Research On Job Scheduling Optimization And Simulation For The Dressing Area Of A Automobile Seat Foaming Production Lin

In the new period,the upgrading and transformation of the auto parts industry is accelerating,and cost reduction and efficiency increase have become the key for auto parts enterprises to make breakthroughs in the fierce market competition.The production of auto parts is characterized by many varieties,complex orders and strict delivery time.This paper takes a mixed-flow production line of a car seat foaming workshop as the research object,studies the latest achievements and development trends of job scheduling research of mixed-flow production line at home and abroad.Combined with the current situation of the enterprise and the actual demand of the enterprise,this paper puts forward a research topic which aims at reducing the completion time,reducing the delivery delay,reducing the station load and reducing the amount of energy consumption around reducing cost and increasing efficiency.Through analyzing the current situation of the current car seat foam production,as well as the domestic and international mainstream fuzzy multi-objective and dynamic multi-objective workshop scheduling system research method,set up according to the characteristics of car seat foam finishing homework fuzzy scheduling model,the needle problem was designed based on the model the dominate the NSGA-II algorithm of genetic algorithm,The optimal solution set was obtained by solving the research model.Digital simulation technology is used to verify the effect of the optimal scheduling scheme.The research results have important scientific significance and practical value.The main research findings of this book are as follows:(1)Conducted field investigation and analysis on the current production of automobile seat foam,and obtained the current status evaluation of the seat foam production line.For hours that exist in the foaming process uncertain characteristics,combined with the traditional flexible jobshop scheduling problem model and characteristics,set up under the work hours of fuzzy comprehensive consideration including minimizing the completion time,minimizing tardiness,the minimum total load,and minimize the power consumption of a mathematical model of multiobjective flexible job shop scheduling problem.(2)The basic process and characteristics of the standard NSGA-II algorithm are analyzed.Aiming at the defect of the unstable convergence process of the conventional NSGA-II algorithm,the principle of self-adaptive balance is introduced to realize the automatic adjustment of the crossover and mutation process,so as to avoid the problem that the convergence process is too fast and easy to fall into the local solution and the convergence is too slow,which leads to low solution efficiency.The elite reservation strategy based on distributed function enriches the diversity of the population,preserves the high quality single objective solution,and improves the quality of the parent population solution.The improved NSGA-II algorithm is compared with conventional NSGA-II algorithm and GA algorithm through a standard calculation example.The results show that the improved NSGA-II algorithm has obvious advantages in solving efficiency and solving quality compared with the previous two algorithms.(3)Analytic hierarchy process(AHP)is applied to select the most satisfactory job scheduling scheme from the optimal solution set to meet the actual demands of the current enterprise load.The parameters of the car seat production system are modeled through digital simulation technology.The optimal satisfactory scheduling scheme is imported into the simulation model and the effect of the optimal scheduling scheme is confirmed through simulation.The feasibility and effectiveness of the optimization scheme are verified by comparing with the current situation of production scheduling before optimization.