A method for verifying MES data

Abstract

The application discloses a MES data verification method, and relates to the field of MES data verification, which comprises a data receiving step, a storage verification step, a feedback verification step and a comprehensive verification step. The method is characterized in that the data receiving, data storage and data sending of the MES system are comprehensively and systematically analyzed, so that the MES data verification is comprehensive. By excluding the interference of network performance and the limitation of storage devices, the analysis of a single variable is maintained to the maximum extent, the accuracy and effectiveness of the MES data verification result are effectively improved, the corresponding data of decision-making is ensured to be real and reliable, and thus the quality and accuracy of decision-making are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of MES data verification, and in particular to a MES data verification method. BACKGROUND

[0002] MES system relies on accurate data to drive production decisions and process optimization. If the data is inaccurate or has errors, the decisions made based on these data may lead to low production efficiency, waste of resources, and even quality problems. MES system collects and analyzes production data to support decision-making. If the data is not verified, the decisions made based on these data may deviate from the actual situation, leading to decision-making errors. Data verification can ensure that the data corresponding to the decisions is true and reliable, thereby improving the quality and accuracy of the decisions. However, the existing technology has the following shortcomings.

[0003] The existing technology usually adopts the way of one-by-one comparison and confirmation when verifying MES data. This way not only has a large amount of work, but also has low work efficiency, which indirectly reduces the timeliness and effectiveness of MES data verification, and further reduces the accuracy of the MES data verification result.

[0004] The existing technology does not systematically analyze the whole process of data reception, storage and transmission when verifying MES data, which makes the judgment of the MES data verification result one-sided, further reduces the accuracy of the MES data verification result, and is not conducive to driving production decisions and process optimization based on accurate data. SUMMARY

[0005] The purpose of the present application is to provide a MES data verification method to solve the problems raised in the background art.

[0006] To achieve the above purpose, the present application provides the following technical solution: a MES data verification method, comprising:

[0007] Data receiving step: MES receives uploaded data from each work unit to obtain a data receiving set corresponding to the MES;

[0008] Storage verification step: used for data receiving verification and data storage verification of the data receiving set corresponding to the MES, to obtain a preliminary abnormality index corresponding to the MES;

[0009] Feedback verification step: used for feedback verification of the data receiving set corresponding to the MES, to obtain a data feedback abnormality coefficient corresponding to the MES;

[0010] Comprehensive verification step: used for total score analysis according to the MES corresponding preliminary anomaly index and the MES corresponding data feedback anomaly coefficient, to obtain the verification result of the MES data.

[0011] In the preferred embodiment of the present scheme, the data receiving step is specifically implemented as follows:

[0012] Each work unit corresponding to the MES uploads data according to the preset data upload timestamp, and the MES receives the uploaded data set from each work unit through the API interface, and obtains the timestamp of receiving the uploaded data set of each work unit, wherein the uploaded data set includes the data packet corresponding to each work unit, the data upload timestamp, the data volume and the data content, wherein the data content includes work data and feedback data, and the uploaded data set of each work unit received by the MES is recorded as the data receiving set corresponding to the MES.

[0013] In the preferred embodiment of the present scheme, the preliminary verification step is specifically implemented as follows:

[0014] Obtain the network performance data set corresponding to the MES;

[0015] According to the data upload timestamp corresponding to each work unit, the theoretical data receiving total amount of each timestamp corresponding to the MES is obtained;

[0016] Establish a data extraction relationship between the preliminary verification step and the database, extract the theoretical receiving duration of each data total amount corresponding to the network performance data set of the MES stored in the database, and obtain the theoretical receiving duration of each timestamp corresponding to the MES according to the network performance data set corresponding to the MES and the theoretical data receiving total amount of each timestamp corresponding to the MES;

[0017] Obtain the data receiving log of the MES; extract the data receiving log of the MES to obtain the actual data receiving total amount and the actual receiving duration of each timestamp corresponding to the MES;

[0018] The data receiving anomaly index of the MES is calculated by the formula ;

