CN-121981504-A - Production plan scheduling method and system of MES system

CN121981504ACN 121981504 ACN121981504 ACN 121981504ACN-121981504-A

Abstract

The application belongs to the technical field of production plan scheduling, and discloses a production plan scheduling method and system of an MES system; the method comprises the steps of preprocessing production order data to generate a comprehensive scheduling value priority sequence, sequentially obtaining compatibility merging groups based on the comprehensive scheduling value priority sequence, constructing a scheduling scheme population, calculating multi-objective evolution fitness based on a meeting period satisfaction rate, a switching cost, a work-in-process turnover time and a repair risk index, executing non-dominant sequencing, crowding distance assessment, selection, crossing and mutation operation to generate an optimal scheduling scheme, verifying the optimal scheduling scheme to generate a verification passing scheme set and a verification failing scheme set, returning to re-optimize if the verification failing scheme set is not empty, generating scheduling instructions and issuing and executing if the verification failing scheme set is empty, and improving production scheduling accuracy, shortening an order response period and reducing process switching burden.

Inventors

HUANG FEI
ZHU CONGLIN

Assignees

武汉至简天成科技有限公司

Dates

Publication Date: 20260505
Application Date: 20260408

Claims (10)

1. A production planning scheduling method of an MES system, comprising: analyzing the received N production order data, identifying and classifying compatibility, and generating a comprehensive scheduling value priority sequence; sequentially acquiring compatibility merging groups based on a comprehensive scheduling value priority sequence, constructing a scheduling scheme population, calculating multi-objective evolution fitness based on a meeting rate of a traffic period, switching cost, work-in-process turnaround time and a repair risk index, and executing non-dominant sorting, crowding distance evaluation, selection, crossing and mutation operation to generate an optimal scheduling scheme; Step three, verifying an optimal scheduling scheme, and generating a verification passing scheme set and a verification failing scheme set according to feasibility, stability and performance indexes; And step four, taking the set of the scheme which does not pass the verification as a comprehensive scheduling value priority sequence if the set of the scheme which does not pass the verification is not empty, returning to the step two for execution, and generating and executing scheduling instructions based on the set of the scheme which does not pass the verification if the set of the scheme which does not pass the verification is empty.
2. The method of claim 1, wherein the generating the set of verification-passing and verification-failing schemes comprises: The method comprises the steps of obtaining corresponding production order data aiming at each optimal scheduling scheme, constructing a production order data set, initializing a feasibility identifier, a stability identifier and a performance index identifier to be no, inputting the optimal scheduling scheme and the production order data set into a scheduling scheme evaluation model, and obtaining an evaluation result set comprising a feasibility score, a stability score and a performance index score; The method comprises the steps of respectively comparing a feasibility score, a stability score and a performance index score with corresponding preset thresholds, if the feasibility score, the stability score and the performance index score are larger than the thresholds, setting corresponding marks as yes, judging whether the feasibility mark, the stability mark and the performance index mark are all yes, adding an optimal scheduling scheme into a verification passing scheme set if the feasibility mark, the stability mark and the performance index mark are all yes, and adding the optimal scheduling scheme into a verification failing scheme set if any mark is not.
3. The method for scheduling production plans of an MES system according to claim 1, wherein the generating method of the optimal scheduling scheme includes: Each compatible combination group is obtained from the comprehensive scheduling value priority sequence, and a scheduling scheme population is initialized for each compatible combination group, wherein each scheduling scheme comprises a batch production sequence, a process switching scheme, a production time scheme and a resource allocation strategy; And performing binary tournament selection according to the comprehensive congestion distance index, performing mapping crossover and random variation to generate a child scheduling scheme, combining the parent and child scheduling schemes to form a new scheduling scheme population, iterating to the preset maximum iteration times, and selecting the scheduling scheme with the maximum comprehensive congestion distance index from the first-layer pareto optimal front edge as an optimal scheduling scheme.
4. The method of claim 1, wherein the method of calculating the multi-objective evolutionary fitness comprises: Calculating to obtain a crossing expiration sufficient rate based on the constructed crossing satisfaction rate objective function; Calculating to obtain switching cost based on the constructed switching cost objective function; calculating the work-in-process turnaround time based on the constructed work-in-process turnaround time objective function; calculating to obtain a repair risk index based on the constructed repair risk index objective function; and calculating to obtain the multi-objective evolutionary fitness based on the meeting rate of the exchange period, the switching cost, the turnover time of the product and the repair risk index.
