Spare parts provisioning decision support model for long lead time spares

• Author / Creator

  Aulakh, Amit

• Large corporations have a significant amount of working capital tied into the acquisition and storage of spare parts. In the industry, spare parts inventory policies and strategies are often developed in isolation from reliability centered maintenance
  practices – this results in significant wasteful direct and indirect cost attached to spare parts management for the equipment operator. This report will focus on developing a methodology for minimizing lifecycle indirect and direct cost that comes from
  storing long lead time spares. A combined Monte-Carlo and Genetic Algorithm based optimization approach to finding the optimal spare parts storage strategy is proposed. In this study, the indirect and direct cost of having a spare part in the storage
  facility will be balanced against the cost of lost opportunity that results from decreased availability - a consequence of not having the required spare part available when an equipment failure event occurs. The results of this study present the benefits
  of optimizing long lead time spares through a joint Monte-Carlo & Genetic Algorithm based approach.

• Subjects / Keywords

  • Montecarlo
  • Genetics
  • Optimization
  • Spares

• Graduation date

  Spring 2011

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R3JQ1F

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.