A Stochastic Methodology for the Optimal Management of Infrequent Demand Spare Parts in the Automotive Industry

Abstract

The paper deals with the management of the spare parts in the automotive sector introducing a first definition of business model aimed to reduce holding costs of stocks, focusing on spare parts distributors point of view, and adopting a probabilistic mathematical approach. The management of spare parts is not trivial due to the infrequent profile that characterizes market demand, in contrast with the necessity of the distributors to keep in stock a large number of items (part numbers) in order to avoid lost sales (back ordering is not allowed). Moreover, given that different distributors can deal the same products among the national market, the total amount of stocks of the same products is multiplied along the supply chain. A mathematical approach adopting probabilistic dynamic programming is presented aimed to optimize the management of spare parts, considering the creation of a platform in which different distributors can participate to share the management of items. The main purpose of the model is to find the optimal allocation of products among distributors and, at the same time, ensuring a balancing in the costs that each player has to bear period by period, providing the optimal reorder policy for each product. A numerical example is also reported.