5. A method of scheduling production plans for an MES system according to claim 3, wherein the method of obtaining the Q-layer pareto ordering structure comprises: S300, setting the initial value of Q to be 1 and the value range of Q to be 1 to Q; S301, marking a first scheduling scheme and a second scheduling scheme for any pair of scheduling schemes aiming at all scheduling schemes in a scheduling scheme population; If the meeting rate, the switching cost, the work-in-process turnaround time and the objective function value of the repair risk index of the first scheduling scheme are all superior to those of the second scheduling scheme, and the multi-objective evolutionary fitness of the first scheduling scheme is greater than that of the second scheduling scheme, judging that the first scheduling scheme dominates the second scheduling scheme; Counting the number of each scheduling scheme which is governed by other scheduling schemes, marking the number as the governed number, and marking the scheduling scheme with the governed number of 0 as the q-th layer pareto optimal front; taking the optimal front edge of the Q-th layer pareto as the Q-th layer of the Q-layer pareto ordering structure; Removing a scheduling scheme corresponding to the q-th layer pareto optimal front edge from the scheduling scheme population; Let q=q+1, if Q is smaller than Q, return to S301 to continue execution, if Q is greater than Q, end the current flow.
6. A method for scheduling a production plan of an MES system according to claim 3, wherein the method for calculating the comprehensive congestion distance index of the scheduling scheme corresponding to the pareto optimal front of each layer comprises: Sequentially obtaining the optimal front edges of the paretos of each layer from the pareto sequencing structure, respectively determining the number of scheduling schemes in the optimal front edges of each layer, sequencing in ascending order according to the multi-objective evolutionary fitness of the scheduling schemes to form an optimal front edge sequence of the paretos, calculating congestion distance increment according to the objective function numerical value difference of adjacent scheduling schemes aiming at each scheduling scheme in the optimal front edge sequence of the paretos, and accumulating the congestion distance increment in each objective function dimension to obtain a corresponding comprehensive congestion distance index.
7. The method for scheduling production plans of an MES system according to claim 1, wherein the method for acquiring the comprehensive scheduling value priority sequence comprises: Carrying out data preprocessing on the received N production order data; extracting a process route identifier corresponding to each production order data, merging the production orders with the same process route identifier into the same process route group to form Y process route groups; executing a predefined process compatibility determination rule on the production orders in each process route group to form M compatibility merging groups; Performing comprehensive scheduling value evaluation based on the production order data corresponding to the M compatible merging groups to obtain comprehensive scheduling value scores corresponding to the M compatible merging groups; and sorting the M compatible merging groups in a descending order according to the corresponding comprehensive scheduling value scores to form a comprehensive scheduling value priority sequence.
8. The method of claim 7, wherein the forming the M compatible merge groups comprises: Acquiring a product process parameter set of each production order in each process route group, summarizing the product process parameter sets of the same group, and constructing a group process parameter set; Comparing the technological parameter indexes of any two production orders in each grouping technological parameter set item by item, calculating the technological parameter similarity, marking the technological parameter similarity as a compatible order pair and generating a compatible label if the technological parameter similarity is higher than a preset technological parameter similarity threshold value, judging whether the compatible label is matched with the compatible label of the existing compatible merging group, adding the compatible order pair into the corresponding compatible merging group if the compatible label is matched with the compatible label, and creating a compatible merging group and distributing the compatible label if the compatible label is not matched with the compatible label, so that M compatible merging groups are finally formed.
9. A method of scheduling production plans for an MES system according to claim 1, wherein the method of generating scheduling instructions based on a verification-passing scheme set and executing includes: For each optimal scheduling scheme in the verification passing scheme set, the corresponding batch production sequence, process switching plan, production time plan and resource allocation strategy are extracted, structured packaging is carried out based on a predefined production scheduling instruction template to form a scheduling execution instruction file, and the scheduling execution instruction file is automatically issued to a manufacturing execution system and an execution unit for execution.
10. A production plan scheduling system of an MES system for implementing a production plan scheduling method of an MES system according to any one of claims 1 to 9, comprising: The order preprocessing module is used for carrying out systematic analysis, compatibility identification, automatic classification and combination processing on the received N production order data to form a standardized comprehensive scheduling value priority sequence; The scheduling optimization module sequentially acquires all compatible merging groups based on the comprehensive scheduling value priority sequence, constructs a scheduling scheme population comprising a batch production sequence, a process switching plan, a production time plan and a resource allocation strategy, performs multi-objective evolutionary adaptability calculation, non-dominant sorting and crowding distance assessment by using a meeting rate of a delivery period, a switching cost, a work-in-process turnover time and a reworking risk index, and generates an optimal scheduling scheme through binary tournament selection, crossover and mutation operation iteration; The scheduling scheme verification module is used for verifying the optimal scheduling scheme output by the scheduling optimization module in real time, evaluating feasibility, stability and performance indexes of the optimal scheduling scheme under actual production conditions, and generating a scheme set passing verification and a scheme set failing verification; and the instruction generation and issuing module takes the non-passing scheme set as a comprehensive scheduling value priority sequence and returns to the scheduling optimization module for execution if the non-passing scheme set is not empty, and generates and executes the scheduling instruction based on the non-passing scheme set if the non-passing scheme set is empty.

