CN115759832A

CN115759832A - Product quality tracing early warning method and system, storage medium and electronic equipment

Info

Publication number: CN115759832A
Application number: CN202211435893.3A
Authority: CN
Inventors: 王醒龙; 苏健; 赵子今; 张珣; 董方旭
Original assignee: Beijing Institute of Radio Measurement
Current assignee: Beijing Institute of Radio Measurement
Priority date: 2022-11-16
Filing date: 2022-11-16
Publication date: 2023-03-07

Abstract

The invention relates to the technical field of product quality management, in particular to a product quality tracing early warning method, a product quality tracing early warning system, a storage medium and electronic equipment, wherein the method comprises the following steps: extracting data in each business data source corresponding to the product into a data warehouse; integrating data of a data warehouse into quality problem data, product data, supply chain data, production condition data and scientific research design data; analyzing the quality problem data, the product data, the supply chain data, the production condition data and the scientific research design data to obtain a plurality of data analysis indexes for representing the product quality; according to the data analysis indexes, product quality problems are traced, the product quality problems are analyzed and displayed, early warning is carried out on problem products, and decision support is provided for a management layer.

Description

Product quality tracing early warning method and system, storage medium and electronic equipment

Technical Field

The invention relates to the technical field of product quality management, in particular to a product quality tracing early warning method, a product quality tracing early warning system, a storage medium and electronic equipment.

Background

In a traditional quality monitoring system, a traditional detection method for product quality is usually carried out in a manual spot inspection mode and only deals with unqualified products, and military products are complex and fine in structure and often move the whole body by pulling, so that the qualification of control parts is strictly required, product problems which cause problems are often required to be zeroed, and quality control is implemented on part-level products. And three steps are performed, and the product information of each link such as production, delivery, inventory and the like of each part using the same batch of the same type of unqualified products is traced. In addition, transverse evaluation is required to be carried out on manufacturers every year, and scores of the manufacturers are evaluated to be used as one index of evaluation of the suppliers; the quality problem is required to be displayed according to different dimensions, and the problem is analyzed in multiple levels and multiple dimensions. And pushing the early warning information to the responsible person, reminding the responsible person to process the early warning information, and pushing the situation to the superior leader when the processing is overdue.

Because quality inspection and analysis need to be related to databases of different standards of a plurality of different architectures of a plurality of business systems, and a plurality of departments of an enterprise need to manually go to different systems to trace product information, and report the product information after integration and statistics, the work of tracing and statistics reporting is very tedious, a large amount of manpower and material resources are needed, and the risk of errors or data tampering exists in manual tracing. The existing system can not provide visual and effective data analysis and management decision support capability, and can not realize effective product quality management and control, so that the problem is caused by the following reasons:

1) And (4) information island. Quality management is a matter throughout the whole enterprise work flow, and various informationized systems such as ERP, PDM, MES, cooperative office systems and the like which are relatively independent in business work are used in the process. Various service data exist independently, the data lack reusability, the data cannot be analyzed and managed in series intuitively and effectively, decision support capability cannot be provided for enterprise managers, wherein the OA is cooperative office work, and the filled data is manually reported data which does not come from an information service system. 2) And data difference, wherein different databases are used by each system, including SqlSever, mySQL, oracle, dameng and the like, the different databases are difficult to be directly interconnected, and related data in business cannot be directly integrated.

3) The whole process tracing, analyzing, processing, monitoring and evaluating capabilities are lacked, the processing period of quality problems is often very long, and the quality problems are difficult to find and process quickly due to the lack of monitoring;

these problems lead to poor control of product quality and inadequate control precision. Therefore, the product quality needs to be assisted to be controlled finely by an informatization means, manpower is liberated, and decision support is provided for a management layer.

Disclosure of Invention

The invention aims to solve the technical problem of the prior art and provides a product quality tracing early warning method, a product quality tracing early warning system, a storage medium and electronic equipment.

