Research And Development Of Product Configuration And Production Scheduling

With the increasing demand for personalized products and timeliness of orders,customization has gradually become the mainstream production mode in the manufacturing industry,which brings challenges to the enterprises in product configuration management and production scheduling.This paper studied product configuration management and production scheduling based on customization to help enterprises provide personalized product configuration solutions that meet customers' demands and complete the production quickly,which is of great significance to improve the response speed of enterprises to orders and enhance the comprehensive competitiveness of enterprises.The following key techniques were studied:In view of the fact that enterprises fail to provide the product configuration solutions quickly and accurately which meet the customers' personalized demands,this paper studied the product configuration management method: a modular product family model based on GBOM(Generic Bill of Material)with constraints was constructed.After that with customers' personalized demands,a combination of case-based reasoning(CBR)and constraints satisfaction problem(CSP)model was used to solve the problem and generate a product configuration solution and EBOM(Engineering Bill of Material).The mechanism of mapping EBOM to PBOM(Process Bill of Material)/MBOM(Manufacturing Bill of Material)was studied,and then a PBOM-based production scheduling problem model was established.Considering the drawbacks of large dependence on parameters and relapsing into local extremum in basic particle swarm optimization(bPSO),this paper proposed an improved particle swarm optimization algorithm based on chaos technology to solve the multi-order production scheduling problem with the objective of minimizing the makespan.The above approaches have been applied to the automobiles product configuration and production scheduling system,which could generate product configuration solutions and optimized scheduling scheme accurately and rapidly.The feasibility and effectiveness of the proposed approaches have been verified by the automobile industry application,which could also be widely used in other industry based on customization.