CN117172449A - Method, device, equipment and storage medium for managing automobile size precision data - Google Patents
Method, device, equipment and storage medium for managing automobile size precision data Download PDFInfo
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Abstract
The invention discloses a method, a device, equipment and a storage medium for managing automobile size precision data, wherein the method comprises the following steps: collecting automobile size precision source data, carrying out structural integration on the automobile size precision source data according to a preset data structure, carrying out real-time monitoring analysis on the structural precision data, and determining abnormal data, influence degree and associated data of the abnormal data according to an analysis result; and determining an early warning level according to the abnormal data and the influence degree, generating a problem improvement list according to the early warning level and the associated data, and monitoring the problem improvement situation. According to the method, the automobile dimensional accuracy data are uniformly managed, the accuracy data are monitored and analyzed in real time, the abnormal data, the influence degree and the associated data are determined, and the problem list is generated to perform early warning and correction monitoring on the abnormal data, so that the efficiency and the accuracy of data management and analysis can be improved, the problem can be rapidly analyzed and corrected, and the stability of the automobile body accuracy is improved.
Description
Technical Field
The present invention relates to the field of automotive dimensional accuracy management technologies, and in particular, to an automotive dimensional accuracy data management method, apparatus, device, and storage medium.
Background
At present, automobile size precision data are managed manually, so that the types of size data are more, the data volume is huge, and the following defects exist: at present, various main precision data lack of unified management, data storage paths are not unified, management modes are not unified, and calling information is not fixed. And the system relates to a plurality of levels, and the data of each department lacks overall planning, so that the data searching efficiency is low. At present, the number of precision data is huge, the data monitoring is ambiguous and has excessive useless information, and various data are independent and lack of relevance. When the precision problem is processed, various data summary needs to be independently inquired for analysis, and the problem correction efficiency is affected. By adopting a manual early warning mode, the existing precision data acquisition amount is extremely large, and the efficiency is too low due to manual operation of various works such as acquired data processing, analysis, report arrangement and the like. Real-time early warning of huge data cannot be realized, and meanwhile, the situation of early warning missing exists in part of data. After the problem occurs, the error judging period of manual analysis is long, the error judging rate is low, the factor needs to be separated from beginning to end each time, and the correction period is long.
Disclosure of Invention
The invention mainly aims to provide a method, a device, equipment and a storage medium for managing automobile size precision data, and aims to solve the technical problems of low data management and analysis efficiency and low precision in the prior art that the automobile size precision data are managed manually.
In order to achieve the above object, the present invention provides a method for managing vehicle dimensional accuracy data, the method comprising the steps of:
collecting automobile size precision source data, carrying out structural integration on the automobile size precision source data according to a preset data structure, and storing the structural precision data;
carrying out real-time monitoring analysis on the structured precision data, and determining abnormal data, influence degree and associated data of the abnormal data according to analysis results;
and determining an early warning level according to the abnormal data and the influence degree, generating a problem improvement list according to the early warning level and the associated data, and monitoring the problem improvement situation.
Optionally, the real-time monitoring analysis is performed on the structured precision data, and determining, according to an analysis result, abnormal data, an influence degree and associated data of the abnormal data includes:
determining associated dimensional accuracy data of the structured accuracy data according to a preset dimensional chain checking model;
determining the contribution degree of the associated dimensional accuracy data;
and when the contribution degree exceeds a contribution degree threshold, determining abnormal data, influence degree and associated data of the abnormal data.
Optionally, the real-time monitoring analysis is performed on the structured precision data, and determining, according to an analysis result, abnormal data, an influence degree and associated data of the abnormal data includes:
performing association degree analysis on the point position where the structured precision data are located according to a preset association model, and determining association point positions, association size rings and history improvement experience;
generating a correlation degree analysis result according to a tree structure and a list structure according to the point position of the structured precision data, the correlation point position, the correlation dimension ring and the history improvement experience;
and determining abnormal data, influence degree and associated data of the abnormal data according to the association degree analysis result.
Optionally, the real-time monitoring analysis is performed on the structured precision data, and determining, according to an analysis result, abnormal data, an influence degree and associated data of the abnormal data includes:
generating a measuring point diagram and a data view diagram according to the structured precision data, wherein the measuring point diagram and the data view diagram are used for displaying the data fluctuation condition;
and carrying out real-time monitoring analysis on the structured precision data according to the test point diagram and the data view diagram, and determining abnormal data, influence degree and associated data of the abnormal data according to analysis results.