The technical scheme of the product quality tracing early warning method is as follows:

extracting data in each business data source corresponding to the product into a data warehouse;

integrating data of the data warehouse into quality problem data, product data, supply chain data, production condition data and scientific research design data;

analyzing the quality problem data, the product data, the supply chain data, the production condition data and the scientific research design data to obtain a plurality of data analysis indexes for representing the product quality;

and according to the data analysis indexes, tracing the product quality problem, analyzing and displaying the product quality problem, and early warning the problem product.

The product quality tracing early warning method has the following beneficial effects:

on one hand, by utilizing a data warehouse technology, data in different formats in each business data source are integrated and connected in series and stored in a unified data warehouse, so that the problems that the business data sources use different databases, the data formats are different, and related data in business cannot be directly integrated are solved; on the other hand, the product quality problem can be traced, analyzed and displayed, and the problem product can be early warned, so that the product quality can be finely managed, decision support is provided for a management layer, and the labor cost can be reduced.

On the basis of the scheme, the product quality tracing early warning method can be further improved as follows.

Further, the extracting data in each business data source corresponding to the product into the data warehouse includes:

and extracting the data in each business data source corresponding to the product into a data warehouse by using an ETL tool.

Further, still include:

and evaluating the suppliers of the problem products according to a plurality of data analysis indexes.

The beneficial effect of adopting the further scheme is that: and the system can also evaluate manufacturers, and further fine management on the product quality is realized.

Further, the plurality of data analysis metrics includes: quality problem quantity, critical quality problem quantity, quality problem handling time, problem handling expiration time, problem impact product quantity, problem impact production order quantity, problem impact purchase order quantity, design change rate, million order problem quantity, million product failure rate, and problem handling timeliness rate.

The technical scheme of the product quality tracing early warning system is as follows:

the system comprises an extraction module, a division module, an analysis module and a subsequent management module;

the extraction module is used for: extracting data in each business data source corresponding to the product into a data warehouse;

the dividing module is configured to: dividing data of the data warehouse into quality problem data, product data, supply chain data, production condition data and scientific research and design data;

the analysis module is configured to: analyzing the quality problem data, the product data, the supply chain data, the production condition data and the scientific research design data to obtain a plurality of data analysis indexes for representing the product quality;

the follow-up management module is configured to: and according to the data analysis indexes, tracing the product quality problem, analyzing and displaying the product quality problem, and early warning the problem product.

The product quality tracing early warning system has the following beneficial effects:

on one hand, by utilizing a data warehouse technology, data in different formats in each business data source are integrated and connected in series and stored in a unified data warehouse, so that the problems that different databases are used by each business data source, the data formats are different, and related data in business cannot be directly integrated are solved; on the other hand, the product quality problem can be traced, analyzed and displayed, and the problem product can be early warned, so that the product quality can be finely managed, decision support is provided for a management layer, and the labor cost can be reduced.

On the basis of the scheme, the product quality tracing early warning system can be further improved as follows.

Further, the extraction module is specifically configured to:

and extracting data in each business data source corresponding to the product into a data warehouse by using an ETL tool.

Further, the subsequent management module is further configured to: and evaluating the suppliers of the problem products according to a plurality of data analysis indexes.

The storage medium of the present invention stores instructions, and when the computer reads the instructions, the computer executes any one of the above product quality tracing and early warning methods.

An electronic device of the present invention includes a processor and the storage medium, where the processor executes instructions in the storage medium.

Drawings

Fig. 1 is a schematic flow chart of a product quality tracing early warning method according to an embodiment of the present invention;

fig. 2 is a second schematic flow chart of a product quality tracing early warning method according to an embodiment of the present invention;

fig. 3 is a schematic structural diagram of a product quality tracing early warning system according to an embodiment of the present invention.

Detailed Description

As shown in fig. 1 and fig. 2, a product quality tracing early warning method according to an embodiment of the present invention includes the following steps:

s1, extracting data in each business data source corresponding to a product into a data warehouse;

s2, integrating data of the data warehouse into quality problem data, product data, supply chain data, production condition data and scientific research design data;

s3, analyzing the quality problem data, the product data, the supply chain data, the production condition data and the scientific research design data to obtain a plurality of data analysis indexes for representing the product quality;

and S4, according to the plurality of data analysis indexes, tracing the product quality problem, analyzing and displaying the product quality problem, and early warning the problem product.

