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A demand classification scheme for spare part inventory model subject to stochastic demand and lead time

2015; Taylor & Francis; Volume: 26; Issue: 16 Linguagem: Inglês

10.1080/09537287.2015.1033497

1366-5871

Samuel Vieira Conceição, Gerson Luis Caetano da Silva, Dawei Lü, Nilson Tadeu Ramos Nunes, Guilherme Corteletti Pedrosa,

Multi-Criteria Decision Making

In this study, we aim to develop a demand classification methodology for classifying and controlling inventory spare parts subject to stochastic demand and lead time. Using real data, the developed models were tested and their performances were evaluated and compared. The results show that the Laplace model provided superior performance in terms of service level, fill rate (FR) and inventory cost. Compared with the current system based on normal distribution, the proposed Laplace model yielded significant savings and good results in terms of the service level and the FR. The Laplace and Gamma optimisation models resulted in savings of 82 and 81%, respectively.