CN-121981412-A - MES-based production data management system

CN121981412ACN 121981412 ACN121981412 ACN 121981412ACN-121981412-A

Abstract

The invention discloses a production data management system based on MES, which relates to the technical field of production management, and discloses a log generation module, an active coordination module and a passive coordination module, wherein the log generation module and the active coordination module are arranged to randomly select production data of production equipment in each procedure through a preset proportion, so that the data quantity required to be synchronously analyzed in the production process can be reduced, further the data analysis load of the system is reduced, meanwhile, the selection equipment of the production data is optimized in real time according to the production condition of each order in each procedure, the cooperative production of each order in each procedure is optimized in time, and the passive coordination module is arranged to passively analyze the production condition of the order in the relevant procedure and mark the corresponding procedure when the cooperative production condition does not exist in the procedure, and the production efficiency of the order is optimized through the cooperative production of the orders of other procedures.

Inventors

Lin Liangfang
LI YAJUN
LIN WEIGONG

Assignees

匠想科技(广州)有限公司

Dates

Publication Date: 20260505
Application Date: 20240409

Claims (7)

1. The MES-based production data management system is characterized by comprising a log generation module, an active coordination module and a passive coordination module; The log generation module randomly selects production equipment in each procedure in the MES according to a preset proportion based on a T period and every period node, acquires production data of the selected production equipment, and generates a production log according to the production data; The active coordination module is used for acquiring a production monitoring value of an order number, marking the order number as a high-yield order number or a low-yield order number according to the production monitoring value, preferentially selecting production equipment of the high-yield order number and the low-yield order number in the process based on a preset proportion when a next period node is used, acquiring total times of the same order number as the low-yield order number in the process in n period nodes before the current time of the system, marking the same order number as a DDC, setting a low-yield order number threshold, marking the order number as a target order number when the DDC is greater than or equal to the low-yield order number threshold, marking the same order number as the total times of the high-yield order number in the process in n period nodes before the current time of the system, marking the same order number as the high-yield order number when the GGM is greater than or equal to the high-yield order number threshold, marking the same order number as the high-yield order number in the process node when the GGM is greater than or equal to the high-yield order number threshold, marking the same order number as the assistance order number in the assistance task in the process, marking the assistance order number as the assistance center when the order number is not in the assistance order number; The passive coordination module marks a process related to a central process as a process to be analyzed through knowledge graph analysis of the production process, marks the process to be analyzed as a target process through a minimum path algorithm, acquires a process influence value of the target process, sets a process influence value threshold, marks the target process as an influence process when the process influence value is greater than or equal to the process influence value threshold, and distributes the production task of the central order number in the influence process to production equipment of the auxiliary order number in the influence process when the auxiliary order number exists in the influence process.
2. The MES-based production data management system of claim 1, wherein the production log includes order numbers, actual capacity.
3. The MES-based production data management system according to claim 1, wherein the raw supervision value of the order number is obtained by: obtaining order numbers of production logs, marking a production log system of the same order number of the process under the periodic node as a same-order production log, obtaining high target capacity and low target capacity of production equipment under the corresponding process, marking the same-order production log as a same-order high-yield log when the actual capacity in the same-order production log is larger than or equal to the high target capacity, carrying out difference calculation on the actual capacity and the high target capacity of the same-order high-yield log to obtain a high-yield deviation value, carrying out summation treatment on all the high-yield deviation values to obtain a high-yield deviation total value, marking the high-yield deviation total value as GCZ, obtaining the total number of the same-order production logs as the same-order high-yield logs, marking the same-order production logs as DGB, and when the actual capacity in the same-order production log is smaller than or equal to the low target capacity, the same-order production log is marked as a same-order low-yield log, the difference value between the low target capacity and the actual capacity of the same-order low-yield log is calculated to obtain a low-yield deviation value, all the low-yield deviation values are summed to obtain a low-yield deviation total value, the same-order production log is marked as DPZ, the total number of same-order low-yield logs is obtained, the same-order production log is marked as FBN, when the actual capacity in the same-order production log is between the high target capacity and the low target capacity, corresponding processing is not performed, and the production monitoring value SWE of the order number is obtained by using the formula SWE= GCZ ×a1+DGBa2-DPZ ×a3+FBNxa 4, wherein a1 is a high-yield deviation total value coefficient, a2 is a same-order high-yield number coefficient, a3 is a low-yield deviation total value coefficient, and a4 is a same-order low-yield number coefficient.
4. The MES-based production data management system according to claim 1, wherein the order number is marked as a high-yield order number or a low-yield order number according to the production monitoring value, specifically, the production monitoring value and the production monitoring value are set, the order number is marked as the high-yield order number when the production monitoring value of the order number is larger than or equal to the production monitoring value, the order number is marked as the low-yield order number when the production monitoring value of the order number is smaller than or equal to the production monitoring value, no corresponding processing is performed when the order number is between the production monitoring value and the production monitoring value, and no corresponding processing is performed when the production deviation average value is smaller than the production deviation average value threshold.
5. The MES-based production data management system according to claim 1, wherein the process to be analyzed is marked as a target process by a minimum path algorithm, specifically, a shortest path between the center process and the process to be analyzed is obtained by the minimum path algorithm, a shortest path threshold is set, and when the shortest path between the center process and the process to be analyzed is smaller than the shortest path threshold, the process to be analyzed is marked as the target process.
6. The MES-based production data management system according to claim 1, wherein the process influence value of the target process is obtained by obtaining the production similarity between the center process and the target process of the center order number by using a similarity algorithm and marking the obtained product similarity as QZR, obtaining the shortest path between the center process and the target process and marking the obtained product similarity as ED, and using the formula Obtaining a process influence value of the target process, wherein b1 is a production similarity coefficient, and b2 is a shortest path coefficient.
7. The MES-based production data management system according to claim 6, wherein the production similarity between the center order number and the target procedure is obtained by using a similarity algorithm, specifically, the production monitor value of the center order number in the current period node is obtained, the total number of times that the center order number in the center order number is marked as a low-production order number before the current time of the system is obtained, the total number of times that the center order number in the center order number is marked as a low-production order number in the current period node is marked as A= [ A 1 ,A 2 ],A 1 ], the total number of times that the center order number in the center order number is marked as a low-production order number before the current time of the system is obtained, the total number of times that the center order number in the target procedure is marked as a low-production order number before the current time of the system is obtained, and the total number of times that the center order number in the target procedure is marked as a low-production order number before the current time of the system is marked as B= [ B 1 ,B 2 ],B 1 ] is obtained, and the similarity algorithm is used between the production similarity between the center order number and the target procedure.