Wherein a theme marketplace may be provided, the theme marketplace comprising: the data analysis is carried out on the quality problem data, the product data, the supply chain data, the production condition data and the scientific research design data, and services such as product quality problem tracing, product quality problem analysis and display, problem product early warning, supplier evaluation and the like are provided at a service end.

Optionally, in the above technical solution, in S1, extracting data in each business data source corresponding to the product into a data warehouse includes:

s10, extracting data in each business data source corresponding to the product into a data warehouse by using an ETL tool.

The service data source corresponding to the product comprises: the MES system, the ERP system and the PDM system respectively extract production operation problem data in the MES system by using an ETL tool, extract purchase quality inspection problems in the ERP system and extract product design problem data in the PDM system, and the production operation problem data, the purchase quality inspection problems and the product design problem data are integrated into a quality problem data set in an enterprise. And extracting product data BOM from the PDM system, extracting supply chain information from the ERP system and extracting production information from the MES system.

Optionally, in the above technical solution, the method further includes:

according to the data analysis indexes, the suppliers of the problem products are evaluated, the manufacturers can also be evaluated, and further fine management on the product quality is realized.

Optionally, in the above technical solution, the plurality of data analysis indicators include: quality problem quantity, critical quality problem quantity, quality problem handling time, problem handling expiration time, problem impact product quantity, problem impact production order quantity, problem impact purchase order quantity, design change rate, million order problem quantity, million product failure rate, and problem handling timeliness rate. Specifically, the method comprises the following steps:

1) Quality problem quantity:

the method comprises the steps of obtaining a quality problem data set, carrying out data recombination according to dimensions such as time, responsibility departments, projects and links, forming a plurality of screenable different dimensions by using Yixin Hua Chen ABI software, displaying statistical graphs of different levels on a platform, and supporting penetration drilling to obtain quality problem details;

2) Number of serious quality problems:

the method comprises the following steps of (1) obtaining a quality problem data set, carrying out data reorganization according to dimensions such as time, responsibility departments, projects and links, forming a plurality of screenable different dimensions by using Yixin Hua Chen ABI software, displaying statistical graphs of different levels on a platform, and supporting penetration drilling to obtain the detail of serious quality problems;

3) Quality problem processing time:

and the quality problem data set and the quality problem processing flow in the system office are taken, and whether the flow is closed loop or not and the closed loop time are checked. And performing data recombination according to dimensions such as time, responsibility departments, projects and links to obtain indexes such as average processing time and longest processing time. A plurality of screenable different dimensions are formed by Yixin Hua Chen ABI software, statistical graphs of different levels are displayed on a platform, and the detail of a treatment flow of severe quality problems of penetration drilling is supported.

4) Problem handling timeout:

and the quality problems are taken from a quality problem data set and a quality problem processing flow in system office, and the quality problems of which the flow is not closed and exceeds a processing time threshold are checked. Data recombination is carried out according to dimensions such as time, responsibility departments, projects and links, a plurality of screenable different dimensions are formed by Yixin Hua Chen ABI software, statistical graphs of different levels are displayed on a platform, detail of a processing flow of penetrating drilling quality problems is supported, and intervention is warned for leaders of problem pushing departments and quality departments in the excess period.

5) Problems affect product quantity:

and (4) taking the data set of the quality problems, correlating the production orders in the MES, and obtaining the quantity of products influenced by the quality problems so as to judge the influence degree of the problems on the production. And (4) performing data recombination according to dimensions of responsibility departments, links, suppliers and the like, and evaluating the quality management capability of the supplier departments. And forming a plurality of screenable statistical graphs with different dimensions and different levels, displaying the statistical graphs on a platform, and supporting penetration drilling to obtain detailed processing flow of serious quality problems.