[0019] Extract the database performance set stored in the database, wherein the database performance set refers to the theoretical storage duration corresponding to different storage data amounts;

[0020] Record the actual data receiving total amount of each timestamp corresponding to the MES as the theoretical storage data total amount of each timestamp corresponding to the MES, and obtain the theoretical storage duration of each timestamp corresponding to the MES according to the theoretical storage data total amount of each timestamp corresponding to the MES;

[0021] ​Obtaining the storage log corresponding to the database, performing data filtering and extraction on the storage log corresponding to the database, obtaining the actual data storage total amount corresponding to each timestamp MES and the actual storage duration of the actual data storage total amount corresponding to each timestamp MES;

[0022] The data storage abnormality index corresponding to the MES is calculated by the calculation formula ;

[0023] The preliminary abnormality index corresponding to the MES is calculated by the calculation formula , wherein represents the number of each timestamp, represents the number of timestamps, , , , respectively represent the theoretical data receiving total amount, the theoretical receiving duration, the theoretical data storage total amount and the theoretical storage duration of each timestamp corresponding to the MES, , , , respectively represent the actual data receiving total amount, the actual receiving duration, the actual data storage total amount and the actual storage duration of each timestamp corresponding to the MES, , respectively represent the preset data receiving abnormality index influence factor and the data storage abnormality index influence factor.

[0024] In the preferred embodiment of the present scheme, the feedback verification step is specifically implemented as follows:

[0025] The feedback data corresponding to each work unit includes the timestamp of the last data transmission of the work unit and the latest instruction information set sent by the system to the work unit, wherein the instruction information set includes an instruction sending timestamp and an instruction data set, and the instruction data set includes an instruction data packet, a data volume and instruction content;

[0026] A data extraction relationship is established between the feedback verification step and the database, and the database is extracted according to the timestamp of the last data transmission of each work unit, to obtain the work data corresponding to the timestamp of the last data transmission of each work unit;

[0027] The work data corresponding to each work unit is analyzed with the work data corresponding to the timestamp of the last data transmission of each work unit, to obtain the actual change amount of each sub-work data corresponding to each work unit;

[0028] ​​extracting a standard data change set corresponding to each work data of each work unit stored in the database and a combination of each work data and instruction content, wherein the data change set includes a standard change amount of each sub-work data, and filtering the standard data change set according to the work data corresponding to a time stamp of the last data transmission of each work unit and the actual instruction content of the latest instruction information set corresponding to each work unit to obtain the standard data change set corresponding to each work unit;

[0029] calculating the data change difference coefficient corresponding to each work unit by the calculation formula , and recording the work data difference coefficient corresponding to each work unit as , wherein represents the number of each sub-work data, represents the number of sub-work data categories, , respectively represents the standard change amount and the actual change amount corresponding to each sub-work data, represents the work data difference coefficient influence factor;

[0030] obtaining the corresponding instruction sending log of the MES, and performing data filtering on the instruction sending log of the MES according to the sending time stamp of the latest instruction information set sent by the system to the work unit to obtain the actual instruction content of the latest instruction information set corresponding to each work unit, wherein the instruction content refers to each control project;

[0031] matching the actual instruction content of the latest instruction information set corresponding to each work unit with the instruction content in the feedback data corresponding to each work unit to obtain each control missing project and the number of control missing projects in the instruction content in the feedback data corresponding to each work unit; and statistically obtaining the proportion of the number of control missing projects to the total number of control projects corresponding to the actual instruction content;

[0032] calculating the data transmission abnormality index of the MES by the calculation formula ;

[0033] calculating the data feedback abnormality coefficient of the MES by the calculation formula , wherein represents the number of each work unit, represents the number of work unit categories, , respectively represents the number of control missing projects in the instruction content in the feedback data corresponding to each work unit and the proportion of the number of control missing projects to the total number of control projects corresponding to the actual instruction content, represents the preset data transmission abnormality index influence factor.

