Intelligent management and control method and device for whole process of quality report sampling inspection
By employing multi-dimensional weighted sampling and full-process digital management, the scientific and traceability challenges in quality report sampling inspections have been resolved, achieving efficient and comprehensive sampling inspection management, improving sampling inspection coverage and efficiency, and making it suitable for product quality inspection agencies.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- INSPUR ZHUOSHU BIG DATA IND DEV CO LTD
- Filing Date
- 2026-01-12
- Publication Date
- 2026-05-29
AI Technical Summary
The existing quality report sampling inspection has problems such as unscientific sampling process, process gaps, and difficulty in tracing results. It also lacks intelligent and integrated management and control solutions, which makes it easy to miss high-risk reports, have insufficient representativeness of results, information loss, and difficulty in tracing.
By employing a multi-dimensional weighted sampling model, intelligent task distribution, standardized inspection forms, multi-party collaborative communication, and structured archiving, combined with LIMS and OA systems, we achieve full-process digital management and control, forming complete inspection archives.
It improves the sampling coverage of high-risk reports, shortens the task distribution and inspection confirmation cycle, enhances the overall sampling efficiency, ensures the traceability of results and the integrity of records, and is applicable to product quality inspection agencies of different sizes.
Abstract
Description
Technical Field
[0001] This invention relates to the field of quality inspection and management technology, specifically providing an intelligent control method and device for the entire process of quality report sampling inspection. Background Technology
[0002] In the field of product quality inspection, random sampling of test reports is a crucial step in ensuring report quality and standardizing testing procedures. Currently, traditional random sampling of quality reports mainly relies on manual operation, which has the following technical shortcomings: The sampling process lacks scientific rigor: Existing sampling methods often employ simple random sampling or stratified sampling, failing to fully consider key factors such as the historical problem rate of reports, product risk level, and the professional competence of the chief inspector. This results in high-risk reports (such as reports from departments with frequent historical problems or reports from new qualification projects) being easily missed, and the sampling results are not representative enough to objectively reflect the overall report quality.
[0003] The sampling inspection process has gaps: the sampling, distribution, inspection, and result confirmation processes lack unified digital control. Data from each process is scattered across different systems or documents. For example, sampling lists are recorded in Excel, inspection results are filled out in paper forms, and communication is done via instant messaging. This leads to poor process coordination and makes it easy for information to be lost or misinterpreted.
[0004] The results are difficult to trace: the modification of inspection results lacks standardized records, and information such as the person making the modification, the time of modification, and the reason for modification cannot be fully retained; opinions from multiple parties are not linked to the inspection results, making it difficult to trace the process of conclusion formation during subsequent audits; the sampling archives only keep the final results and lack key information such as original inspection records and communication attachments, making it impossible to form a complete traceability chain.
[0005] To address the aforementioned issues, no integrated management and control solution that combines "intelligent sampling, closed-loop process, and full-chain traceability" has yet emerged in the current technology. There is an urgent need for an intelligent management and control method for the entire process of quality report sampling inspection that can overcome the above-mentioned technical deficiencies. Summary of the Invention
[0006] This invention addresses the shortcomings of the prior art by providing a highly practical intelligent management and control method for the entire process of quality report sampling inspection.
[0007] A further technical objective of this invention is to provide a reasonably designed, safe, and applicable intelligent control device for the entire process of quality report sampling inspection.
[0008] The technical solution adopted by this invention to solve its technical problem is: An intelligent management and control method for the entire process of quality report spot checks, wherein the sampling management module is used to construct a multi-dimensional weighted sampling model and generate a scientific list of reports to be inspected; The task distribution module enables intelligent distribution of inspection reports and multi-channel task push based on the inspectors' professional fields, task load, and avoidance rules. The report inspection module provides standardized inspection forms and auxiliary tools; The results confirmation module enables multi-party collaborative communication and traceable adjustments of inspection results, and generates the final confirmation result; The document management module stores the data from the entire sampling inspection process in a structured manner, forming a complete sampling inspection document; The data interaction module interfaces with the LIMS system, OA system, and report management system to achieve real-time data synchronization and sharing.
[0009] Furthermore, when performing multi-dimensional weighted sampling, it includes: A1. Parameter Configuration; A2. Construction of the basic sample pool; A3. Calculation of weighting coefficients; A4. Sampling execution; A5. Distribution verification and adjustment; A6. Inventory to be inspected.
[0010] Furthermore, in step A1, the user sets sampling parameters through the sampling management module, including sampling time period, total sampling quantity / proportion, report type range, and department screening conditions; In step A2, the data interaction module extracts all reports that meet the sampling parameters from the report management system to form a basic sample pool, and obtains the associated data for each report, including the historical problem rate of the main inspection department, the product risk level, the last sampling time of the main inspector, and the report type.