Optionally, the determining an early warning level according to the abnormal data and the influence degree, and generating a problem improvement sheet according to the early warning level and the associated data, and monitoring the problem improvement situation includes:
determining an early warning level according to the abnormal data and the influence degree;
inquiring a preset problem record library according to the abnormal data, and judging whether a history problem record corresponding to the abnormal data exists in the preset problem record library;
if so, generating a problem improvement list according to the early warning level, the historical problem record and the associated data, and monitoring the problem improvement condition.
Optionally, after the step of determining the early warning level according to the abnormal data and the influence degree, generating the problem improvement sheet according to the early warning level and the associated data, and monitoring the problem improvement situation, the method further includes:
acquiring a problem improvement list fed back by a user after problem processing, and extracting problem reasons and correction countermeasures;
and generating a problem record according to the problem reason and the rectifying and modifying countermeasure, and adding the problem record into the preset problem record library.
Optionally, the determining an early warning level according to the abnormal data and the influence degree, and generating a problem improvement sheet according to the early warning level and the associated data, and monitoring the problem improvement situation includes:
determining an early warning level according to the abnormal data and the influence degree;
and carrying out color marking on the associated data, generating a problem improvement list according to the early warning level, the associated data and early warning personnel, and monitoring the problem improvement situation.
The invention discloses a method, a device, equipment and a storage medium for managing automobile size precision data, wherein the method comprises the following steps: collecting automobile size precision source data, carrying out structural integration on the automobile size precision source data according to a preset data structure, carrying out real-time monitoring analysis on the structural precision data, and determining abnormal data, influence degree and associated data of the abnormal data according to an analysis result; and determining an early warning level according to the abnormal data and the influence degree, generating a problem improvement list according to the early warning level and the associated data, and monitoring the problem improvement situation. According to the method, the automobile dimensional accuracy data are uniformly managed, the accuracy data are monitored and analyzed in real time, the abnormal data, the influence degree and the associated data are determined, and the problem list is generated to perform early warning and correction monitoring on the abnormal data, so that the efficiency and the accuracy of data management and analysis can be improved, the problem can be rapidly analyzed and corrected, and the stability of the automobile body accuracy is improved.
Drawings
FIG. 1 is a schematic diagram of an apparatus for managing automotive dimensional accuracy data in a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a flowchart of a first embodiment of a method for managing vehicle dimensional accuracy data according to the present invention;
FIG. 3 is a schematic diagram of functional modules of an automotive dimensional accuracy data management system according to the present invention;
FIG. 4 is a schematic diagram of a data structure of an automotive dimensional accuracy data management system according to the present invention;
FIG. 5 is a schematic diagram of a problem improvement sheet of the vehicle dimensional accuracy data management system of the present invention;
FIG. 6 is a flowchart of a second embodiment of a method for managing vehicle dimensional accuracy data according to the present invention;
FIG. 7 is a schematic diagram of correlation analysis in the method for managing vehicle dimensional accuracy data according to the present invention;
FIG. 8 is a flowchart of a third embodiment of a method for managing vehicle dimensional accuracy data according to the present invention;
FIG. 9 is a schematic diagram of the early warning judgment criteria of the method for managing vehicle dimensional accuracy data according to the present invention;
fig. 10 is a block diagram showing the construction of a first embodiment of the apparatus for managing vehicle dimensional accuracy data according to the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, fig. 1 is a schematic diagram of an automotive dimensional accuracy data management device in a hardware running environment according to an embodiment of the present invention.
As shown in fig. 1, the vehicle dimensional accuracy data management apparatus may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, a memory 1005. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wireless-Fidelity (WI-FI) interface). The Memory 1005 may be a high-speed random access Memory (Random Access Memory, RAM) or a stable nonvolatile Memory (NVM), such as a disk Memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
It will be appreciated by those skilled in the art that the structure shown in fig. 1 does not constitute a limitation of the vehicle dimensional accuracy data management apparatus, and may include more or fewer components than shown, or may combine certain components, or may have a different arrangement of components.
As shown in fig. 1, an operating system, a data storage module, a network communication module, a user interface module, and an automobile dimensional accuracy data management program may be included in the memory 1005 as one type of storage medium.