6) Problems affect production order quantity:

and (4) taking the data set of the quality problem, associating the production orders in the MES to obtain the quantity of the production orders influenced by the quality problem, and judging the influence degree of the problem on the production. And (4) performing data recombination according to dimensions of responsibility departments, links, suppliers and the like, and evaluating the quality management capability of the supplier departments. And forming a plurality of screenable statistical graphs with different dimensions and different levels, displaying the statistical graphs on a platform, and supporting penetration drilling to obtain detailed processing flow of serious quality problems.

7) The problem affects the number of purchase orders:

and (4) taking the data set of the quality problems, associating purchase orders in the ERP to obtain the quantity of the purchase orders influenced by the quality problems, and judging the influence degree of the problems on production. And (4) performing data recombination according to dimensions of responsibility departments, links, suppliers and the like, and evaluating the quality management capability of the supplier departments. A plurality of screenable statistical graphs with different dimensions and different levels are formed and displayed on a platform, and penetration drilling is supported to obtain detailed processing flow of serious quality problems.

8) Design change rate:

and the design quality is judged according to the number of times of change of the design file mounted in the BOM by taking the product data BOM. And performing data recombination according to the dimensions of responsibility departments, links and the like, and evaluating the design quality of a design department. And forming a plurality of screenable different dimensions, displaying statistical graphs of different levels on a platform, and supporting penetration drilling design change lists and file details.

9) Million order questions:

the quality problem/quality problem of the single-batch purchase order and the sum of the purchase orders in the same batch are 1000000, the quality problem data set is obtained, the purchase orders in the ERP are correlated, and the sum of the purchase orders corresponding to the quality problem is obtained. And performing data reorganization according to the supplier, the contract and the order dimension, and performing evaluation on the quality management capacity of the supplier department and proportional floating of the payment of the enterprise. A plurality of screenable different dimensions are formed, statistical graphs of different levels are displayed on the platform, and penetrating order details are supported.

10 Million product failure rates:

million product failure rate = quality problem product quantity/1000000, and the quality problem quantity is obtained from a quality problem data set. And performing data reorganization according to the supplier dimension, and evaluating the quality management capability of the supplier department. A plurality of screenable different dimensions are formed, statistical graphs of different levels are displayed on a platform, and penetrating order detail is supported.

11 Problem handling timeliness:

the number of quality problems/the number of quality problems to be processed in time is taken from a quality problem data set, and the quality problem processing flow in the cooperative office is checked to see whether the flow is closed loop or not and the closed loop time. And (4) performing data recombination according to dimensions such as time, responsibility departments, projects, links and the like to obtain unprocessed quality problems. A plurality of screenable different dimensions are formed by ABI software, statistical graphs of different levels are displayed on a platform, and a penetration quality problem processing flow is supported.

The following scheme is adopted for tracing the quality problem:

and extracting production operation problem data in an MES system, extracting purchase quality inspection problems in an ERP system, extracting product design problem data in a PDM system and integrating the product design problem data into an enterprise quality problem data set by using an ETL tool. And extracting product data BOM from the PDM system, extracting supply chain information from the ERP system, extracting production information from the MES system, and associating the three to obtain structured product full-chain data. The method comprises the steps of raw material purchasing, inspection and warehousing until the finished product is manufactured, inspected and delivered. After the quality problem is found, the quality supervisor selects whether to trace back the product information, and then traces back the full-chain product information for the quality problem. In the process, according to the product drawing number and the product model, the problem product data which is only corresponding to the product drawing number and the product model is searched, and the information is pushed to all link responsible persons through the cooperative office platform. Meanwhile, for the quality problems, a quality supervisor starts three processes, the quality control system obtains and uses the unified batch of products and the same version of design drawings, the finished products of the same version of software trace the whole link, and early warning information is generated and pushed to a link supervisor.

The explanation of each service data source corresponding to the product is as follows:

MES system: the manufacturing execution system, the executive function of the enterprise resource plan, can link the plan with job site control of the plant. On-site control package expansion PLC, data acquisition unit, bar code and the like

ERP system: an enterprise resource planning system comprises multiple functions of production resource planning, finance, production, sales, purchasing and the like, and is an enterprise management system which takes management accounting as a core and can integrate real-time information.

