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Managing system obsolescence via multicriteria decision making

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  • Oluwatomi Adetunji
  • John Bischoff
  • Christopher J. Willy

Abstract

Obsolescence occurs when system elements become outdated, and it leads to operational, logistical, reliability, and cost implications. In the U.S. military, this problem is a result of the U.S. Department of Defense's (DoD) departure from Military Specification (MILSPEC) standards in 1994 and transition to the use of Commercial Off the Shelf products. Obsolescence costs the DoD more than $750 million annually. The current risk management tools for obsolescence are based on a quantitative approach that uses cost optimization, and expert judgment is not used as a critical criterion. A review of the literature has revealed that during the design phase of technological systems, there is limited knowledge and a lack of training associated with mitigating obsolescence, and multicriteria decision‐making (MCDM) methods are not currently used to mitigate the risk of obsolescence. Thus, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS, which is a MCDM method) and Monte Carlo simulations are proposed as the foundation for this work. This paper adds to the methodology by introducing an expert judgment criterion. A case study was conducted using military and civilian experts. Expert validation showed that the TOPSIS model successfully identified the best system for mitigating obsolescence. This model can be used by system designers and other decision makers to conduct trade studies in obsolescence management.

Suggested Citation

  • Oluwatomi Adetunji & John Bischoff & Christopher J. Willy, 2018. "Managing system obsolescence via multicriteria decision making," Systems Engineering, John Wiley & Sons, vol. 21(4), pages 307-321, July.
    • Handle: RePEc:wly:syseng:v:21:y:2018:i:4:p:307-321
    DOI: 10.1002/sys.21436
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    1. Georgios K. Koulinas & Olympia E. Demesouka & Konstantinos A. Sidas & Dimitrios E. Koulouriotis, 2021. "A TOPSIS—Risk Matrix and Monte Carlo Expert System for Risk Assessment in Engineering Projects," Sustainability, MDPI, vol. 13(20), pages 1-14, October.
    2. Imen Zaabar & Raul Arango-Miranda & Yvan Beauregard & Marc Paquet, 2021. "A Sustainable Multicriteria Decision Framework for Obsolescence Resolution Strategy Selection," Sustainability, MDPI, vol. 13(15), pages 1-16, August.
    3. Ates, Aylin & Acur, Nuran, 2022. "Making obsolescence obsolete: Execution of digital transformation in a high-tech manufacturing SME," Journal of Business Research, Elsevier, vol. 152(C), pages 336-348.
    4. Jung-Fa Tsai & Chin-Po Wang & Ming-Hua Lin & Shih-Wei Huang, 2021. "Analysis of Key Factors for Supplier Selection in Taiwan’s Thin-Film Transistor Liquid-Crystal Displays Industry," Mathematics, MDPI, vol. 9(4), pages 1-18, February.

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