In the automobile dimensional accuracy data management apparatus shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the automobile size precision data management apparatus of the present invention may be provided in an automobile size precision data management apparatus, and the automobile size precision data management apparatus calls an automobile size precision data management program stored in the memory 1005 through the processor 1001 and executes the automobile size precision data management method provided by the embodiment of the present invention.
An embodiment of the invention provides an automobile size precision data management method, referring to fig. 2, fig. 2 is a flow chart of a first embodiment of the automobile size precision data management method of the invention.
In this embodiment, the method for managing the dimensional accuracy data of the automobile includes the following steps:
step S10: and acquiring automobile size precision source data, carrying out structural integration on the automobile size precision source data according to a preset data structure, and storing the structural precision data.
It should be noted that, the execution body of the method of the embodiment may be an automobile data management device having functions of data integration, data analysis, anomaly early warning, network communication and program operation, for example, an automobile size precision data management device; other vehicle dimensional accuracy data management devices having the same or similar functions, or servers for vehicle dimensional accuracy data management are also possible. The present embodiment and the following embodiments will exemplify the vehicle dimensional accuracy data management method of the present invention by taking a vehicle dimensional accuracy data management apparatus as an example.
It can be understood that an automobile size precision data management system can be established in the automobile size precision data management device, and replaces manual precision data management by the system, and the functional modules of the system can refer to fig. 3, and fig. 3 is a schematic diagram of the functional modules of the automobile size precision data management system. The white car precision data can be imported into the system for digital control, and unified precision data and same platform management are realized. The complex work of manual data import is reduced, the automatic importing system of precision data breaks through the mode that data acquisition, compiling and arrangement are all responsible for by manpower and have low efficiency, data conversion staff are developed, automatic data reading and identification are realized, and the workload of precision data management staff is reduced.
It should be appreciated that automatic collection of data may be achieved by maintaining a basic configuration of the data source, configuring an automatic execution thread. The data source basic configuration information may include address, access mode, timed execution thread rule, etc. configurations. The automobile size precision source data such as skeleton precision, online measurement, construction and payment precision, matching precision, sub-assembly UCF, stamping PCF, fixture precision, scanning point cloud and the like can be automatically acquired. And the acquisition process checks the original data according to the related rules and records the abnormal condition. Various data are measured and exported by equipment, a measuring table is input, and the system is used for analysis and generation.
It is easy to understand that the structural integration of the vehicle dimensional accuracy source data can be performed according to a preset data structure. Data structures may be maintained by the system, including hierarchical trees of various types of data and point location configuration information. And the quick query and abnormal real-time feedback of the data are realized. Referring to fig. 4, fig. 4 is a schematic diagram of a data structure of an automotive dimensional accuracy data management system according to the present invention, a hierarchical tree may be a structure of data type → line body → vehicle type → part/area → point location, and maintenance of point location information may include: point location number, theoretical value, management value, up-down deviation, feature name (chinese), measurement point nature, selection of applicable early warning rules, setting importance a/B/C, whether to hide in report, setting criteria of good/pass/fail/reject (configured in tolerance range), responsible person, related person, self-engineering confirmer, post-engineering confirmer, point location type (measurement type/calculation type, wherein calculation type point location needs a system to provide a calculation formula, satisfies calculation conditions between referring to other nodes), and association point location setting. Besides the measuring points, the calculation type size can be customized, the calculation formula of the function size is filled in by referring to the system measuring points, and the added calculation type size can be calculated by using common running symbols.
In addition, the structured precision data is stored by the system, so that the precision data can be inquired. Specifically, the skeleton precision data of the white automobile body can be called only by inputting the relevant automobile body number, other data can be called at any time in daily life, the traceability of the precision big data is realized, and the limitation of the measurement group number of the traditional electronic measurement meter is improved.
Step S20: and carrying out real-time monitoring analysis on the structured precision data, and determining abnormal data, influence degree and associated data of the abnormal data according to an analysis result.
It can be understood that the comprehensive analysis and management of the data can be realized through the functions of association analysis, size analysis and the like, and the linkage, intelligent analysis, intelligent decision and intelligent early warning of all the data are realized through defining the association and size chain relation of various data, so that the rapid analysis of abnormal automatic problems is realized.