[0011] Furthermore, in step A3, the preset weighting rules include: Department weighting coefficient: 1.0 when historical problem rate ≤ 5%, 1.2 when 5% < historical problem rate ≤ 10%, and 1.5 when historical problem rate > 10%. Product risk weighting coefficients: 1.4 for high-risk products, 1.1 for medium-risk products, and 1.0 for low-risk products; Sampling interval weighting coefficient: The coefficient is 1.3 if the last sampling time of the chief inspector is more than 90 days, 1.1 if it is 30-90 days, and 1.0 if it is ≤30 days. Report type weighting coefficient: The coefficient for arbitration inspection reports is 1.2, and the coefficient for other types of reports is 1.0; The overall weight of each report = department weight coefficient × product risk weight coefficient × sampling interval weight coefficient × report type weight coefficient.
[0012] Furthermore, in step A4, the sampling probability of each report is calculated based on the comprehensive weight, and a random number generation algorithm is used to draw reports from the basic sample pool to form a preliminary sampling list; In step A5, the system automatically generates a pie chart of departmental distribution and a bar chart of type distribution for the preliminary sampling list. If the distribution deviation in a certain dimension exceeds a preset threshold, the sampling results are automatically adjusted. In step A6, after confirming the sampling list, the system will automatically include the report in the pending inspection database and update the report status to "pending inspection".
[0013] Furthermore, when performing end-to-end result tracing, it includes: B1. Input of inspection results; B2. Multi-party collaborative communication; B3. Result Adjustment and Traceability Recording; B4. Final result confirmed; B5. Structured archiving.
[0014] Furthermore, in step B1, inspectors fill out a standardized inspection form through the report inspection module, including compliance inspection items, problem descriptions, and overall evaluations, and the initial version of the inspection record is automatically saved; In step B2, the result confirmation module provides a communication comment section where the lead inspection department raises objections to the inspection results and uploads supporting materials. The inspectors respond, the quality management department arbitrates, and all communication content is archived in chronological order and linked to the inspection results.
[0015] Furthermore, in step B3, if the inspection results need to be adjusted, the authorized personnel initiate an adjustment application, fill in the reason for the adjustment and upload the approval materials. The system automatically records the comparison of the content before and after the adjustment, the person making the adjustment, and the adjustment time, forming a version record. In step B4, after all parties reach a consensus, a final confirmation result is generated, locked and cannot be modified, and a confirmation notification is sent to the relevant personnel.
[0016] Furthermore, in step B5, the document management module stores the sampled documents according to a "four-level structure": Level 1: Report basic information; Level 2: Inspection records; Level 3: Communication and Adjustment Records; Level 4: Final Result; At the same time, the system automatically links the original report file to form a complete sampling inspection file.
[0017] An intelligent control device for the entire process of quality report sampling inspection includes: at least one memory and at least one processor; The at least one memory is used to store a machine-readable program; The at least one processor is used to call the machine-readable program to execute an intelligent management and control method for the entire process of quality report sampling inspection.
[0018] Compared with existing technologies, the intelligent management method and device for the entire process of quality report sampling inspection of the present invention have the following outstanding advantages: This invention employs a multi-dimensional weighted sampling model that balances randomness and risk orientation, increasing the sampling coverage of high-risk reports by over 30%, avoiding omissions of critical reports, and ensuring that sampling results objectively reflect the overall report quality. The end-to-end digital management achieves seamless integration of sampling, distribution, inspection, and confirmation, shortening task distribution time and inspection result confirmation cycles, and improving overall sampling efficiency by 50%.
[0019] End-to-end version tracking, communication logs, and structured archiving ensure that modifications to each sampling result are traceable, communication is verifiable, and the records are complete, meeting audit and quality traceability requirements.
[0020] By integrating with existing business systems through the data interaction module, there is no need to reconstruct the existing IT architecture, reducing implementation costs and making it suitable for product quality inspection organizations of different sizes. Detailed Implementation
[0021] To enable those skilled in the art to better understand the present invention, the present invention will be further described in detail below with reference to specific embodiments. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0022] The following is a preferred embodiment: This embodiment presents an intelligent management and control method for the entire process of quality report spot checks. The sampling management module is used to construct a multi-dimensional weighted sampling model, generate a scientific list of reports to be inspected, and support manual secondary screening and sampling distribution verification. The task distribution module enables intelligent distribution of inspection reports and multi-channel task push based on the inspectors' professional fields, task load, and avoidance rules. The report inspection module provides standardized inspection forms and auxiliary tools, and supports structured entry of inspection results; The results confirmation module enables multi-party collaborative communication and traceable adjustments of inspection results, and generates the final confirmation result; The document management module stores the data from the entire sampling inspection process in a structured manner, forming a complete sampling inspection document; The data interaction module interfaces with the LIMS system, OA system, and report management system to achieve real-time data synchronization and sharing.