The PDM system comprises: the product data management system is a system specially used for managing all information related to products, and comprises part information, configuration, documents, CAD files and structures.

Collaborative office (OA system): the office automation system links the flow with daily things, improves the efficiency of the official document in the aspects of stream-to-approval, release and the like, and is a set of information processing and management of enterprises except production control.

The process of integrating the data of the data warehouse specifically comprises the following steps:

1. and obtaining the batches and codes of the products used in all the links of the production process according to the product data and the production condition data, namely representing the unique identification of the products, and forming a full-link traceable product structure tree. The circulation path of a product can be traced.

2. And (3) associating the quality problem data with the product structure tree formed by the step (1) according to the unique product identifier to obtain the product structure tree covering the quality problem. The influence of each quality problem on production can be traced, and whether the product uses the product with the quality problem or not can be traced.

3. And the supply chain data and the structure tree formed by the data 2 are associated with the unique product identifier, so that the corresponding suppliers of the product and the in-transit production outsourcing orders can be further traced.

4. And finally, forming a full-link traceable structure tree containing all the product production information, the quality problem information and the supply chain information, and storing the full-link traceable structure tree in a data warehouse in a data table mode. The inner product is called the inner product full chain data.

The quality problem data, product data, supply chain data, production situation data and scientific design data are explained as follows:

1) The quality issue data includes: cause of problem, classification of problem, severity, time of occurrence, etc. of quality problem

2) The product data includes: product information, product superior information, product version, version validation time and other data describing product attributes

3) The supply chain data includes: data generated by supplier, batch, code, purchase date and other supply chain links

4) The production situation data includes: data generated in production links such as production order coding, production matching detail and the like

5) The scientific design data comprises: producing attribute data in scientific research design links such as product drawing number, design data version, design information, drawing, version effective time and the like

The process of obtaining a plurality of data analysis indexes for characterizing the product quality is as follows:

1) The quality problems are as follows: the sum of the number of data pieces of the quality issue recorded in the data warehouse comes from the quality issue data.

2) The number of serious quality problems is: the severity of the quality problem recorded in the data warehouse is the sum of the number of serious data pieces, derived from the quality problem data.

3) The quality problem treatment time is as follows: the mean of the difference between the time of problem resolution and the time of problem occurrence for the quality problem data that has been resolved recorded in the data warehouse is derived from the quality problem data.

4) The problem treatment expiration time is as follows: the mean time-out of time for the out-of-date unsolved quality problem recorded in the data warehouse is derived from the quality problem data.

5) The problem affects the product quantity as follows: the product with the problem corresponds to the number of upper-level products in the BOM structure after production or during production. Quality problem data, product data, production situation data. The obtained specific process refers to the integration process of a data warehouse, products using the products are searched in the full-chain data of the products, the number of each affected product is recorded as 1, and the sum of the number of affected products is taken as the number of affected products.

6) The problem affects the number of production orders as: the product in question is taken as the complement of the corresponding number of completed or in-progress production orders. Quality problem data, product data, production situation data. The obtained specific process refers to the integration process of a data warehouse, all the products used as matched production orders are searched in the product full-chain data, the number of each affected production order is recorded as 1, and the sum of the affected production orders is taken as the number of the affected production orders.

7) The problem affects the quantity of purchase orders as follows: the product in question is taken as the complement of the corresponding number of completed or in-progress purchase orders. From quality problem data, product data, supply chain data, production situation data. The obtained specific process refers to the integration process of a data warehouse, all products used as matched purchase orders are searched in the product whole-chain data, the number of each affected purchase order is recorded as 1, and the sum of the affected purchase orders is taken as the number of the affected purchase orders.

8) The design change rate is: the number of times of file changes mounted in the product data BOM is from scientific research design data, and the calculation mode is that the number of files of the historical version/the total number of files is multiplied by 100 percent

9) The million order questions are: the quantity of quality issues that occur for a product purchased at a single supplier/the amount of orders purchased at that supplier x 1000000, out of the quality issue data, supply chain data.