It is worth to say that, the correlation trend graph can display the correlation between the measuring points, so that corresponding correlation data can be found according to the abnormal data. The trend graph shows the trend of measurement data of a single characteristic direction of a measuring point in a sample size, wherein the measurement data of a horizontal axis is taken as time, and the vertical axis is taken as time, and is matched with the boundary line of three-level tolerance. It can reflect the trend of the measured value of the measuring point and display a series of parameters of the measuring point in the sample size at the lower part of the graph. The correlation trend graph can display correlation trend graphs of N measurement characteristic directions selected from sample size data and analyze statistical data. From the correlation between the stations, the interrelationship between the stations can be deduced, and when a problem occurs at one station, the root of the problem can be deduced from the change of the associated station. And finishing the correlation trend graph through multiple selected points. In addition, correlation analysis can be performed through commonly used statistical graphs, such as rainbow graphs, single-value moving range control graphs, mean moving range control graphs, median moving range control graphs, histograms, and the like.
Step S30: and determining an early warning level according to the abnormal data and the influence degree, generating a problem improvement list according to the early warning level and the associated data, and monitoring the problem improvement situation.
It can be understood that a measurement model can be established, deviation occurs in any dimension child item in the structured precision data, and whether the deviation exceeds the tolerance or not, the influence degree (median and dispersion CP) on the corresponding parent dimension item of the upper-level large assembly and the whole body of the white car can be reflected; when the deviation exceeds the technical requirements of the project, different levels of early warning can be provided according to different degrees of exceeding. The precision, the payment precision and the QVCC size of the white automobile body can be decomposed into key control factors such as stamping parts, sub-assemblies, door cover assemblies, clamps and the like through size chain checking, when the QVCC size deviates, the system automatically provides the influence degree of each influence factor, the factor is locked rapidly, and disposal countermeasures are timely taken; therefore, intelligent error judgment and decision making of the system are realized, and the process personnel are assisted to improve the analysis efficiency of the dimensional accuracy problem, the consistency of analysis ideas and the accuracy.
In a specific implementation, referring to fig. 5, fig. 5 is a schematic diagram of a problem improvement list of the vehicle dimensional accuracy data management system of the present invention. The problem improvement list can be generated by marking the abnormal data in different modes according to different early warning levels, the problem improvement list is sent to corresponding responsible personnel for problem improvement, the improvement situation can be monitored and tracked through the system, and abnormal data processing closed loop is guaranteed.
It can be understood that when a certain part or region is changed according to the design/process, the point position synchronization in the drawing can be correspondingly adjusted, including the addition, deletion, modification and the like of the point positions. In a specific operation, change information may be filled in, approval initiated, and change records may be queried in a change ledger (history). The system can also update the standard of the corresponding measuring point through the change flow of the sealing data, and the monitoring of the sealing data is realized by combining the system setting.
In the embodiment, the method comprises the steps of collecting automobile size precision source data, carrying out structural integration on the automobile size precision source data according to a preset data structure, carrying out real-time monitoring analysis on the structural precision data, and determining abnormal data, influence degree and associated data of the abnormal data according to an analysis result; and determining an early warning level according to the abnormal data and the influence degree, generating a problem improvement list according to the early warning level and the associated data, and monitoring the problem improvement situation. According to the method and the device for monitoring the vehicle body accuracy, the vehicle size accuracy data are uniformly managed, the accuracy data are monitored and analyzed in real time, abnormal data, influence degree and associated data are determined, and the problem list is generated to perform early warning and correction monitoring on the abnormal data, so that the efficiency and accuracy of data management and analysis can be improved, the problem can be rapidly analyzed and corrected, and the stability of the vehicle body accuracy is improved.
Referring to fig. 6, fig. 6 is a flowchart illustrating a second embodiment of a method for managing vehicle dimensional accuracy data according to the present invention.
Further, the size analysis is performed through a preset size chain check model, comprehensive analysis management of data can be achieved, linkage, intelligent analysis, intelligent decision and intelligent early warning of all data are achieved through definition of size chain relations of various data, and abnormal automatic problem rapid analysis is achieved. Therefore, based on the first embodiment, in the present embodiment, the step S20 includes:
step S201: and determining the associated dimensional accuracy data of the structured accuracy data according to a preset dimensional chain checking model.
Step S202: and determining the contribution degree of the associated dimensional accuracy data.
Step S203: and when the contribution degree exceeds a contribution degree threshold, determining abnormal data, influence degree and associated data of the abnormal data.
It can be understood that the associated size of a certain size can be found according to a preset size chain checking model, and the contribution degree of each associated size is calculated through the duty ratio condition of analysis results such as standard deviation square and the like. The parameters are set according to the requirements by selecting system measuring points (custom data), the corresponding checking result can be automatically calculated, and the early warning requirement can be set to realize automatic early warning.