[0034] In the preferred embodiment of the present scheme, the comprehensive verification step is specifically implemented as follows:

[0035] The comprehensive data deviation coefficient of the MES is calculated by the following formula ;

[0036] The comprehensive data deviation coefficient of the MES is compared with the preset comprehensive data deviation coefficient threshold value. If the comprehensive data deviation coefficient of the MES is less than or equal to the preset comprehensive data deviation coefficient threshold value, it indicates that the MES passes the data verification and the MES is in normal working condition, and the MES is not processed. The MES passing the data verification and the MES being in normal working condition is recorded as the verification result of the MES data. If the comprehensive data deviation coefficient of the MES is greater than the preset comprehensive data deviation coefficient threshold value, it indicates that the MES fails the data verification and the MES is in an abnormal working condition, and the MES is processed accordingly. The MES failing the data verification and the MES being in an abnormal working condition is recorded as the verification result of the MES data.

[0037] Compared with the prior art, the present application has the following advantages:

[0038] The present application comprehensively analyzes the data receiving, data storage and data sending corresponding to the MES system, so that the MES data verification is comprehensive, thereby increasing the accuracy and effectiveness of the MES data verification result.

[0039] The present application excludes the interference of network performance and the limitation of storage devices, maximally maintains the analysis of single variable, effectively improves the accuracy and effectiveness of the MES data verification result, ensures that the data corresponding to the decision is real and reliable, and thereby improves the quality and accuracy of the decision. BRIEF DESCRIPTION OF DRAWINGS

[0040] The present application will be further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present application. Other drawings can be obtained by those skilled in the art without creative labor.

[0041] Figure 1 The present application will be further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present application. Other drawings can be obtained by those skilled in the art without creative labor. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the present application will be described clearly and completely with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.​

[0043] Referring to Figure 1 The application provides a MES data verification method, which comprises a data receiving step, a storage verification step, a feedback verification step and a comprehensive verification step.

[0044] The data receiving step is connected with the storage verification step and the feedback verification step, the storage verification step is connected with the comprehensive verification step, and the feedback verification step is connected with the comprehensive verification step.

[0045] The data receiving step receives uploading data from each work unit to obtain a data receiving set corresponding to the MES.

[0046] Further, the specific execution mode of the data receiving step is as follows:

[0047] Each work unit corresponding to the MES uploads data according to a preset data uploading timestamp, and the MES receives the uploading data set from each work unit through an API interface to obtain a timestamp of receiving completion of the uploading data set of each work unit, wherein the uploading data set comprises a data packet corresponding to each work unit, a data uploading timestamp, a data volume and data content, wherein the data content comprises work data and feedback data, and the uploading data set of each work unit received by the MES is recorded as a data receiving set corresponding to the MES.

[0048] It should be noted that the data volume refers to the data size of the data packet, for example, 2 kb or 1 mb, and the data content refers to the specific content of the data packet, for example, monitoring data of a monitoring device or progress data of a work device.

[0049] The storage verification step is used for data receiving verification and data storage verification on the data receiving set corresponding to the MES to obtain a preliminary abnormality index corresponding to the MES.

[0050] Further, the specific execution mode of the preliminary verification step is as follows:

[0051] The network performance data set corresponding to the MES is obtained.

[0052] The data uploading timestamps corresponding to each work unit are counted to obtain a theoretical total data receiving amount of each timestamp corresponding to the MES.

[0053] A data extraction relationship between the preliminary verification step and the database is established to extract the theoretical receiving time length of each data total amount corresponding to each network performance data set of the MES stored in the database, and the theoretical receiving time length of each timestamp corresponding to the MES is obtained according to the network performance data set corresponding to the MES and the theoretical total data receiving amount of each timestamp corresponding to the MES.