10 Million product failure rates are: the quantity of product for which a quality issue occurs for a product purchased at a single supplier/the quantity of product purchased at that supplier x 1000000, derived from the quality issue data, supply chain data.

11 Problem handling timeliness rate is: quality problem number/quality problem number of a single supplier to handle in time, out of quality problem data, supply chain data.

According to the data analysis indexes, the specific processes of tracing the product quality problem, analyzing and displaying the product quality problem, early warning the problem product and evaluating the supplier of the problem product are as follows:

1) The concrete implementation mode for tracing the product quality problem is as follows:

the process refers to the integration process of a data warehouse, all links using the product, including purchasing, production and the like, can be traced in the product whole-chain data, and meanwhile, responsibility departments and responsible persons of the corresponding links are traced.

2) The specific implementation mode for analyzing and displaying the product quality problem is as follows:

and designing a webpage according to different dimensions by adopting a BI tool, displaying the webpage by using a plurality of statistical charts, drilling data according to different granularities, and displaying specific information.

3) The concrete implementation mode of early warning the problem products is as follows:

the process refers to the integration process of a data warehouse, all links using the product can be traced in the product whole-chain data, and the responsibility departments and responsible persons of the corresponding links can be traced. After a problem occurs, the early warning information is pushed to the responsible person of each link related to the product with the problem, the information such as the reason of the problem is contained in the early warning information, and the responsible person of each link is reminded to carry out self-checking.

4) The specific implementation manner of evaluating the suppliers of the problem products is as follows:

and according to the three indexes, namely the million order problem number, the million product problem number and the problem processing timeliness rate, taking a certain weight value as an evaluation index of the supplier, and recording the evaluation index into a supplier evaluation system.

To address the need for cross-system, complex data monitoring, we employ a Business Intelligence (BI) analysis system. Business intelligence is a set of theories, methods, procedures, and techniques for collecting, organizing, analyzing raw data, transforming it into meaningful information, and providing decision support. The method comprises the steps of extracting data of each business system by using an ETL (Extract-Transform-Load) tool, integrating, connecting in series, cleaning and converting various business data according to business relations, loading the data into a data warehouse (DataWarehouse) according to a predefined data warehouse model, analyzing and mining the data in the data warehouse on the basis, and providing various visual pages, thereby providing decision support for a management layer and forming a set of complete enterprise-level business intelligent analysis system. The difference between the data warehouse and the common database is that the original business data generated in each information system is stored in the database, and the data stored in the data warehouse is the data cleaned and integrated according to the analysis requirements. The ETL tool is an important ring in a BI analysis system, and the ETL tool is used for extracting required data from a plurality of different data warehouses, cleaning and converting the data and then storing the data into the data warehouses. Data analysis mining enables data analysts to quickly, consistently, and interactively view information from various dimensions, and mine deep information hidden beneath business information surfaces through statistical analysis processing, retrieval, and the like. For the analyzed data, the information such as data indexes and the like still needs to be converted into recognizable forms such as graphs, images, animations and the like, and the user is allowed to interact with the data.

In recent years, the technologies are gradually paid more attention, a hospital cheap administration risk prevention and control system developed by CN110765116A based on a commercial intelligent system, a multidimensional Chinese patent medicine full-industry supply chain efficiency analysis system developed by CN106651173A based on big data, and a hospital assistant decision support system developed by CN 101986333A.

The application of business intelligence in the field of product quality management is often regarded as a set of complete solutions, each link and product information of a problem product are traced by integrating mass data of a heterogeneous system in enterprise operation, indexes are formed to conduct transverse evaluation on manufacturers, scores of the manufacturers are evaluated, the problems are analyzed and displayed in a multi-level and multi-dimensional mode, and more accurate and clear data guarantee is provided for decision support of enterprise managers. The applicant utilizes the commercial intelligent system to independently research and design a product quality control system, and is used for solving the problem that an enterprise cannot trace and process a problem product to monitor immediately.

