Joint optimization of spare parts inventory and maintenance policies using genetic algorithms


Ilgin M. A., Tunali S.

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, vol.34, pp.594-604, 2007 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 34
  • Publication Date: 2007
  • Doi Number: 10.1007/s00170-006-0618-z
  • Journal Name: INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.594-604
  • Keywords: genetic algorithms, inventory, maintenance, simulation, spare parts, SIMULATION OPTIMIZATION, SYSTEM, METHODOLOGY
  • Dokuz Eylül University Affiliated: No

Abstract

In general, the maintenance and spare parts inventory policies are treated either separately or sequentially in industry. However, since the stock level of spare parts is often dependent on the maintenance policies, it is a better practice to deal with these problems simultaneously. In this study, a simulation optimization approach using genetic algorithms (GAs) has been proposed for the joint optimization of preventive maintenance (PM) and spare provisioning policies of a manufacturing system operating in the automotive sector. A factorial experiment was carried out to identify the best values for the GA parameters, including the probabilities of crossover and mutation, the population size, and the number of generations. The computational experiments showed that the parameter settings given by the proposed approach achieves a significant cost reduction while increasing the throughput of the manufacturing system.