Bayesian model for spare parts management

The inventory management amelioration is influenced by Several factors such as the inventory consolidation, the supply flexibility, the quality and the transmission speed of information. The important factors influencing the stock, the purchase decision and the quantity to buy are the supply time and the demand. The first factor may cause the shortage risk if it has exceeded a desired delay. The non-stationary demand can cause a dead stock i.e. an obsolescence risk. The latter two types of risk generate an additional costs for the purchasing and storage costs. To avoid these costs, these risks have to be known with high precision. Furthermore, Bayesian networks are among the tools used in risk management. In this paper, we show the utility of Bayesian networks as reliable tool to model the spare parts inventory management.