Leader-Follower Optimization Of Order Decomposition And Production Sequencing For Bus Mixed-Model Assembly Line

Mixed-model assembly line is a manufacturing method that can respond to the diversified and rapidly-changing market demands,and it has gradually become one of the trends in reforming production methods for manufacturing enterprises.Order decomposition and production sequencing are interacted in a optimization process.Co-optimization of the two under limited resources generates a reasonable order task production plan.The plan is an effective management method for an enterprise to customize its products,maximize the capacity of the mixed-model production line and decrease the product delivery time.This thesis includes the following specifics:This paper firstly details the characteristics and related theories of the mixed-model assembly line,and analyzes the current status of order decomposition and production sequencing in the actual bus production process.According to the field investigation in a local bus company,several aspects that need to be improved are identified,i.e.on-time order delivery,short-cycle manufacturing and full use of the maximum capacity of the production line.Corresponding solutions to those problems are therefore proposed based on the above investigations.According to the proposed improvement solution for order decomposition and production sequencing,an order decomposition optimization model with the delivery time,product quantity and product-line matching degree as inputs is established to maximize both the product urgency and product-line matching degree.Such a solution avoids the economic loss due to the late product delivery,and enables fully using the limited resources to meet the current order tasks.According to the proposed improvement solution for the actual production sequencing problem,a subjective-objective model is established,which takes the manufacturing time and the number of products as inputs,and the production line workload and the number of product switching as objectives in the manufacturing process.The established model have considered objective factors in order to optimize the production line workload and achieve peak cutting during the peak load period.Meanwhile,the model introduces subjective factors,such as the inertia of online operators,and therefore,reduces the error rate due to frequent product switching and maintains the high proficiency of those operators.A genetic algorithm coupled with order decomposition and production sequencing model based on practical engineering problems is designed.Ensure that both the production line workload and the product switching times model for production sequencing are optimized while optimizing the matching degree and emergency degree for order decomposition.Finally,the best order decomposition and production sequencing schemes are obtained.Finally,Development of a mixed-model assembly line production scheduling system based on order decomposition and production sequencing optimization techniques for data management and application analysis.The proposed method in this thesis is validated using a case study about a local bus product line.