In the concrete implementation, the size checking record can be created, the information such as the size name is filled in, and the system automatically calculates the contribution degree of each associated size; if the size check record table has the size point position selected from the point position numbers of the data analysis, when the size chain factor of the related point position acquires the latest data, indexes such as contribution degree and the like are updated in real time, and early warning is performed when the size chain factor exceeds a threshold value. The system can also generate a size checking ledger according to the requirement, so that the user can conveniently inquire, check and export.
Further, through the association analysis function, further analysis and management of data are realized, and through defining the association of various data, linkage, intelligent analysis, intelligent decision and intelligent early warning of all data are realized, and abnormal automatic problem rapid analysis is realized. Therefore, the step S20 further includes: performing association degree analysis on the point position where the structured precision data are located according to a preset association model, and determining association point positions, association size rings and history improvement experience; generating a correlation degree analysis result according to a tree structure and a list structure according to the point position of the structured precision data, the correlation point position, the correlation dimension ring and the history improvement experience; and determining abnormal data, influence degree and associated data of the abnormal data according to the association degree analysis result.
It is easy to understand that the point positions can be selected, the point positions where the structured precision data are located are subjected to association degree analysis according to a preset association model, association point positions, association size rings and history improvement experience are automatically searched, the association point positions are displayed in a tree structure and a list structure, and a conclusion is given according to the contribution degree of the size rings.
It should be understood that the correlation analysis may also be performed on the point where the structural accuracy data is located, and referring to fig. 7, fig. 7 is a schematic diagram of the correlation analysis in the method for managing the dimensional accuracy data of the automobile according to the present invention. Two points with data can be selected for calculation according to various statistical models such as a binary linear regression equation, and a two-dimensional formula calculation relationship is obtained.
Furthermore, in order to monitor abnormal data more intuitively, the data monitoring can be performed by combining the measuring point diagram and the data view, the abnormal data can be captured more timely and accurately, and the reliability and the accuracy of data monitoring management are improved. Therefore, the step S20 further includes: generating a measuring point diagram and a data view diagram according to the structured precision data, wherein the measuring point diagram and the data view diagram are used for displaying the data fluctuation condition; and carrying out real-time monitoring analysis on the structured precision data according to the test point diagram and the data view diagram, and determining abnormal data, influence degree and associated data of the abnormal data according to analysis results.
It can be understood that a measuring point diagram and a data view diagram can be generated according to the structured precision data, the measuring point diagram can be connected with the measuring point position through a self-defined measuring point frame, the measuring point frame comprises statistical information such as trend diagrams, CPs, CPKs, variances, extremely bad and the like of measuring points, fluctuation conditions of the latest measuring point data are visually displayed, and abnormal real-time monitoring is achieved. The data view is similar to a common measuring table, comprises measuring point information, position pictures and measuring point data, and monitors abnormal data by defining query conditions (date, car body number and sample) and checking the data in real time.
In this embodiment, determining associated dimensional accuracy data of the structured accuracy data according to a preset dimensional chain check model is disclosed; determining the contribution degree of the associated dimensional accuracy data; and when the contribution degree exceeds a contribution degree threshold, determining abnormal data, influence degree and associated data of the abnormal data. The embodiment performs size analysis through the preset size chain check model, determines the contribution degree of the associated size precision data of the structured precision data, can realize comprehensive analysis management of the data, and realizes linkage, intelligent analysis, intelligent decision and intelligent early warning of all the data by defining the size chain relation of various data, thereby realizing rapid analysis of abnormal automatic problems.
Referring to fig. 8, fig. 8 is a flowchart illustrating a third embodiment of a method for managing vehicle dimensional accuracy data according to the present invention.
Further, when abnormal data is found and workers are reminded to carry out correction, whether the abnormal data has faults or not can be firstly inquired in a preset problem record library, if the faults occur, historical problem correction records recorded in the library are added into a problem improvement list, the workers are assisted to locate and solve problems more quickly, the problem correction efficiency is improved, and the period is shortened. Therefore, based on the first embodiment, in the present embodiment, the step S30 includes:
step S301: and determining the early warning level according to the abnormal data and the influence degree.
