Optimizing Critical Spare Parts and Location Based on the Conditional Value-At-Risk Criterion

Abstract

This article considers the problem of managing the risks associated with random equipment failures by optimizing decisions regarding the quantity and placement of critical spares over a network of related industrial sites. To develop the model and provide a practical example, we focus on the allocation of electrical transformer spares for a large-scale industrial producer, such as a mining company or chemical manufacturer, operating several different sites across a geographic region. In particular, we consider the risk of financial loss due to interrupted business and lost production following an unexpected transformer failure. A two-stage stochastic integer programming model with a conditional value-at-risk (CVaR) criterion to incorporate risk aversion is developed. Computational results are presented to illustrate the advantages of the CVaR approach compared to a corresponding expected cost minimization approach. The CVaR model results in policies that have lower loss than the corresponding risk neutral model since, at sufficiently high risk aversion levels, the CVaR model introduces the acquisition of more spares as a hedge against catastrophic scenarios.

Additional information

Notes on contributors

Stephan A. Trusevych

Stephan A. Trusevych is an MA.Sc. candidate at the Centre for Maintenance Optimization and Reliability Engineering (C-MORE) in the Department of Mechanical and Industrial Engineering at the University of Toronto. He holds a B.Sc. in mathematics and engineering from Queen's University in Kingston, Ontario, Canada. Prior to joining C-MORE, Stephan spent 4 years at an engineering consulting company where his responsibilities included the design and construction of high-voltage power systems for the mining and metals industry.

Roy H. Kwon

Roy H. Kwon is an associate professor in the Department of Mechanical and Industrial Engineering at the University of Toronto. He obtained his Ph.D. in operations Research at the University of Pennsylvania. His primary focus is in operations research (mathematical programming) with applications in financial engineering and supply chain management. He is also a member of the faculty in the Mathematical Finance Department. Dr. Kwon has experience in operations research consulting in the defense, financial, and management consulting industries.

Andrew K. S. Jardine

Andrew K. S. Jardine is Professor Emeritus and director of the Centre for Maintenance Optimization and Reliability Engineering at the University of Toronto. He obtained his Ph.D. in engineering production from the University of Birmingham, England. Professor Jardine's teaching and research focuses on the optimization of engineering asset management decisions. He is a Fellow of IIE and the Canadian Academy of Engineering.