A digital platform for quality innovation and improvement project management tools
By designing the digital platform for quality innovation and improvement of project management tools, the problems of confusing data access, messy formats and missing quality verification in traditional quality control methods have been solved, efficient access to multi-source data, fast unified formats and accurate data monitoring have been achieved, and quality management efficiency and data quality have been improved.
Patent Information
- Application Number
- CN202411784204.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-06
- Publication Date
- 2025-04-04
AI Technical Summary
Traditional quality control methods have problems such as chaotic data access, chaotic data formats, and missing quality verification, resulting in lagging feedback on quality problems and low efficiency.
A digital platform for quality innovation and improvement project management tools has been designed, and real-time acquisition, format and data verification of multi-source data are realized through the multi-source data access end, data format unified end and data verification center. The platform analyzes the conversion rates between different formats through historical data analysis, determines the unified conversion processing logic, and dynamically monitors the data range of the data interface in the data verification center to ensure data accuracy and stability.
It realizes efficient access and transmission of multi-source data, quickly and accurately unify formats, improves data flow efficiency and system data throughput capabilities, and ensures data accuracy and stability through intelligent format selection and accurate data health monitoring.
Smart Images
Figure CN119761988A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of project data management, and in particular to a digital platform for quality innovation and improvement of project management tools. Background Art
[0002] Traditional quality control methods have gradually revealed many drawbacks, giving rise to an urgent need for quality innovation and improvement of digital platforms for project management tools; From the perspective of State Grid's internal operations, the production process of products and services is becoming increasingly complex, involving multiple departments, numerous links, and massive data interactions. In the past, it relied on manual records, paper document delivery, and quality information scattered across various business systems, which was difficult to integrate and deeply mine and analyze. Due to inconsistent data formats and poor information flow between different departments, feedback on quality issues is delayed and inefficient. For example, in the manufacturing industry, the R&D department designs new products, but the production link cannot accurately obtain design details and quality standards, resulting in frequent process execution deviations. After the customer feedback information collected by the after-sales department has been reported at various levels and manually summarized and sorted, the key issues have long missed the best time to be resolved, and a large number of valuable improvement opportunities have been lost. At the same time, cutting-edge technologies such as big data, artificial intelligence, and cloud computing are booming. Big data technology makes it possible to store and process massive, multi-source data quickly; artificial intelligence algorithms can deeply analyze the correlation between complex quality data and predict potential quality risks; cloud computing gives companies the ability to flexibly allocate computing resources and reduce the cost of digital transformation. Based on these advanced technologies, a digital platform for quality innovation and improvement project management tools has emerged. It aims to solve the confusion of multi-source data access, messy data formats, and lack of quality verification in one stop, assisting companies to accurately control quality dynamics and efficiently drive continuous innovation and improvement of quality. Summary of the invention
[0003] In view of the deficiencies in the prior art, the present invention provides a digital platform for quality innovation and improvement project management tools, which solves the problems of chaotic multi-source data access, messy data formats, and lack of quality verification.