It can be understood that the early warning level can be determined by the early warning rule, and the system sends early warning information in real time when the data is updated, and meanwhile, single monitoring problem correction is improved through the problem improvement. The early warning rule may be illustrated with reference to fig. 9. For example, the pre-warning rules may include criteria for disagreement, wherein a high-level authority user makes a number of modifications in the criteria, such as criterion 1: the 1 point falls outside zone a (the number of 1 s can be modified) while other rules are set by tolerance. The method can set the applicable early warning rules in the point position configuration, and can set the applicable early warning rules in batches for the point positions (A/B/C) with the same importance.
Step S302: and inquiring a preset problem record library according to the abnormal data, and judging whether a history problem record corresponding to the abnormal data exists in the preset problem record library.
Step S303: if so, generating a problem improvement list according to the early warning level, the historical problem record and the associated data, and monitoring the problem improvement condition.
It should be understood that, a problem record library may be preset for recording problems that have occurred in the history, and in order to speed up the efficiency of problem analysis processing, when abnormal data is detected, the preset problem record library may be queried, and if a corresponding history problem record exists, the history problem record is added to the problem improvement list. The method not only can provide an auxiliary analysis function, but also can enumerate reasons and solutions for the past faults, and arrange relevant reasons and solutions according to the common adoption and effectiveness in a memory bank, so that the problem positioning efficiency is accelerated.
Further, after each occurrence of abnormal data and correction of a problem associated with the abnormal data, the cause of the problem and correction measures can be recorded, and the past failure formation memory bank of each data can be accumulated. When the size deviates again, not only an auxiliary analysis function can be provided, but also the past reasons and the past solutions of the faults can be listed, and the relevant reasons and the relevant solutions are arranged according to the common adoption and the effectiveness in a memory bank, so that the efficiency and the accuracy of data analysis and problem solution are improved. Therefore, after the step S30, the method further includes: acquiring a problem improvement list fed back by a user after problem processing, and extracting problem reasons and correction countermeasures; and generating a problem record according to the problem reason and the rectifying and modifying countermeasure, and adding the problem record into the preset problem record library.
It should be understood that, in order to provide the system with a cumulative analysis function of learning ability, each time the size deviation is ascertained, the cause of the failure and effective corrective measures can be filled in the system. The system accumulates the past fault forming memory library of each size, and when the size is deviated, not only the auxiliary analysis function can be provided, but also the reasons and the solutions of the past faults can be listed, and the relevant reasons and the solutions are arranged according to the common adoption and the effectiveness in the memory library.
Furthermore, the dimensional accuracy system can monitor all abnormal data in real time according to preset rules through unified data management, meanwhile, the early warning problem is subjected to flow monitoring, the abnormal data is comprehensively monitored, zero outflow is realized, and the problem early warning and management efficiency is greatly improved compared with that of manual management. Therefore, the step S30 further includes: determining an early warning level according to the abnormal data and the influence degree; and carrying out color marking on the associated data, generating a problem improvement list according to the early warning level, the associated data and early warning personnel, and monitoring the problem improvement situation.
It should be understood that the definition of the early warning object can be set, the responsible person and the related person who set the point location are taken as early warning personnel, and the system sends early warning information and notifies the related responsible person in real time when the data is updated, and meanwhile, the problem improvement is carried out through the problem improvement single monitoring. And when the system automatically grabs the data, the system performs color identification on the abnormal data according to the early warning model to generate an early warning report. The generated early warning notification can be sent through the communication APP, and the problem improvement flow is sent to the corresponding responsible person for rectification. The method can visually check the related statistics data of the current data early warning, realize the data query of the mobile phone terminal, and solve the trouble that the user must return to the office to query the data when the field problem is handled.
In this embodiment, determining an early warning level according to the anomaly data and the influence degree is disclosed; inquiring a preset problem record library according to the abnormal data, and judging whether a history problem record corresponding to the abnormal data exists in the preset problem record library; if so, generating a problem improvement list according to the early warning level, the historical problem record and the associated data, and monitoring the problem improvement condition. In the embodiment, when the problem improvement list is generated, the history problem records are firstly queried in the preset problem record library, and the queried records are added into the problem improvement list, so that a worker can be assisted to locate and solve the problem more quickly, the problem improvement efficiency is improved, and the period is shortened.
In addition, the embodiment of the invention also provides a storage medium, wherein the storage medium stores an automobile size precision data management program, and the automobile size precision data management program realizes the steps of the automobile size precision data management method when being executed by a processor.