Description

MES-based production data management system Technical Field The invention relates to the technical field of production management, in particular to a production data management system based on MES. Background The MES is a production informatization management system oriented to a workshop execution layer of a manufacturing enterprise, and because of the complexity of the production process of the manufacturing enterprise, the MES needs to manage a plurality of working procedures and production equipment, and the production data volume needing to be monitored is large, so that the MES is easy to overload and crash. And because the number of the working procedures and the production equipment which need to be supervised is too large, when the yield of part of working procedures and production equipment is reduced, the system cannot prompt in time, and further, part of orders are affected, so that the management of MES on production data of each order is optimized, smooth production of each order is ensured, and the problem which needs to be solved at present is solved urgently. Disclosure of Invention Aiming at the defects existing in the prior art, the invention aims to provide a production data management system based on MES. In order to achieve the above purpose, the present invention provides the following technical solutions: a MES-based production data management system comprises a log generation module, an active coordination module and a passive coordination module; The log generation module randomly selects production equipment in each procedure in the MES according to a preset proportion based on a T period and every period node, acquires production data of the selected production equipment, and generates a production log according to the production data; The active coordination module is used for acquiring a production monitoring value of an order number, marking the order number as a high-yield order number or a low-yield order number according to the production monitoring value, preferentially selecting production equipment of the high-yield order number and the low-yield order number in the process based on a preset proportion when a next period node is used, acquiring total times of the same order number as the low-yield order number in the process in n period nodes before the current time of the system, marking the same order number as a DDC, setting a low-yield order number threshold, marking the order number as a target order number when the DDC is greater than or equal to the low-yield order number threshold, marking the same order number as the total times of the high-yield order number in the process in n period nodes before the current time of the system, marking the same order number as the high-yield order number when the GGM is greater than or equal to the high-yield order number threshold, marking the same order number as the high-yield order number in the process node when the GGM is greater than or equal to the high-yield order number threshold, marking the same order number as the assistance order number in the assistance task in the process, marking the assistance order number as the assistance center when the order number is not in the assistance order number; The passive coordination module marks a process related to a central process as a process to be analyzed through knowledge graph analysis of the production process, marks the process to be analyzed as a target process through a minimum path algorithm, sets a process influence value threshold, marks the target process as an influence process when the process influence value is greater than or equal to the process influence value threshold, and distributes the production task of the central order number in the influence process to production equipment of the influence process when the auxiliary order number exists in the influence process. Further, the production log includes order numbers and actual capacity. Further, the raw supervision value of the order number is obtained through the following steps: obtaining order numbers of production logs, marking a production log system of the same order number of the process under the periodic node as a same-order production log, obtaining high target capacity and low target capacity of production equipment under the corresponding process, marking the same-order production log as a same-order high-yield log when the actual capacity in the same-order production log is larger than or equal to the high target capacity, carrying out difference calculation on the actual capacity and the high target capacity of the same-order high-yield log to obtain a high-yield deviation value, carrying out summation treatment on all the high-yield deviation values to obtain a high-yield deviation total value, marking the high-yield deviation total value as GCZ, obtaining the total number of the same-order production logs as the same-order high-yield logs, marking the same-order production logs as DGB,