[0004] To achieve the above objectives, the present invention is implemented through the following technical solutions: a digital platform for quality innovation and improvement project management tools, including: The multi-source data access terminal confirms several data interfaces associated with the digital platform, and based on the different multi-source data associated with each data interface, transmits the multi-source data of different data interfaces collected in real time to the data format unified terminal; The data format unification end defines a set of processing cycles, and performs unified format processing on different multi-source data associated with several data interfaces within this processing cycle. The conversion rate between different formats is identified from historical data, and then the unified conversion processing logic is determined based on the data formats of different multi-source data within this processing cycle. The specific method is as follows: Confirm the formats that can be managed by the digital platform one by one, where the management format is a preset format, and simultaneously define a set of processing cycles, where the processing cycle is a preset cycle; The data capacity of different multi-source data in the processing cycle is confirmed and calibrated as R i , where i represents different multi-source data, and classifies the multi-source data of the same format, identifies the data area of the same format, and calibrates the sum of the data capacity of different multi-source data in the data area of the same format as RZ k , where k represents different data areas of the same format; Based on the confirmed groups of different management formats, a group of management formats is randomly selected as the format to be converted, and then the data format corresponding to the same format data area is used as the main format, and the conversion data when the main format is converted to the format to be converted is searched from the historical data, and the conversion rate is searched from the conversion data, and the associated groups of different conversion rates are averaged to confirm the conversion average speed as the characteristic average speed when the main format is converted to the format to be converted. Based on the RZ determined in the same format data area corresponding to the main format k And the calibrated characteristic average speed, lock conversion time: T k =RZ k ÷ characteristic average speed; For the same format to be converted, the conversion durations associated with other data areas of the same format are confirmed in turn in the same way, and the confirmed groups of conversion durations are summed up to lock the total duration value, and the total duration value is marked as the characteristic value associated with the format to be converted; Then, other management formats are taken as formats to be converted in turn, and characteristic values associated with the corresponding formats to be converted are confirmed in turn, a minimum value is selected from a number of groups of characteristic values, and the format to be converted corresponding to the minimum value is taken as the execution format; Based on the determined execution format, a number of multi-source data associated in the current processing cycle are processed in a unified format, multi-source data in different formats are converted into the execution format, and the multi-source data after format conversion are transmitted to the data verification center; The data verification center verifies the multi-source data after the format is unified, confirms the multi-source data with the same data interface, and evaluates whether the multi-source data transmitted by the data interface is normal based on different data presentations in different processing cycles. The specific methods are as follows: Confirm the multi-source data after the format is unified within the processing cycle, and then mark the multi-source data belonging to the same data interface as Y q-j , where q represents different data interfaces and j represents different multi-source data; Based on several groups of multi-source data Y associated with the corresponding data interface in this processing cycle q-j , based on several sets of multi-source data Y q-j The minimum and maximum values of the data interface are used to confirm that the data interface is within the floating range of the current processing cycle. Then determine the floating range generated by this data interface in the past processing cycle, and cross-process the confirmed groups of floating ranges to determine the cross-range. When confirming the cross-range, the floating ranges involved in the cross-confirmation must be at least two groups. The floating range including the corresponding cross-range is marked as the characteristic range of this cross-range, and the number of characteristic ranges associated with the same group of cross-ranges is marked as G. h , where h represents different crossover ranges, G is selected h The crossover range corresponding to max is used as the standard range of this data interface; The range length of the floating range corresponding to this data interface in the current processing cycle is calibrated as CD1, and the range length of the standard range determined by this data interface is calibrated as CD2, and it is identified whether CD1 and CD2 meet the following conditions: CD1÷CD2≥3. If so, a data range abnormality signal of this data interface is generated through the signal end for display. If not, no processing is required.
[0005] Preferably, it also includes: The abnormal data confirmation end, for the relevant data interface with abnormal data range signals, will confirm the abnormality of the data generated in the corresponding processing cycle, and lock the abnormal data for display. The specific method is as follows: Based on the determined standard range and the determined range length CD2, a set of determined ranges is locked, and the proposed standard range is [F1, F2]. The locked determined range is expressed as: [F1-CD2, F2+CD2]. The initial value of the determined range is locked by tracing back the range length CD2 from the initial value of the standard range, and the end value of the determined range is locked by extending the range length CD2 from the end value of the standard range. The data that does not belong to the determined range in this data interface during this processing cycle is marked as abnormal data, and the marked abnormal data is displayed for external personnel to view.
