A demand classification scheme for spare part inventory model subject to stochastic demand and lead time |
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| Authors: | Samuel Vieira Conceição Gerson Luis Caetano da Silva Dawei Lu Nilson Tadeu Ramos Nunes Guilherme Corteletti Pedrosa |
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| Institution: | 1. Industrial Engineering Department, Universidade Federal de Minas Gerais, Av. Presidente Ant?nio Carlos, 6627, CEP 31270-901 Belo Horizonte, MG, Brazilsvieira@dep.ufmg.br;3. ArcelorMittal, Belo Horizonte, MG, Brazil;4. WMG International Manufacturing Centre, University of Warwick, UK;5. Transport and Geotechnical Department, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil;6. Industrial Engineering Department, Universidade Federal de Minas Gerais, Av. Presidente Ant?nio Carlos, 6627, CEP 31270-901 Belo Horizonte, MG, Brazil |
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| Abstract: | 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. |
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| Keywords: | inventory control spare parts MRO – maintenance repair and operating items steel industry |
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