Referring to fig. 10, fig. 10 is a block diagram showing the construction of a first embodiment of an apparatus for managing vehicle dimensional accuracy data according to the present invention.
As shown in fig. 10, an apparatus for managing vehicle dimensional accuracy data according to an embodiment of the present invention includes:
the data integration module 1001 is configured to collect vehicle dimensional accuracy source data, perform structural integration on the vehicle dimensional accuracy source data according to a preset data structure, and store the structural accuracy data;
the data analysis module 1002 is configured to perform real-time monitoring analysis on the structured precision data, and determine abnormal data, an influence degree, and associated data of the abnormal data according to an analysis result;
and the abnormality early warning module 1003 is used for determining an early warning level according to the abnormality data and the influence degree, generating a problem improvement sheet according to the early warning level and the associated data, and monitoring the problem improvement situation.
According to the embodiment, the automobile size precision source data are collected, structured integration is carried out on the automobile size precision source data according to a preset data structure, real-time monitoring analysis is carried out on the structured precision data, and abnormal data, influence degree and associated data of the abnormal data are determined according to analysis results; and determining an early warning level according to the abnormal data and the influence degree, generating a problem improvement list according to the early warning level and the associated data, and monitoring the problem improvement situation. According to the method and the device for monitoring the vehicle body accuracy, the vehicle size accuracy data are uniformly managed, the accuracy data are monitored and analyzed in real time, abnormal data, influence degree and associated data are determined, and the problem list is generated to perform early warning and correction monitoring on the abnormal data, so that the efficiency and accuracy of data management and analysis can be improved, the problem can be rapidly analyzed and corrected, and the stability of the vehicle body accuracy is improved.
Based on the above-described first embodiment of the vehicle dimensional accuracy data management device of the present invention, a second embodiment of the vehicle dimensional accuracy data management device of the present invention is proposed.
In this embodiment, the data analysis module 1002 is further configured to determine associated dimensional accuracy data of the structured accuracy data according to a preset dimensional chain checking model; determining the contribution degree of the associated dimensional accuracy data; and when the contribution degree exceeds a contribution degree threshold, determining abnormal data, influence degree and associated data of the abnormal data.
As an implementation manner, the data analysis module 1002 is further configured to perform association degree analysis on the point location where the structured precision data is located according to a preset association model, so as to determine an association point location, an association size ring and a history improvement experience; generating a correlation degree analysis result according to a tree structure and a list structure according to the point position of the structured precision data, the correlation point position, the correlation dimension ring and the history improvement experience; and determining abnormal data, influence degree and associated data of the abnormal data according to the association degree analysis result.
As an implementation manner, the data analysis module 1002 is further configured to generate a measurement point map and a data view chart according to the structured precision data, where the measurement point map and the data view chart are used for displaying a data fluctuation situation; and carrying out real-time monitoring analysis on the structured precision data according to the test point diagram and the data view diagram, and determining abnormal data, influence degree and associated data of the abnormal data according to analysis results.
As an implementation manner, the anomaly early warning module 1003 is further configured to determine an early warning level according to the anomaly data and the influence degree; inquiring a preset problem record library according to the abnormal data, and judging whether a history problem record corresponding to the abnormal data exists in the preset problem record library; if so, generating a problem improvement list according to the early warning level, the historical problem record and the associated data, and monitoring the problem improvement condition.
As an implementation manner, the anomaly early warning module 1003 is further configured to obtain a problem improvement list fed back by a user after the problem is processed, and extract a cause of the problem and a countermeasure for correction; and generating a problem record according to the problem reason and the rectifying and modifying countermeasure, and adding the problem record into the preset problem record library.
As an implementation manner, the anomaly early warning module 1003 is further configured to determine an early warning level according to the anomaly data and the influence degree; and carrying out color marking on the associated data, generating a problem improvement list according to the early warning level, the associated data and early warning personnel, and monitoring the problem improvement situation.
Other embodiments or specific implementation manners of the vehicle dimensional accuracy data management device of the present invention may refer to the above method embodiments, and will not be described herein.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as described above, comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (10)
1. A method for managing dimensional accuracy data of an automobile, the method comprising:
collecting automobile size precision source data, carrying out structural integration on the automobile size precision source data according to a preset data structure, and storing the structural precision data;
carrying out real-time monitoring analysis on the structured precision data, and determining abnormal data, influence degree and associated data of the abnormal data according to analysis results;
and determining an early warning level according to the abnormal data and the influence degree, generating a problem improvement list according to the early warning level and the associated data, and monitoring the problem improvement situation.