[0006] The present invention provides a digital platform for quality innovation and improvement of project management tools. Compared with the prior art, it has the following beneficial effects: Efficient data access and transmission: The multi-source data access terminal accurately confirms several related data interfaces, systematically collects multi-source data from different interfaces in real time, and quickly transmits it to the data format unified terminal to ensure the timeliness of data flow, lay a solid foundation for subsequent rapid processing and analysis of data, avoid process jams caused by poor data access, and greatly improve the overall data flow efficiency; Fast and accurate format unification: The data format unification end systematically formats complex multi-source data by limiting the preset processing cycle, and uses historical data to gain insight into the conversion rates between different formats, so as to accurately determine the unified conversion processing logic, greatly shortening the time required for data format unification. For example, when faced with a massive influx of data in different formats, it can quickly organize them into a unified format, reducing data processing delays caused by format issues, making data available faster, and improving the system's data throughput capacity; Intelligent format selection: Through a rigorous format conversion time measurement process, the optimal execution format is selected from a number of preset management formats, and multi-source data in different formats are uniformly converted, which not only ensures the standardization of the data format, but also avoids unnecessary conversion attempts due to accurate decision-making, further optimizes processing efficiency, and reduces resource consumption in the data processing process; Accurate data health monitoring: The data verification center conducts verification work on multi-source data after the format is unified. Based on the data display in different processing cycles and the data fluctuations on the same data interface, it cleverly defines the floating range and standard range of the data interface, and realizes dynamic and accurate control of data transmission through the data interface. It can keenly capture abnormal data fluctuations and promptly discover potential problems, such as data deviations caused by interface failures, data source abnormalities, etc. during data transmission, to ensure data accuracy and stability. BRIEF DESCRIPTION OF THE DRAWINGS
[0007] Figure 1 It is a schematic diagram of the principle framework of the present invention. DETAILED DESCRIPTION
[0008] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0009] First embodiment See also Figure 1, the present application provides a digital platform for quality innovation and improvement project management tools, including a multi-source data access terminal, a data format unified terminal, a data verification center, a signal terminal and an abnormal data confirmation terminal, wherein the multi-source data access terminal is electrically connected to an input node of the data format unified terminal, and the data format unified terminal, the data verification center and the signal terminal are all electrically connected from an output node to an input node, and the data verification center is electrically connected to an input node of the abnormal data confirmation terminal; Among them, the multi-source data access terminal confirms several data interfaces associated with the digital platform, and based on the different multi-source data associated with each data interface, transmits the multi-source data of different data interfaces collected in real time to the data format unified terminal; Among them, the data format unification end defines a set of processing cycles, performs format unification processing on different multi-source data associated with several data interfaces in this processing cycle, identifies the conversion rate between different formats from historical data, and then determines the unified conversion processing logic based on the data formats of different multi-source data in this processing cycle, completes the format unification work of several multi-source data in this processing cycle, shortens the processing time of data format unification, and improves its processing rate; The specific method of processing the formats of the associated different multi-source data in a unified manner is as follows: Confirm the formats that can be managed by this digital platform one by one, where the management format is a preset format, which is preset in the digital platform in advance and is a specified format. Simultaneously limit a set of processing cycles, which are preset cycles and are prepared in advance by relevant operators; The data capacity of different multi-source data in the processing cycle is confirmed and calibrated as R i , where i represents different multi-source data, and classifies the multi-source data of the same format, identifies the data area of the same format, and calibrates the sum of the data capacity of different multi-source data in the data area of the same format as RZ k , where k represents different data areas of the same format; Based on the confirmed groups of different management formats, a group of management formats is randomly selected as the format to be converted, and then the data format corresponding to the same format data area is used as the main format, and the conversion data when the main format is converted to the format to be converted is searched from the historical data, and the conversion rate is searched from the conversion data, and the associated groups of different conversion rates are averaged to confirm the conversion average speed as the characteristic average speed when the main format is converted to the format to be converted. Based on the RZ determined in the same format data area corresponding to the main format k And the calibrated characteristic average speed, lock conversion time: T k =RZ k ÷ characteristic average speed; For the same format to be converted, the conversion durations associated with other data areas of the same format are confirmed in turn in the same way, and the confirmed groups of conversion durations are summed up to lock the total duration value, and the total duration value is marked as the characteristic value associated with the format to be converted; Then, other management formats are taken as formats to be converted in turn, and characteristic values associated with the corresponding formats to be converted are confirmed in turn, a minimum value is selected from a number of groups of characteristic values, and the format to be converted corresponding to the minimum value is taken as the execution format; Based on the determined execution format, a number of multi-source data associated in the current processing cycle are processed in a unified format, multi-source data in different formats are converted into the execution format, and the multi-source data after format conversion are transmitted to the data verification center; Specifically, when confirming the data format conversion, because the selected formats to be converted are different, the conversion rates generated during the conversion will also be different. Due to the differences in the overall capacity of the data and the conversion rate, the specific differences in the corresponding conversion times will be caused. Therefore, based on the several groups of time associated with the corresponding formats to be converted, they are summed up and the total time characteristics are locked. Subsequently, the best execution format can be selected from the corresponding time characteristics to perform unified execution of the conversion.
