What is it about?
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 the desired delay. The non-stationary demand can cause a dead stock i.e. an obsolescence risk. The latter two types of risk generate 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.
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Why is it important?
In this paper, we show the utility of Bayesian networks as reliable tool to model the spare parts inventory management.
Perspectives
Finally, in our future works, we will test the proposed model on an appropriate application, in another manner, we pass to the programming of the model which will allow to compare the obtained results with the previous one in the existent works. Moreover, we envisage in future work to compare this approach with another one.
oumaima bounou
Universite Sidi Mohamed Ben Abdallah
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This page is a summary of: Bayesian model for spare parts management, April 2017, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.1109/logistiqua.2017.7962899.
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