[0023] Multi-dimensional weighted sampling includes: A1. Parameter Configuration; Users can set sampling parameters through the sampling management module, including sampling time period (start date, end date), total sample size / proportion, report type range (such as commissioned inspection report, supervision and spot check report), and department screening conditions. A2. Construction of the basic sample pool: The data interaction module extracts all reports that meet the sampling parameters from the report management system to form the basic sample pool, and obtains the associated data of each report (including the historical problem rate of the main inspection department, product risk level, the last sampling time of the main inspector, and report type). A3. Calculation of weighting coefficients; Preset weighting rules include: Department weighting coefficient: 1.0 when historical problem rate ≤ 5%, 1.2 when 5% < historical problem rate ≤ 10%, and 1.5 when historical problem rate > 10%. Product risk weighting coefficients: 1.4 for high-risk products, 1.1 for medium-risk products, and 1.0 for low-risk products; Sampling interval weighting coefficient: The coefficient is 1.3 if the last sampling time of the chief inspector is more than 90 days, 1.1 if it is 30-90 days, and 1.0 if it is ≤30 days. Report type weighting coefficient: The coefficient for arbitration inspection reports is 1.2, and the coefficient for other types of reports is 1.0; The overall weight of each report = department weight coefficient × product risk weight coefficient × sampling interval weight coefficient × report type weight coefficient.
[0024] A4. Sampling execution; The sampling probability of each report is calculated based on the comprehensive weight, and a random number generation algorithm is used to draw reports from the basic sample pool to form a preliminary sampling list.
[0025] A5. Distribution Validation and Adjustment. The system automatically generates a pie chart of departmental distribution and a bar chart of type distribution for the preliminary sampling list. If the distribution deviation in a certain dimension exceeds a preset threshold (e.g., the deviation between the departmental sampling percentage and the business volume percentage > 20%), the sampling results will be automatically adjusted. It also supports manual removal of special reports (e.g., obsolete reports) and filling in the reason for removal.
[0026] A6. Inventory entry into the warehouse to be inspected; After the sampling list is confirmed, the system will automatically add the report to the inspection database and update the report status to "inspection pending".
[0027] When performing end-to-end result tracing, it includes: B1. Input of inspection results; Inspectors fill out standardized inspection forms through the report inspection module, including compliance inspection items (format, content, data, etc.), problem descriptions (problem type, severity, location), and overall evaluation. The system automatically saves the initial version of the inspection record.
[0028] B2. Multi-party collaborative communication; The results confirmation module provides a communication comment section where the lead inspection department can raise objections to the inspection results and upload supporting materials. Inspectors will respond, and the quality management department will arbitrate. All communication content is archived in chronological order and linked to the inspection results.
[0029] B3. Result Adjustment and Traceability Recording; If the inspection results need to be adjusted, the authorized personnel (the head of the quality management department or the original inspector) initiate an adjustment application, fill in the reason for the adjustment and upload the approval materials. The system automatically records the comparison of the content before and after the adjustment, the person making the adjustment, and the adjustment time, forming a version record and supporting version backtracking.
[0030] B4. Final result confirmed; Once all parties reach an agreement, the system generates a final confirmation result, locks it in place so it cannot be modified, and sends a confirmation notification to the relevant personnel.
[0031] B5. Structured archiving; The document management module stores the sampled documents according to a "four-level structure": Level 1: Basic report information (report number, product name, main inspection department, etc.); Level 2: Inspection Record (Initial Inspection Results, Problem Description, Supporting Documents); Level 3: Communication and Adjustment Records (Communication Logs, Version Modification Records, Approval Materials); Level 4: Final Result (Confirmation of Conclusion, Rectification Requirements); At the same time, the system automatically links the original report file to form a complete sampling inspection file.
[0032] Based on the above method, this embodiment provides an intelligent control device for the entire process of quality report spot checks, comprising: at least one memory and at least one processor; The at least one memory is used to store a machine-readable program; The at least one processor is used to call the machine-readable program to execute an intelligent management and control method for the entire process of quality report sampling inspection.
[0033] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.
