Resource Optimization Of After-sales Service Supply Chain In Automobile Industry

Nowadays, as a trend of product homogeneity, manufacturers take after-sales service as a resource of revenue, profits and competition. After-sales service has become an important area for enterprises to capture consumer. However, most enterprises have not notice the difference of after-sales service supply chain and traditional manufacture supply chain, and apply the theory of manufacture supply chain to after-sales management, leading to less effect. So how to manage the after-sales service supply chain in a right way is an important issue nowadays.After-sales service supply chain refers to the whole support activities to ensure the smooth implementation of after-sales service, related to service plans, resource allocation, spare parts management, maintenance and recycling collection and other activities and processes. The object of after-sales service supply chain management is to configure the resource rightly, including service parts and service people. This paper focused on the automotive industry, summarized the exiting lecture on after-sales service supply chain, and analyzed the typical service network of the automotive industry; found out some problems existing in the service network. By implementing the peer transit inventory strategies, it improved the existing network. Based on this, combining the characteristics of whole-set order, it proposed a multi-objective decision model, which minimizes the total cost of the supply chain and the total waiting time. Then we optimized the spare parts inventory and applied the queuing theory to configure the service staffing. Finally, we employed genetic algorithm to solve this problem, and then analyzed how some parameters affects the objective decision-making.