Research On Mixed-Model Assembly Line’s Sorting Of Many Varieties And Small Batch Based On JIT

Mixed-model assembly lines (MMALS) with many varieties of small quantities are able to respond market quickly in JIT. Enable enterprises to respond quickly to market, which is no longer dependent on the product inventory. Meeting customer demand timely, Minimizing inventory with raw materials, WIP and produced in production system. Because the car’s vehicle production is often difficult to complete within one workshop, which need to go through welding, painting and assembly shop. In order to achieve a smooth production in JIT.Optimization of sorting operations plan has become the key, which in improving plant productivity, keeping production load balancing in workshop and improving product quality.At present, optimization problem about assembly generally focused on a single workshop at home and abroad, whether on mathematical modeling or algorithm. Multi-shop sequencing problem considered is less in JIT. Facing the sorting demand in JIT, In order to achieve a smooth production in welding, painting and assembly shop, Mixed-model assembly line’s problem is researched in JIT, which is based on multi-related workshop.First of all, Production process with welding, painting and assembly shop is analyzed. In order to achieve a balance system in smooth production, sorting model with welding, painting and assembly shop is formulated, which is used to improve the production efficiency of the vehicle. Then AHP and the weighted average method are used to build sorting model with many varieties of small quantities in JIT.Secondly, the sorting model with many varieties of small quantities in JIT is solved with multiple population adaptive genetic algorithm(MPAGA). Improving the searching efficiency of the algorithm by multiple civilian population.In order to ensure the quality of the gene can be shared in the population through immigration operation. Heuristic algorithm to generate the initial populations, ensure that chromosome to meet the requirements of the painting process. Preventing the loss of best individual in the selection process, Roulette selection and elitist strategy are used in selection. Then ensuring quality strategy is used, which improve the ability of the algorithm optimization. By designing adaptive crossover probability and adaptive mutation probability, increasing the diversity of the population process and avoiding the convergence of the algorithm in the evolutionary. Demonstrating the effectiveness of the algorithm by the example in literature .And sorting simulation of multi workshop is completed in FAW JIEFANG AUTOMOTIVE COMPANY.LTD.Lastly, sorting simulation model of MMALs is established, which through the establishment of a global table, the dynamic parameters set and the message trigger mechanism in Flexsim. And analyzing the balance of the production line which by Sorting of MMALS. Further validate the effectiveness, which using MPAGA to solve the MMALS sequencing problem.