2. The method for managing automotive dimensional accuracy data according to claim 1, wherein the real-time monitoring and analyzing the structured accuracy data, determining abnormal data, a degree of influence, and associated data of the abnormal data based on the analysis result, comprises:
determining associated dimensional accuracy data of the structured accuracy data according to a preset dimensional chain checking model;
determining the contribution degree of the associated dimensional accuracy data;
and when the contribution degree exceeds a contribution degree threshold, determining abnormal data, influence degree and associated data of the abnormal data.
3. The method for managing automotive dimensional accuracy data according to claim 1, wherein the real-time monitoring and analyzing the structured accuracy data, determining abnormal data, a degree of influence, and associated data of the abnormal data based on the analysis result, comprises:
performing association degree analysis on the point position where the structured precision data are located according to a preset association model, and determining association point positions, association size rings and history improvement experience;
generating a correlation degree analysis result according to a tree structure and a list structure according to the point position of the structured precision data, the correlation point position, the correlation dimension ring and the history improvement experience;
and determining abnormal data, influence degree and associated data of the abnormal data according to the association degree analysis result.
4. The method for managing automotive dimensional accuracy data according to claim 1, wherein the real-time monitoring and analyzing the structured accuracy data, determining abnormal data, a degree of influence, and associated data of the abnormal data based on the analysis result, comprises:
generating a measuring point diagram and a data view diagram according to the structured precision data, wherein the measuring point diagram and the data view diagram are used for displaying the data fluctuation condition;
and carrying out real-time monitoring analysis on the structured precision data according to the test point diagram and the data view diagram, and determining abnormal data, influence degree and associated data of the abnormal data according to analysis results.
5. The method for managing vehicle dimensional accuracy data according to any one of claims 1 to 4, wherein the determining an early warning level based on the abnormality data and the degree of influence, and generating a problem improvement sheet based on the early warning level and the associated data, and monitoring the problem improvement, comprises:
determining an early warning level according to the abnormal data and the influence degree;
inquiring a preset problem record library according to the abnormal data, and judging whether a history problem record corresponding to the abnormal data exists in the preset problem record library;
if so, generating a problem improvement list according to the early warning level, the historical problem record and the associated data, and monitoring the problem improvement condition.
6. The method for managing vehicle dimensional accuracy data according to claim 5, wherein the step of determining an early warning level based on the abnormality data and the degree of influence, generating a problem improvement sheet based on the early warning level and the associated data, and monitoring the problem improvement, further comprises, after the step of:
acquiring a problem improvement list fed back by a user after problem processing, and extracting problem reasons and correction countermeasures;
and generating a problem record according to the problem reason and the rectifying and modifying countermeasure, and adding the problem record into the preset problem record library.
7. The method for managing vehicle dimensional accuracy data according to claim 1, wherein the determining the pre-warning level according to the anomaly data and the degree of influence, and generating the problem improvement sheet according to the pre-warning level and the associated data, and monitoring the problem improvement comprises:
determining an early warning level according to the abnormal data and the influence degree;
and carrying out color marking on the associated data, generating a problem improvement list according to the early warning level, the associated data and early warning personnel, and monitoring the problem improvement situation.
8. An automotive dimensional accuracy data management apparatus, characterized in that the automotive dimensional accuracy data management apparatus comprises:
the data integration module is used for collecting the automobile size precision source data, carrying out structural integration on the automobile size precision source data according to a preset data structure, and storing the structural precision data;
the data analysis module is used for carrying out real-time monitoring analysis on the structured precision data and determining abnormal data, influence degree and associated data of the abnormal data according to analysis results;
and the abnormality early warning module is used for determining an early warning level according to the abnormality data and the influence degree, generating a problem improvement list according to the early warning level and the associated data, and monitoring the problem improvement situation.
9. An automotive dimensional accuracy data management apparatus, characterized in that the apparatus comprises: a memory, a processor, and a vehicle dimensional accuracy data management program stored on the memory and executable on the processor, the vehicle dimensional accuracy data management program configured to implement the steps of the vehicle dimensional accuracy data management method of any one of claims 1 to 7.
10. A storage medium having stored thereon a vehicle dimensional accuracy data management program which, when executed by a processor, implements the steps of the vehicle dimensional accuracy data management method according to any one of claims 1 to 7.
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