The invention relates to a product quality control system developed based on a commercial intelligent system, which integrates data of all business systems in an enterprise by adopting a commercial intelligent system, extracts the data of all business systems through an ETL tool, integrates and connects various business data in series according to business relations to construct a unified and complete enterprise-level data warehouse, analyzes and excavates the data in the data warehouse according to indexes concerned by business departments, provides various data analysis services to form index items, integrates the index items into structured data according to displayed logic, processes the structured data into drillable and analyzable charts for information display by using a Yixin Hua Chen ABI tool, and realizes information classification display through a platform portal, and aims to:

the system takes the working requirements of business departments as starting points, and traces back all links of the same batch of products of the same category of the inspected problematic products, and an early warning link is responsible for inspecting whether the similar products have problems, so that the method works in the opposite way; important indexes for product quality control include: quality problem quantity, severe quality problem quantity, quality problem processing time, problem processing expiration time, problem impact product quantity, problem impact production order quantity, problem impact purchase order quantity, design change rate, million order problem quantity, million product failure rate. The system management layer can be used for monitoring the existing risk items in real time and evaluating suppliers, departments and designers.

The key points of the invention are as follows:

1) By utilizing the ETL technology, data in each independent service system which operates on line are extracted into the data warehouse, and the data can be extracted in a time period when the service system is not busy every day in a self-defined mode, so that unnecessary pressure on the operating service system is avoided, and normal operation is not influenced. The ETL technology can extract required data from different databases, solves the problem that various service data of different databases are independent, updates data every day to ensure that the data are all up-to-date every day, improves the analysis timeliness, reduces the manual processing link, reduces the workload, and improves the accuracy and the authenticity;

2) By utilizing the data warehouse technology, the data in different formats in each system are integrated and connected in series and stored in a unified data warehouse, so that the problems that different databases are used by each system, the data formats are different, and the related data in business cannot be directly integrated are solved. The data stored in the data warehouse can be directly analyzed and processed according to the analysis requirements;

3) By utilizing a data visualization technology, the deep information hidden under the surface of the business information is mined by using Yixin Hua Chen ABI software through statistical analysis processing, retrieval and other modes. The analyzed data still needs to convert information such as data indexes into recognizable forms such as graphs, images and animations, and allows users to interact with the data, so that data analysts can observe the information from all dimensions quickly, consistently and interactively. The method improves the capability of tracing the product with the problems of the enterprise to prevent the problems from happening again and monitoring and evaluating the quality management capability of the supplier and the department, and solves the problems that the quality problem is difficult to trace, the quality management capability of the supplier is difficult to evaluate, and the quality management capability of the enterprise and the department is difficult to analyze.

The invention provides a supply chain management and control method based on business intelligent system development, which integrates all business information systems in an enterprise by utilizing the existing business intelligent system, extracts key information of product quality management and control from data in an online running business system to a data warehouse by an ETL tool in the business intelligent system, analyzes and excavates the data in the data warehouse to define index items, and integrates the index items into data to be displayed; finally, the Yixin Hua Chen ABI is utilized to make data to be displayed into various charts, the charts are visually displayed through an information display platform, and detailed information is drilled and viewed layer by layer; the system improves the product quality control capability since the operation, and can accurately position the delay link and the problem main body. The information is transparent, the control is carried out by data speaking, and the reflecting result is objective and accurate. A plurality of hidden problems on the service are exposed, the service management is promoted, and a new mode and means are provided for service management and control. The labor productivity is improved, the original product quality management is time-consuming and labor-consuming to obtain, manual statistics and layer-by-layer reporting are needed, and the product quality management can be obtained from the system at any time. And decision support basis is provided for enterprise managers.

In the above embodiments, although the steps are numbered as S1, S2, etc., but only the specific embodiments are given in the present application, and a person skilled in the art may adjust the execution sequence of S1, S2, etc. according to the actual situation, which is also within the protection scope of the present invention, it is understood that some embodiments may include some or all of the above embodiments.

