Optimizing capital investments under technological change and deterioration: A case study on MRI machine replacement

ABSTRACT

We study the multiple style and type parallel asset replacement problem (MST-PRES), which determines an optimal policy for keeping or replacing a group of assets that operate in parallel under a limited budget. Operating assets generally suffer from deterioration, which results in high operation and maintenance (O&M) cost and decreased salvage value, and technological improvements make it possible for new assets to operate more efficiently at a lower cost. In order to address these issues, we formulate a multi-objective mixed-integer programming (MIP) model that minimizes fixed and variable costs of purchasing new assets, O&M cost, inventory cost, and penalty cost for unmet demand minus salvage values, while considering technological advances and deterioration as a gain and loss in capacity, respectively. We apply our model to a case study involving two different styles of assets: a full-body magnetic resonance imaging (MRI) machine and a smaller extremity magnetic resonance imaging (eMRI) machine. Each has two types: high-field and low-field. We perform computational experiments and analyses using key model parameters and illustrate optimal replacement strategies considering the impact of technological advances and deterioration. Results show that the proposed MIP model provides valuable insights and strategies for companies, decision makers, and government entities on the capital asset management.

Acknowledgment

We thank Tate Lampe for his help during the initial stage of this research.

Notes on contributors

Emmanuel des-Bordes is a Ph.D. candidate in industrial and manufacturing engineering at Wichita State University. He received his M.S. in industrial engineering in 2011 from New Mexico State University, M.S. degree in statistics from the University of Akron, and M.S. degree in mathematics from Georgia State University. He received his B.S. in mathematics from Kwame Nkrumah University of Science and Technology, Kumasi, Ghana. His research interests include applications of mixed integer programming approaches to 0-1 knapsack and asset replacement problems. He is the recipient of the best paper award at the International Conference on Agriculture, Environment, and Biological Sciences (ICFAE’14) in 2014.

İ. Esra Büyüktahtakin is Assistant Professor in the Department of Industrial and Manufacturing Engineering at Wichita State University. She served the INFORMS Junior Faculty Interest Group (JFIG) in various roles (secretary, vice president, and president) between 2011 and 2015. From 2009 to 2011, Dr. Büyüktahtakın worked as a visiting assistant professor in the Department of Systems and Industrial Engineering at the University of Arizona. She completed her Ph.D. in industrial and systems engineering at the University of Florida in 2009 and holds M.S. degrees from Lehigh University (2007) and Bilkent University (2005). Her areas of expertise include optimization, in particular mixed-integer programming and dynamic programming, with applications in production and logistics planning, sustainability, and capital asset management. Her awards include the 2015 INFORMS Best Publication Award in Environment and Sustainability, the best paper award at the ICFAE’14, NSF EPSCoR First Award, and USDA AFRI grant award. Dr. Büyüktahtakın’s former publication in The Engineering Economist was recognized as a featured article in the Industrial Engineer (IE) magazine of the Institute of Industrial Engineers (IIE) in 2015.

Funding

We gratefully acknowledge the support of the National Science Foundation under grant no. EPS-0903806, the state of Kansas through the Kansas Board of Regents, and the KEEP program at Wichita State University through the Workforce Center of Kansas.