Research On Remanufacturing Process Planning And Scheduling Optimization Models Under Uncertain Environment

Recently,with the rapid development of the manufacturing industry and the increasingly severe global ecological environment,the traditional manufacturing mode is gradually transforming to a green and sustainable manufacturing mode under the guidance of governments and organizations.As an important part of green and sustainable manufacturing mode,remanufacturing has received wide attention from all sectors of the community.Remanufacturing is a general term for a series of engineering activities to repair and modify end-of-life products under the guidance of whole product life cycle design and management.Remanufacturing process planning and shop scheduling are two important sub-problems in the remanufacturing process.Process planning and reprocessing of remanufacturable commponts is the core link of the whole remanufacturing process,and an effective and reasonable shop scheduling plan plays a vital role in improving the efficiency of remanufacturing processing.Compared with traditional manufacturing systems,remanufacturing systems have more uncertainties due to the usage of end-of-life products as raw materials,which makes the remanufacturing process planning and shop scheduling problems more complicated.Currently,remanufacturing process planning and shop scheduling problems are attracting the attention of many researchers.However,in traditional remanufacturing systems,process planning and shop scheduling problems are studied separately,with remanufacturing shop scheduling providing scheduling guidance to the shop based on pre-defined process planning.Although a few researchers have realized that the use of manufacturing resources in the shop scheduling needs to be considered in the process planning stage,and studied the integrated remanufacturing process planning and shop scheduling,the impact of uncertainties in remanufacturing systems has not been well considered.Therefore,in order to overcome the above-mentioned limitations,this thesis studies the remanufacturing process planning and scheduling optimization problem under uncertainties.This study first studies the remanufacturing shop scheduling problem and considers the impact of uncertainties on shop scheduling.An optimization model of remanufacturing shop scheduling under uncertainties is constructed to maximize the efficiency of shop scheduling.On this basis,this thesis studies the integrated remanufacturing process planning and scheduling optimization problem.And an integrated remanufacturing process planning and scheduling model under uncertainties is constructed to improve remanufacturing shop flexibility and processing efficiency.The main innovations of this study are the following two aspects:(1)A remanufacturing shop scheduling model under uncertainties is proposed,which considers the impact of uncertainties on remanufacturing shop scheduling,and minimizes the completion time,energy consumption and mean of earliness and tardiness as the optimization objectives.To solve the proposed model,a criterion selection-based multi-objective approach is employed,and an improved discrete particle swarm optimization algorithm is proposed to solve this model,which incorporates an effective two-dimensional representation scheme,embeds a Nash equilibrium solution evaluation method,employs a global search structure with multiple genetic operators,and applies a local search strategy.Finally,the experiments results demonstrate the effectiveness of the algorithm in solving this model and the system stability of this model.(2)An integrated remanufacturing process planning and scheduling model under uncertainties is proposed,which integrates the remanufacturing process planning and shop scheduling problems into the model and incorporates the uncertainties into it to improve the feasibility and flexibility of the remanufacturing system.To solve the proposed model,a Pareto selection-based multi-objective approach is employed,and an extended non-dominated sorting genetic algorithm-II with a multi-dimensional representation scheme is proposed,an adaptive strategy and a local search strategy are introduced to improve the performance of the algorithm.Finally,the experiments results demonstrate the practicality and effectiveness of the algorithm.The research results of this study are innovation and development in the field of remanufacturing process planning and shop scheduling,and have greater theoretical significance for enriching the research in it.In addition,this study provides some technical support to improve the remanufacturing shop scheduling efficiency.At the same time,it has great practical significance for the development of remanufacturing industry and the sustainability of society.