As shown in fig. 3, a product quality tracing early warning system 200 according to an embodiment of the present invention includes an extraction module 210, a division module 220, an analysis module 230, and a subsequent management module 240;

the extraction module 210 is configured to: extracting data in each business data source corresponding to the product into a data warehouse;

the partitioning module 220 is configured to: dividing data of a data warehouse into quality problem data, product data, supply chain data, production condition data and scientific research design data;

the analysis module 230 is configured to: analyzing the quality problem data, the product data, the supply chain data, the production condition data and the scientific research design data to obtain a plurality of data analysis indexes for representing the product quality;

the follow-up management module 240 is configured to: and according to the data analysis indexes, tracing the product quality problem, analyzing and displaying the product quality problem, and early warning the problem product.

Optionally, in the above technical solution, the extraction module 210 is specifically configured to:

Optionally, in the above technical solution, the subsequent management module is further configured to: and evaluating the suppliers of the problem products according to a plurality of data analysis indexes.

Optionally, in the above technical solution, the plurality of data analysis indicators include: quality issue quantity, severe quality issue quantity, quality issue handling time, issue handling expiration time, issue impact product quantity, issue impact production order quantity, issue impact purchase order quantity, design change rate, million order issue quantity, million product failure rate, and issue handling timeliness rate.

The above steps for realizing the corresponding functions of each parameter and each unit module in the product quality tracing early warning system 200 of the present invention can refer to each parameter and step in the above embodiment of a product quality tracing early warning method, which are not described herein again.

The storage medium of the embodiment of the present invention stores instructions, and when the instructions are read by a computer, the computer is enabled to execute any one of the above product quality tracing and early warning methods.

The electronic device of the embodiment of the invention comprises a processor and the storage medium, wherein the processor executes instructions in the storage medium, and the electronic device can be a computer, a mobile phone and the like.

As will be appreciated by one skilled in the art, the present invention may be embodied as a system, method or computer program product.

Accordingly, the present disclosure may be embodied in the form of: may be embodied entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or in a combination of hardware and software, and may be referred to herein generally as a "circuit," module "or" system. Furthermore, in some embodiments, the invention may also be embodied in the form of a computer program product in one or more computer-readable media having computer-readable program code embodied in the medium.

Any combination of one or more computer-readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.

Claims

1. A product quality tracing early warning method is characterized by comprising the following steps:

2. The method for tracing and warning the product quality according to claim 1, wherein the extracting the data in each business data source corresponding to the product into a data warehouse comprises:

3. The product quality tracing early warning method according to claim 1, further comprising:

4. The product quality tracing early warning method according to any one of claims 1 to 3, wherein the plurality of data analysis indexes comprise: quality problem quantity, critical quality problem quantity, quality problem handling time, problem handling expiration time, problem impact product quantity, problem impact production order quantity, problem impact purchase order quantity, design change rate, million order problem quantity, million product failure rate, and problem handling timeliness rate.

5. A product quality tracing early warning system is characterized by comprising an extraction module, a division module, an analysis module and a subsequent management module;

the analysis module is to: analyzing the quality problem data, the product data, the supply chain data, the production condition data and the scientific research design data to obtain a plurality of data analysis indexes for representing the product quality;

6. The product quality tracing early warning system according to claim 5, wherein the extraction module is specifically configured to:

7. The product quality tracing early warning system of claim 5, wherein the follow-up management module is further configured to: and evaluating the suppliers of the problem products according to a plurality of data analysis indexes.

8. The product quality tracing early warning system of any one of claims 5 to 7, wherein the plurality of data analysis indicators comprise: quality problem quantity, critical quality problem quantity, quality problem handling time, problem handling expiration time, problem impact product quantity, problem impact production order quantity, problem impact purchase order quantity, design change rate, million order problem quantity, million product failure rate, and problem handling timeliness rate.

9. A storage medium having stored therein instructions which, when read by a computer, cause the computer to execute a product quality tracing early warning method according to any one of claims 1 to 4.

10. An electronic device comprising a processor and the storage medium of claim 9, the processor executing instructions in the storage medium.