[0054] acquire a data receiving log of the MES; perform data extraction on the data receiving log of the MES to obtain actual data receiving total amounts and actual receiving time lengths of the MES corresponding to respective timestamps;

[0055] The data receiving abnormality index of the MES is calculated by the following formula ;

[0056] extract a database performance set stored in the database, wherein the database performance set refers to theoretical storage time lengths corresponding to different stored data amounts;

[0057] record the actual data receiving total amounts of the MES corresponding to respective timestamps as the theoretical data storage total amounts of the MES corresponding to respective timestamps, and filter the theoretical data storage total amounts of the MES corresponding to respective timestamps to obtain theoretical storage time lengths of the MES corresponding to respective timestamps;

[0058] acquire a storage log corresponding to the database, perform data filtering extraction on the storage log corresponding to the database to obtain actual data storage total amounts of the MES corresponding to respective timestamps and actual storage time lengths of the actual data storage total amounts of the MES corresponding to respective timestamps;

[0059] The data storage abnormality index of the MES is calculated by the following formula ;

[0060] The preliminary abnormality index of the MES is calculated by the following formula , wherein represents the number of the respective timestamps, represents the number of the timestamps, , , , respectively represent theoretical data receiving total amounts, theoretical receiving time lengths, theoretical data storage total amounts and theoretical storage time lengths of the MES corresponding to respective timestamps, , , , respectively represent actual data receiving total amounts, actual receiving time lengths, actual data storage total amounts and actual storage time lengths of the MES corresponding to respective timestamps, , respectively represent preset data receiving abnormality index influence factors and data storage abnormality index influence factors.

[0061] The feedback verification step is configured to perform feedback verification on the data receiving set corresponding to the MES to obtain a data feedback abnormality coefficient of the MES;

[0062] ​​​Further, the specific implementation of the feedback verification step is as follows:

[0063] The feedback data corresponding to each work unit includes a timestamp of the last data transmission of the work unit and a latest instruction information set sent by the system to the work unit, wherein the instruction information set includes an instruction sending timestamp and an instruction data set, and the instruction data set includes an instruction data packet, a data volume, and instruction content;

[0064] A data extraction relationship between the feedback verification step and the database is established, and the database is extracted according to the timestamp of the last data transmission of each work unit, to obtain work data corresponding to the timestamp of the last data transmission of each work unit;

[0065] The work data corresponding to each work unit and the work data corresponding to the timestamp of the last data transmission of each work unit are analyzed, to obtain an actual change amount of each sub-work data corresponding to each work unit;

[0066] It should be noted that the latest instruction information sent by the system to the work unit is obtained by analyzing the work data transmitted by the work unit last time;

[0067] The standard data change set corresponding to the combination of the instruction content and each work data corresponding to each work unit stored in the database is extracted, wherein the data change set includes a standard change amount of each sub-work data, and the standard data change set corresponding to each work unit is obtained by filtering the actual instruction content of the latest instruction information set corresponding to each work unit according to the work data corresponding to the timestamp of the last data transmission of each work unit and each work unit;

[0068] The data change difference coefficient corresponding to each work unit is calculated by the following formula , and is recorded as the work data difference coefficient corresponding to each work unit , wherein represents the number of each sub-work data, represents the number of sub-work data, , represents the standard change amount and the actual change amount of each sub-work data, respectively, represents the work data difference coefficient influence factor;

[0069] The corresponding instruction sending log of the MES is obtained, the instruction sending log corresponding to the MES is filtered according to the sending timestamp of the latest instruction information set sent by the system to the work unit, to obtain the actual instruction content of the latest instruction information set corresponding to each work unit, wherein the instruction content refers to each control project;

[0070] The actual instruction content of each work unit corresponding to the latest instruction information set is matched with the instruction content in the feedback data corresponding to each work unit to obtain each missing control item and the number of missing control items in the instruction content in the feedback data corresponding to each work unit; and the proportion of the number of missing control items to the total number of control items corresponding to the actual instruction content is obtained by statistics;

[0071] It should be noted that: the missing control item refers to the control item in the instruction content in the feedback data that is not in the matching process of the actual instruction content corresponding to each control item.

[0072] The data transmission abnormality index corresponding to the MES is calculated by the calculation formula ;

[0073] The data feedback abnormality coefficient corresponding to the MES is calculated by the calculation formula , wherein represents the number of each work unit, represents the number of work unit types, , respectively represent the number of missing control items in the instruction content in the feedback data corresponding to each work unit and the proportion of the number of missing control items to the total number of control items corresponding to the actual instruction content, represents a preset data transmission abnormality index influence factor.

