Research On Optimization Method Of Multi-variety And Small-batch Flexible Mixing Production Operation

With the steady improvement of the national economic strength and the continuous enhancement of comprehensive national strength,the field of aerospace manufacturing,which is an important economic pillar,is also constantly expanding.In order to continuously improve the comprehensive competitiveness of aerospace enterprises,the management and optimization during the production operations play a vital role.As an important production unit in our country,aerospace enterprises have a fundamentally different way in formulating production plans from other manufacturing enterprises.In this thesis,the optimization research on the production and operation scheduling of aerospace enterprises is carried out to achieve the purpose of improving the production efficiency of the enterprises.This article takes a typical aerospace component manufacturer as the research object.The problem of poor order delivery capacity caused by the aerospace company’s order scheduling is deeply analyzed,and the optimization method of multi-variety and small-batch aerospace companies’ order scheduling is systematically studied.The specific research are as follows.(1)An order production priority evaluation index system is established to evaluate the factors affecting enterprise order production,aiming at the problem of cross-confusion in production management caused by order flattening in multi-order production of enterprises.The weights of different evaluation indicators and the final score of each order are assigned and obtained through the TOPSIS entropy weight method.According to the order of priority,the production conflict during order scheduling can effectively be reduced.(2)In order to solve the problems of order priority differences in the production planning process of aerospace enterprises,the variety of orders and products,and the crossover of process capacity,the order production scheduling model of aerospace enterprises is established with the optimization objectives of minimizing the delay cost,inventory cost and the number of mold change adjustments.The model established belongs to the problem of NP-Hard.Aiming at solving the multi-parameter NP-Hard problem,an improved sparrow search algorithm is proposed and the TOPSIS entropy weight method is used to evaluate the pareto solution scheme.Finally,taking the planning schedule of the aerospace enterprise as an example,the optimization schemes obtained by the improved sparrow search algorithm,the original sparrow search algorithm and the NSGA-Ⅱ algorithm are compared through the TOPSIS entropy weight method to verify the feasibility of the proposed improved algorithm.(3)The software Plant Simulation is applied to realize the simulation of the best scheme obtained from the algorithm improved sparrow search algorithm and NSGA-Ⅱ.In the software,the production layout simulation modeling and process information programming of the actual enterprise are carried out,and the specific scheduling information of the two schemes are input.The change of product value-added rate of different scheduling schemes in the same production simulation state is compared in order to verify the effectiveness of the improved scheme.