 2 executes the program, the corresponding processes in the various methods of the embodiments of the present application are implemented, which will not be repeated here for the sake of brevity.

[0138] In an exemplary embodiment, the present application also provides a storage medium, namely a computer storage medium, specifically a computer-readable storage medium, for example, a memory 3 storing a computer program, and the computer program can be executed by a processor 2 to complete the steps of the aforementioned method. The computer-readable storage medium can be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface storage, optical disk, CD-ROM, etc.

[0139] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above-mentioned method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium, which, when executed, executes the steps of the above-mentioned method embodiment; and the aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, disks or optical disks.

[0140] Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application can essentially or in other words, the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for an electronic device (which can be a personal computer, server, network device, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0141] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A production monitoring method for industrial products, characterized in that: include: Determine that the collected production information of industrial products is incremental production information; Update the intermediate tables corresponding to different production indicators according to the collected incremental production information; The total number of defective weighted indexes of different production factors is calculated according to the full amount of data in the intermediate table; wherein the total number of defective weighted indexes includes the sum of the defective weighted indexes of the production factors under different test items, and the defective weighted index includes the defective rate and the proportion of the same type of defective products of the production factors under the corresponding test items; Based on the total number of the defective weighted indexes, the plurality of production factors are sorted to generate a production monitoring result of the industrial product.

2. The production monitoring method of industrial products according to claim 1, characterized in that: Also includes: Collect processing information of industrial products through processing stations, and collect detection information of the industrial products through detection stations; The processing information and the detection information are determined as production information of the industrial product.

3. The production monitoring method of industrial products according to claim 1, characterized in that: Also includes: Obtaining project information and production process information of the industrial product; An intermediate table corresponding to the different production indicators is generated according to the project information, the production process information and the production information collected in real time.

4. The production monitoring method of industrial products according to claim 1, characterized in that: The total number of bad weighted indexes of different production factors is calculated based on the full amount of data in the intermediate table, including: Determine the plurality of production factors according to the full amount of data in the intermediate table, and determine the number of defective products corresponding to the production factors under each test item; Calculate the defective rate and the proportion of the same category of the production factor under each test item according to the number of defective products corresponding to the production factor under each test item; Calculate the defect weighted index of the production factor under each test item according to the defect rate and similar proportion of the production factor under each test item; The bad weighted indexes of the same production factor under different test items are summed to obtain the total number of bad weighted indexes of the different production factors.

5. The production monitoring method of industrial products according to claim 4, characterized in that: The calculating the defective rate and the proportion of the same category of the production factor under each test item according to the number of defective products corresponding to the production factor under each test item includes: Under each test item, the ratio between the number of defective products of the production factor and the total number of industrial products produced is calculated as the defective rate of the production factor, and the ratio between the number of defective products of the production factor and the total number of defective products is calculated as the same category proportion of the production factor; The calculation of the defect weighted index of the production factor under each test item according to the defect rate and the proportion of the same type of the production factor under each test item includes: The bad weighted index of the production factor is calculated according to the bad weighted index calculation formula; wherein the bad weighted index calculation formula is: Defective weighted index = (2×same category proportion×defective rate) / (same category proportion +defective rate).

6. The production monitoring method of industrial products according to claim 1, characterized in that: The step of ranking the plurality of production factors based on the total number of the bad weighted indexes comprises: Calculate the bad weight percentage of each of the production factors according to the total bad weighted index of each of the production factors and the sum of the total bad weighted index of all the production factors; The defective weight percentages of the plurality of production factors are displayed in descending order of the defective weight percentages.

7. The production monitoring method of industrial products according to claim 1, characterized in that: Also includes: The production factor corresponding to the maximum total number of defective weighted indexes is determined as the maximum suspected factor for producing defective industrial products, so as to inspect and repair the maximum suspected factor.

8. A production monitoring device for industrial products, characterized in that: include: A first determination module is used to determine that the collected production information of the industrial product is incremental production information; An update module is used to update the intermediate tables corresponding to different production indicators according to the collected incremental production information; A calculation module, used to calculate the total number of defective weighted indexes of different production factors according to the full amount of data in the intermediate table; wherein the total number of defective weighted indexes includes the sum of the defective weighted indexes of the production factors under different test items, and the defective weighted index includes the defective rate and the proportion of the same type of defective products of the production factors under the corresponding test items; The first generating module is used to sort the plurality of production factors based on the total number of the defective weighted indexes to generate a production monitoring result of the industrial product.

9. An electronic device, characterized in that: include: Memory for storing computer programs; A processor, configured to implement the steps of the method for monitoring the production of industrial products as claimed in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed, the steps of the production monitoring method of an industrial product as claimed in any one of claims 1 to 7 are implemented.

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