[0074] The comprehensive verification step is used to perform total score analysis according to the preliminary abnormality index corresponding to the MES and the data feedback abnormality coefficient corresponding to the MES to obtain the verification result of the MES data.

[0075] Further, the specific execution mode of the comprehensive verification step is as follows:

[0076] The comprehensive data deviation coefficient corresponding to the MES is calculated by the calculation formula ;

[0077] ​​​The comprehensive data deviation coefficient corresponding to the MES is compared and analyzed with the preset comprehensive data deviation coefficient threshold value. If the comprehensive data deviation coefficient corresponding to the MES is less than or equal to the preset comprehensive data deviation coefficient threshold value, it indicates that the MES passes the data verification and the MES is in a normal working state, and the MES is not processed. The MES passing the data verification and the MES being in the normal working state is recorded as the verification result of the MES data. If the comprehensive data deviation coefficient corresponding to the MES is greater than the preset comprehensive data deviation coefficient threshold value, it indicates that the MES fails the data verification and the MES is in an abnormal working state, and the MES is processed accordingly. The MES failing the data verification and the MES being in the abnormal working state is recorded as the verification result of the MES data.

[0078] The above are preferred embodiments of the present application, and do not limit the protection scope of the present application. Therefore, equivalent changes made on the basis of the structure, shape, and principle of the present application should be covered within the protection scope of the present application.

