Integration of Real-Time Demand Information and Spare Parts Distribution Planning for the Optimization of Spare Parts Supply in After-Sales Service Networks

Abstract

Accurate spare parts demand planning and effective distribution planning is essential for providers of after-sales services in the machine and plant engineering industry to ensure high spare parts availability for maintenance and failure orders (callouts) at a reasonable cost. Low spare parts availability is primarily the result of high uncertainty in spare parts demand, leading to misallocation of parts within aftersales service networks. The lack of spare parts availability causes equipment downtime, resulting in customer dissatisfaction and possible penalty costs for after-sales service providers, if response times are contractually fixed. This paper proposes an approach and planning methods for integrating real-time status information about equipment utilization and service conditions to determine optimal spare parts stocking strategies. For this purpose, spare parts stocking strategies and ordering policies for application in after-sales service networks are analyzed. Furthermore, a binary linear optimization model is developed for the assignment of stocking strategies to spare parts based on real-time demand information of the equipment to be serviced. This method uses data provided by an internationally operating elevator company.