[0010] Second embodiment This embodiment, in its specific implementation process, includes all the implementation processes of the above two groups of embodiments; The data verification center verifies the multi-source data after the format is unified, confirms the multi-source data with the same data interface, and evaluates whether the multi-source data transmitted by the data interface is normal based on different data presentations in different processing cycles. The specific methods of data verification are as follows: Confirm the multi-source data after the format is unified within the processing cycle, and then mark the multi-source data belonging to the same data interface as Y q-j , where q represents different data interfaces and j represents different multi-source data; Based on several groups of multi-source data Y associated with the corresponding data interface in this processing cycle q-j , based on several sets of multi-source data Y q-j The minimum and maximum values of the data interface are used to confirm that the data interface is within the floating range of the current processing cycle. Then determine the floating range generated by this data interface in the past processing cycle, and cross-process the confirmed groups of floating ranges to determine the cross-range. When confirming the cross-range, the floating ranges involved in the cross-confirmation are at least two groups (that is, the cross-region between two groups of floating ranges belongs to one cross-range. When three groups of floating ranges have a common cross-region, the corresponding cross-region is the cross-range of the three groups of floating ranges). The floating range including the corresponding cross-range is marked as the feature range of this cross-range, and the number of feature ranges associated with the same group of cross-ranges is marked as G. h , where h represents different crossover ranges, G is selected h The crossover range corresponding to max is used as the standard range of this data interface; The range length of the floating range corresponding to this data interface in the current processing cycle is calibrated as CD1, and the range length of the standard range determined by this data interface is calibrated as CD2, and it is identified whether CD1 and CD2 meet: CD1÷CD2≥3. If they meet, the data range abnormality signal of this data interface is generated through the signal end for display. If not, no processing is required; Specifically, under normal circumstances, the data generated by the corresponding data interface should be normal rather than chaotic, and its generation depends on the set relevant logic. However, in the actual processing process, if the data range of a data interface changes or fluctuates greatly, it means that the data generated by such data interface is abnormal, and it is necessary to judge and process the abnormality to achieve more accurate data management results and improve the overall effectiveness of this digital platform.
[0011] Among them, the abnormal data confirmation end, for the relevant data interface with abnormal data range signals, will confirm the abnormality of the data generated in the corresponding processing cycle, and lock the abnormal data for display. The specific method of abnormal confirmation is: Based on the determined standard range and the determined range length CD2, a set of determined ranges is locked, and the proposed standard range is [F1, F2]. The locked determined range is expressed as: [F1-CD2, F2+CD2]. The initial value of the determined range is locked by tracing back the range length CD2 from the initial value of the standard range, and the end value of the determined range is locked by extending the range length CD2 from the end value of the standard range. The data that does not belong to the determined range in this data interface during this processing cycle is marked as abnormal data, and the marked abnormal data is displayed for external personnel to view.
[0012] Third embodiment The specific implementation process of this embodiment includes all the implementation processes of the above two groups of embodiments.
[0013] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.
[0014] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.
Claims
1. A digital platform for quality innovation and improvement project management tools, characterized by: include: The multi-source data access terminal confirms several data interfaces associated with the digital platform, and based on the different multi-source data associated with each data interface, transmits the multi-source data of different data interfaces collected in real time to the data format unified terminal; The data format unification end defines a set of processing cycles, performs format unification processing on different multi-source data associated with several data interfaces within the processing cycle, identifies the conversion rate between different formats from historical data, and then determines the unified conversion processing logic based on the data formats of different multi-source data within the processing cycle; The data verification center verifies the multi-source data after the format is unified, confirms the multi-source data with the same data interface, and evaluates whether the multi-source data transmitted by its data interface is normal based on different data presentations in different processing cycles.