Claims

1. A method for verifying MES data, characterized by: Comprise: Data receiving step: MES receives upload data from each work unit to obtain the data receiving set corresponding to the MES; Storage verification step: used for data receiving verification and data storage verification of the data receiving set corresponding to the MES, to obtain the preliminary abnormality index corresponding to the MES; The specific execution mode of the storage verification step is as follows: Obtain the network performance data set corresponding to the MES; According to the data upload timestamp corresponding to each work unit, the theoretical total data receiving amount of each timestamp corresponding to the MES is obtained; Establish a data extraction relationship between the preliminary verification step and the database, extract the theoretical receiving duration of each data total amount corresponding to the MES stored in the database, and obtain the theoretical receiving duration of each timestamp corresponding to the MES according to the network performance data set corresponding to the MES and the theoretical total data receiving amount of each timestamp corresponding to the MES; Obtain the data receiving log of the MES; Data extraction is performed on the data receiving log of the MES to obtain the actual total data receiving amount and the actual receiving duration of each timestamp corresponding to the MES; The data reception abnormality index corresponding to the MES is calculated by the calculation formula ;​ Extract the database efficiency set stored in the database, wherein the database efficiency set refers to the theoretical storage duration corresponding to different storage data amounts; The actual total data receiving amount of each timestamp corresponding to the MES is recorded as the theoretical total data storage amount of each timestamp corresponding to the MES, and the theoretical storage duration of each timestamp corresponding to the MES is obtained according to the theoretical total data storage amount of each timestamp corresponding to the MES; Obtain the storage log corresponding to the database, and perform data filtering extraction on the storage log corresponding to the database to obtain the actual total data storage amount of each timestamp corresponding to the MES and the actual storage duration of the actual total data storage amount of each timestamp corresponding to the MES. The data storage abnormality index corresponding to the MES is calculated by the calculation formula , and is ​ The preliminary abnormal index corresponding to the MES is calculated by a calculation formula , wherein , wherein represents the number of each timestamp, represents the number of timestamps, , , , respectively represent the total amount of theoretical data received, the theoretical receiving duration, the total amount of theoretical data to be stored and the theoretical storage duration of each timestamp corresponding to the MES, , , , respectively represent the total amount of actual data received, the actual receiving duration, the total amount of actual data stored and the actual storage duration of each timestamp corresponding to the MES, , respectively represent the preset data receiving abnormal index influence factor and the data storage abnormal index influence factor. Feedback verification step: used for feedback verification of the data receiving set corresponding to the MES, to obtain the data feedback abnormality coefficient corresponding to the MES; Comprehensive verification step: used for total score analysis according to the preliminary abnormality index corresponding to the MES and the data feedback abnormality coefficient corresponding to the MES, to obtain the verification result of the MES data. 2.The MES data verification method of claim 1, wherein: The specific execution mode of the data receiving step is as follows: Each work unit corresponding to the MES uploads data according to the preset data upload timestamp, and the MES receives the upload data set from each work unit through the API interface to obtain the timestamp of receiving the upload data set of each work unit, wherein the upload data set includes the data packet, data upload timestamp, data amount and data content corresponding to each work unit, and the data content includes work data and feedback data. The upload data set of each work unit received by the MES is recorded as the data receiving set corresponding to the MES. 3.The MES data verification method of claim 2, wherein: The specific execution mode of the feedback verification step is as follows: The feedback data corresponding to each work unit includes the timestamp of the last data transmission of the work unit and the latest instruction information set sent by the system to the work unit, wherein the instruction information set includes the instruction sending timestamp and the instruction data set, and the instruction data set includes the instruction data packet, data amount and instruction content; The data extraction relationship between the feedback verification step and the database is established, and the database is extracted according to the time stamp of the last data transmission of each work unit to obtain the work data corresponding to the time stamp of the last data transmission of each work unit; The corresponding work data of each work unit and the work data corresponding to the time stamp of the last data transmission of each work unit are analyzed to obtain the actual change of each sub-work data corresponding to each work unit; The standard data change set corresponding to the combination of the work data of each work unit stored in the database and the instruction content is extracted, wherein the data change set includes the standard change of each sub-work data, and the actual instruction content of the latest instruction information set corresponding to each work unit is filtered according to the work data corresponding to the time stamp of the last data transmission of each work unit to obtain the standard data change set corresponding to each work unit; The data change difference coefficient corresponding to each work unit is calculated by the calculation formula , and is recorded as the work data difference coefficient corresponding to each work unit , wherein is the number of each sub-work data, is the number of sub-work data, , respectively represents the standard change and the actual change corresponding to each sub-work data, is the work data difference coefficient influence factor; The corresponding instruction sending log of the MES is obtained, and the instruction sending log of the MES is data filtered according to the sending time stamp of the latest instruction information set sent by the system to the work unit to obtain the actual instruction content of the latest instruction information set corresponding to each work unit, wherein the instruction content refers to each control project; The actual instruction content of the latest instruction information set corresponding to each work unit is matched with the instruction content in the feedback data corresponding to each work unit to obtain each control missing project and the number of control missing projects in the instruction content in the feedback data corresponding to each work unit; The proportion of the number of control missing projects to the total number of control projects corresponding to the actual instruction content is obtained. The data transmission abnormality index corresponding to the MES is calculated by the calculation formula ;​ The data feedback abnormality coefficient corresponding to MES is calculated by the calculation formula , wherein , wherein represents the number of each work unit, represents the number of work unit types, , respectively represent the number of control missing items in the instruction content in the feedback data corresponding to each work unit and the proportion of the number of control missing items in the total control items corresponding to the actual instruction content, represents a preset data transmission abnormality index influence factor.

4. The method of claim 3, wherein: The specific execution mode of the comprehensive verification step is as follows: The comprehensive data deviation coefficient corresponding to the MES is calculated by the calculation formula , and is represented as ; The comprehensive data deviation coefficient corresponding to the MES is compared and analyzed with the preset comprehensive data deviation coefficient threshold value, if the comprehensive data deviation coefficient corresponding to the MES is less than or equal to the preset comprehensive data deviation coefficient threshold value, it indicates that the MES passes the data verification and the MES works normally, and the MES is not processed, the MES passes the data verification and the MES works normally is recorded as the verification result of the MES data, if the comprehensive data deviation coefficient corresponding to the MES is greater than the preset comprehensive data deviation coefficient threshold value, it indicates that the MES does not pass the data verification and the MES is in an abnormal working state, the MES is processed accordingly, and the MES does not pass the data verification and the MES is in an abnormal working state is recorded as the verification result of the MES data.

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