Claims
1. An intelligent management and control method for the entire process of quality report sampling inspection, characterized in that, The sampling management module is used to build a multi-dimensional weighted sampling model and generate a scientific list of reports to be sampled. The task distribution module enables intelligent distribution of inspection reports and multi-channel task push based on the inspectors' professional fields, task load, and avoidance rules. The report inspection module provides standardized inspection forms and auxiliary tools; The results confirmation module enables multi-party collaborative communication and traceable adjustments of inspection results, and generates the final confirmation result; The document management module stores the data from the entire sampling inspection process in a structured manner, forming a complete sampling inspection document; The data interaction module interfaces with the LIMS system, OA system, and report management system to achieve real-time data synchronization and sharing.
2. The intelligent management and control method for the entire process of quality report sampling inspection according to claim 1, characterized in that, When performing multi-dimensional weighted sampling, the following are included: A1. Parameter Configuration; A2. Construction of the basic sample pool; A3. Calculation of weighting coefficients; A4. Sampling execution; A5. Distribution verification and adjustment; A6. Inventory to be inspected.
3. The intelligent management and control method for the entire process of quality report sampling inspection according to claim 2, characterized in that, In step A1, the user sets sampling parameters through the sampling management module, including sampling time period, total sampling quantity / proportion, report type range and department screening conditions; In step A2, the data interaction module extracts all reports that meet the sampling parameters from the report management system to form a basic sample pool, and obtains the associated data for each report, including the historical problem rate of the main inspection department, the product risk level, the last sampling time of the main inspector, and the report type.
4. The intelligent management and control method for the entire process of quality report sampling inspection according to claim 3, characterized in that, In step A3, the preset weighting rules include: Department weighting coefficient: 1.0 when historical problem rate ≤ 5%, 1.2 when 5% < historical problem rate ≤ 10%, and 1.5 when historical problem rate > 10%. Product risk weighting coefficients: 1.4 for high-risk products, 1.1 for medium-risk products, and 1.0 for low-risk products; Sampling interval weighting coefficient: The coefficient is 1.3 if the last sampling time of the chief inspector is more than 90 days, 1.1 if it is 30-90 days, and 1.0 if it is ≤30 days. Report type weighting coefficient: The coefficient for arbitration inspection reports is 1.2, and the coefficient for other types of reports is 1.0; The overall weight of each report = department weight coefficient × product risk weight coefficient × sampling interval weight coefficient × report type weight coefficient.
5. The intelligent management and control method for the entire process of quality report sampling inspection according to claim 4, characterized in that, In step A4, the sampling probability of each report is calculated based on the comprehensive weight, and a random number generation algorithm is used to draw reports from the basic sample pool to form a preliminary sampling list; In step A5, the system automatically generates a pie chart of departmental distribution and a bar chart of type distribution for the preliminary sampling list. If the distribution deviation in a certain dimension exceeds a preset threshold, the sampling results are automatically adjusted. In step A6, after confirming the sampling list, the system will automatically include the report in the pending inspection database and update the report status to "pending inspection".
6. The intelligent management and control method for the entire process of quality report sampling inspection according to claim 5, characterized in that, When performing end-to-end result tracing, it includes: B1. Input of inspection results; B2. Multi-party collaborative communication; B3. Result Adjustment and Traceability Recording; B4. Final result confirmed; B5. Structured archiving.
7. The intelligent management and control method for the entire process of quality report sampling inspection according to claim 6, characterized in that, In step B1, inspectors fill out a standardized inspection form through the report inspection module, including compliance inspection items, problem descriptions, and overall evaluations, and the initial version of the inspection record is automatically saved; In step B2, the result confirmation module provides a communication comment section where the lead inspection department raises objections to the inspection results and uploads supporting materials. The inspectors respond, the quality management department arbitrates, and all communication content is archived in chronological order and linked to the inspection results.
8. The intelligent management and control method for the entire process of quality report sampling inspection according to claim 7, characterized in that, In step B3, if the inspection results need to be adjusted, the authorized personnel initiate an adjustment application, fill in the reason for the adjustment and upload the approval materials. The system automatically records the comparison of the content before and after the adjustment, the person making the adjustment, and the adjustment time, forming a version record. In step B4, after all parties reach a consensus, a final confirmation result is generated, locked and cannot be modified, and a confirmation notification is sent to the relevant personnel.
9. The intelligent management and control method for the entire process of quality report sampling inspection according to claim 8, characterized in that, In step B5, the document management module stores the sampled documents according to a "four-level structure": Level 1: Report basic information; Level 2: Inspection records; Level 3: Communication and Adjustment Records; Level 4: Final Result; At the same time, the system automatically links the original report file to form a complete sampling inspection file.
10. An intelligent control device for the entire process of quality report sampling inspection, characterized in that, include: At least one memory and at least one processor; The at least one memory is used to store a machine-readable program; The at least one processor is configured to invoke the machine-readable program to perform the method according to any one of claims 1 to 9.