Spare Parts Inventory Control Under Markov Modulated Supply Risk
Spare parts supply chains are highly dependent on the dynamics of their installed bases. Varying number of capital products in use strongly affects the non-stationary supply-side risk especially towards the end-of-life of capital products. This supply-side risk presents itself through stochastic lead times coupled with risk of losing the supplier permanently, which we call supply failure. In this paper, we consider Markov modulated random lead time and supply failure probabilities to capture the non-stationarity in supply-side risk. Under no order crossover assumption, we proved that base stock policy is optimal and with certain conditions optimal base stocks levels are monotonic. Also, we conduct a numerical study to understand the value of considering stochastic lead times and supply failure risk in inventory control. Our results indicate that considering supply-side risk can save total discounted costs up-to 51% and increase service levels up-to 21%.
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