Research On Production Scheduling And Handling Of Urgent Order Change In A Welding Shop Of A Car Company

At present,the "small batch,multi-variety" mixed-flow production method has become the mainstream production method of automobile manufacturers,which brings consumers more choices of personalized automobile matching,and also allows automobile manufacturers to gain more profit in the process of satisfying the market.In the production of automobiles,the welding workshop is an on-line workshop,which is of great significance to the normal progress of the automobile production plan.There are problems such as low production and processing efficiency,inability to deliver the bodyin-white on time according to the schedule,and poorly balanced component consumption.The current scheduling method has a large space for optimization.This article studies the scheduling and scheduling of a welding workshop of a company.This article studies the scheduling of a company’s welding shop.This article takes the welding workshop of a certain company as the research object to study the scheduling optimization problem of the welding workshop and the dynamic scheduling problem after an emergency order change event occurs in the normal welding process.Aiming at the optimization of the welding workshop’s production scheduling,combined with the actual production process of minimizing the maximum completion time,minimizing the delivery delay and the balanced production goal of parts consumption,a production scheduling optimization model containing three goals is established.As for the three emergency order change events,emergency cancellation,emergency insertion,and emergency advance in production,this article establishes a window-based dynamic scheduling model with the goal of minimizing the maximum completion time.In order to solve the established multi-objective scheduling model,this article designs an improved multi-objective genetic algorithm to solve the model.In the normalization of multiple goals,the fuzzy analytic hierarchy process(FAHP)is used to transform multiple goals into a single goal,and four production scheduling modes are designed,namely,comprehensive mode,efficiency priority mode,on-time delivery priority mode,and parts Consumption equalization priority mode;in the cross-mutation probability calculation method,an adaptive calculation method of the individual crossmutation probability based on the population fitness value is designed,which can better jump out of the local optimal solution and prevent premature maturity;In terms of mutation and crossover methods,a hybrid mutation method that mixes three operations of crossover,reverse order,and insertion,and a multipoint crossover method(IPOX)are designed to improve the efficiency of searching for better solutions.In order to verify the quality of the solution,this article designs two types of experiments for scheduling optimization and dynamic scheduling,and at the same time establishes a Plant Simulation model of the mixed flow welding workshop to simulate and verify the experimental results.Taking a certain batch production plan in the welding workshop as an example,a production scheduling optimization experiment and a dynamic scheduling experiment are designed.We use Siemens Plant Simulation to establish a virtual production line in the welding workshop,and simulate and verify the results of the solution.According to the solution results,compared with the optimization of the traditional genetic algorithm,the improved genetic algorithm minimizes the maximum completion time by 4.8%,minimizes the On-time delivery time by 18.2%,and optimizes the balance of parts consumption by 55.6%;In the dynamic scheduling of emergency cancellation,emergency insertion,and emergency advance events,the optimal optimization is 3.9%,3.4%,and 5.4%,respectively.