A Study Of Balancing And Sequencing Problems Of Mixed-model Automobile Assembly Lines

Without any substantial modification to existing production facilities, mixed-model assembly lines(MMALs) are capable of producing a variety of product models similar in construction and configuration concurrently,provided that MMALs are well balanced and sequenced.MMALs yield customised products and services with the manufacturing cost and response speed which are usually required under mass production.With the diversification and subdivision of the automobile market demand,automakers choose to use MMALs to sharpen their competitive edge.Focusing on the manufacturing in an automaker located in Rizhao,Shandong,the thesis examines the key technological issues that need urgent treatment.Further,the balancing and sequencing problems in MMALs are studied using applicable optimisation algorithms of VNS.The study may benefit automakers with similar MMALs and similar production context.Balancing and sequencing involve in the quantitative decision-making process aiming at improving the performance of MMALs.As the problem size grows,the computational complexity grows on a factorial basis.Thus, VNS-based heuristics were used to solve the following balancing and sequencing problems in MMALs.Balancing of MMALs.Optimisation models maximising production rate and smoothing index are formulated for the designing and operating stage of MMALs, respectively.The PG(precedence graph) model for describing assembly precedence relations is proposed,and precedence matrix and data file are used to implement PG models.Based on the theoretical framework,a Memetic algorithm is devised for solving the proposed balancing model.To verify the balancing model and Memetic algorithm,a case study is given together with a comparative test with Lingo 11.0 package. Sequencing of MMALs.Based on the analysis of the consequence analysis of launching permutation on logistics,setup time,workload and minimal production cycle of MMALs,optimal models minimising material consumption variation, setup time incurred by adjustment for model changing,utility work necessitated by overload of workstations,and total assembly cost are formulated.Finally,8 problems are tested to verify the proposed Memetic algorithm used to solve the multi-criteria model.Systematical optimisation of mixed-model automobile assembly lines.The scope of optimisation is expanded forward from the assembly shop to the paint shop,and the practical constraints including color changes and workload/material balancing in both shops are analysed.According to the impact on optimal solutions,the constraints are classified into soft constraints and hard constraints.The classification enables the model formulation to be more congruent with the practical manufacturing environment.It also facilitates the searching process for feasible solutions that is basically hard with the traditional constraints satisfaction method.To compare the assembly time of optional parts and the assembly capacity of workstations,the concept of ration constraint, which is actually the launching rule for controlling workload bottlenecks,is proposed.At the end of this part,an integer linear programming model with the objective of minimising the total assembly cost is formulated and solved with the improved neighborhood search algorithm.To sum up,the methodology adopted in each optimisation problem is meaningful to the balancing and/or sequencing optimisation of general assembly lines,and is of guiding significance for the optimal configuration and scheduling of similar mixed-model automobile assembly lines.