Description

Production plan scheduling method and system of MES system Technical Field The invention relates to the technical field of production plan scheduling, in particular to a production plan scheduling method and system of an MES system. Background Under the mode of multi-variety small-batch production, manufacturing enterprises generally face challenges such as urgent production order delivery, complex and diverse process routes, limited resource allocation, higher repair risk and the like. The existing production planning scheduling method generally adopts a scheduling strategy based on rules or a priority ordering mode based on single indexes, and combines limited process compatibility judgment and experience adjustment to carry out production task scheduling. The partial scheduling system has the functions of order merging and batch ordering, but the partial scheduling system is mostly dependent on a linear evaluation model with fixed weight, lacks the collaborative optimization capability of multiple targets such as the exchange period, the switching cost, the turnover time, the quality reliability and the like, and is difficult to consider the global balance of the performance and the production efficiency of the exchange period under the complex order environment. In the prior art, as the multi-objective evolutionary scheduling algorithm and the process parameter similarity grouping method cannot be integrated, the scheduling scheme often has defects in the aspects of batch process compatibility, meeting rate of the exchange period, repairing risk and the like, so that the process switching complexity in the production process is increased, the order response period is prolonged, and the utilization rate of production line resources is reduced. In addition, the existing scheduling scheme lacks automatic closed-loop association with a production verification link, the scheduling result is directly executed without verification, production bottlenecks and plan failures are easily caused, and comprehensive requirements on production plan scheduling scientificity and execution stability in a high-flexibility production environment are difficult to meet. Therefore, there is a need for a production plan scheduling method capable of optimizing, merging batch compatibility and verifying closed loops based on multi-objective evolution, so as to improve scheduling accuracy, shorten order response period, and reduce process switching burden and rework risk. In view of the above, the present invention provides a method and system for scheduling production plans of an MES system to solve the above-mentioned problems. Disclosure of Invention In order to overcome the defects in the prior art and achieve the purposes, the invention provides a production plan scheduling method of an MES system, which comprises the following steps: analyzing the received N production order data, identifying and classifying compatibility, and generating a comprehensive scheduling value priority sequence; sequentially acquiring compatibility merging groups based on a comprehensive scheduling value priority sequence, constructing a scheduling scheme population, calculating multi-objective evolution fitness based on a meeting rate of a traffic period, switching cost, work-in-process turnaround time and a repair risk index, and executing non-dominant sorting, crowding distance evaluation, selection, crossing and mutation operation to generate an optimal scheduling scheme; Step three, verifying an optimal scheduling scheme, and generating a verification passing scheme set and a verification failing scheme set according to feasibility, stability and performance indexes; And step four, taking the set of the scheme which does not pass the verification as a comprehensive scheduling value priority sequence if the set of the scheme which does not pass the verification is not empty, returning to the step two for execution, and generating and executing scheduling instructions based on the set of the scheme which does not pass the verification if the set of the scheme which does not pass the verification is empty. Further, the method for generating the verification passing scheme set and the verification failing scheme set comprises the following steps: The method comprises the steps of obtaining corresponding production order data aiming at each optimal scheduling scheme, constructing a production order data set, initializing a feasibility identifier, a stability identifier and a performance index identifier to be no, inputting the optimal scheduling scheme and the production order data set into a scheduling scheme evaluation model, and obtaining an evaluation result set comprising a feasibility score, a stability score and a performance index score; The method comprises the steps of respectively comparing a feasibility score, a stability score and a performance index score with corresponding preset thresholds, if the feasibility score, the stability sc