Optimal decision making for spare part management with time varying demands

Abstract

Controlling spare parts inventory of a product is a major effort to many companies. The problem becomes more challenging when the installed base of the product changes over time. In order to cope with the situation, the inventory value needs to be adjusted according to the resulting non-stationary maintenance demand. This problem is usually encountered when a manufacturer starts selling a new product and agrees to provide spare parts for maintenance. In this research, a special case involving a new non-repairable product with a single spare pool is considered. It is assumed that the new sales follow some popular stochastic processes, and the product.s failure time follows the Weibull distribution or Exponential distribution. The mathematical model for the resulting maintenance demand is formulated and calculated through simulation. Based on the maintenance demand, a dynamic (Q, r) - (lotsize/reorder-point) restocking policy is formulated and solved using a multi-resolution approach. Finally, numerical examples with the objective of minimizing the inventory cost under a service level constraint are provided to demonstrate the proposed methodology in practical use.