2. A digital platform for quality innovation and improvement project management tools according to claim 1, characterized in that: The specific method of the data format unification end for unifying the formats of the associated different multi-source data is as follows: Confirm the formats that can be managed by the digital platform one by one, where the management format is a preset format, and simultaneously define a set of processing cycles, where the processing cycle is a preset cycle; The data capacity of different multi-source data in the processing cycle is confirmed and calibrated as R i , where i represents different multi-source data, and classifies the multi-source data of the same format, identifies the data area of the same format, and calibrates the sum of the data capacity of different multi-source data in the data area of the same format as RZ k , where k represents different data areas of the same format; Based on the confirmed groups of different management formats, a group of management formats is randomly selected as the format to be converted, and then the data format corresponding to the same format data area is used as the main format, and the conversion data when the main format is converted to the format to be converted is searched from the historical data, and the conversion rate is searched from the conversion data, and the associated groups of different conversion rates are averaged to confirm the conversion average speed as the characteristic average speed when the main format is converted to the format to be converted. Based on the RZ determined in the same format data area corresponding to the main format k And the calibrated characteristic average speed, lock conversion time: T k =RZ k ÷ characteristic average speed; For the same format to be converted, the conversion durations associated with other data areas of the same format are confirmed in turn in the same way, and the confirmed groups of conversion durations are summed up to lock the total duration value, and the total duration value is marked as the characteristic value associated with the format to be converted; Then, other management formats are taken as formats to be converted in turn, and characteristic values associated with the corresponding formats to be converted are confirmed in turn, a minimum value is selected from a number of groups of characteristic values, and the format to be converted corresponding to the minimum value is taken as the execution format; Based on the determined execution format, several multi-source data associated in the current processing cycle are formatted in a unified manner, multi-source data in different formats are converted into the execution format, and the multi-source data after format conversion are transmitted to the data verification center.
3. A digital platform for quality innovation and improvement project management tools according to claim 1, characterized in that: The specific method of the data verification center for performing data verification on multi-source data is as follows: Confirm the multi-source data after the format is unified within the processing cycle, and then mark the multi-source data belonging to the same data interface as Y q-j , where q represents different data interfaces and j represents different multi-source data; Based on several groups of multi-source data Y associated with the corresponding data interface in this processing cycle q-j , based on several sets of multi-source data Y q-j The minimum and maximum values of the data interface are determined to confirm that the data interface is within the floating range of the current processing cycle. Then determine the floating range generated by this data interface in the past processing cycle, and cross-process the confirmed groups of floating ranges to determine the cross-range. When confirming the cross-range, the floating ranges involved in the cross-confirmation must be at least two groups. The floating range including the corresponding cross-range is marked as the characteristic range of this cross-range, and the number of characteristic ranges associated with the same group of cross-ranges is marked as G. h , where h represents different crossover ranges, G is selected h The crossover range corresponding to max is used as the standard range of this data interface; The range length of the floating range corresponding to this data interface in the current processing cycle is calibrated as CD1, and the range length of the standard range determined by this data interface is calibrated as CD2, and it is identified whether CD1 and CD2 satisfy: CD1÷CD2≥3. If so, a data range abnormality signal of this data interface is generated through the signal end for display.
4. A digital platform for quality innovation and improvement project management tools according to claim 3, characterized in that: If CD1 and CD2 do not satisfy CD1÷CD2≥3, no processing is required.
5. A digital platform for quality innovation and improvement project management tools according to claim 1, characterized in that: Also includes: The abnormal data confirmation end, for the relevant data interface with abnormal data range signals, will confirm the abnormality of the data generated in the corresponding processing cycle, and lock the abnormal data for display.
6. A quality innovation and improvement project management tool digital platform according to claim 5, characterized in that: The specific method of locking the abnormal data at the abnormal data confirmation end is: Based on the determined standard range and the determined range length CD2, a set of determined ranges is locked, and the proposed standard range is [F1, F2]. The locked determined range is expressed as: [F1-CD2, F2+CD2]. The initial value of the determined range is locked by tracing back the range length CD2 from the initial value of the standard range, and the end value of the determined range is locked by extending the range length CD2 from the end value of the standard range. The data that does not belong to the determined range in this data interface during this processing cycle is marked as abnormal data, and the marked abnormal data is displayed for external personnel to view.