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Cost of ownership model for spare engines purchase for the Korean navy acquisition program

Author

Listed:
  • S Y Sohn

    (Yonsei University)

  • Y Kim

    (Yonsei University)

  • B T Kim

    (Yonsei University)

Abstract

Major weapon system acquisition programmes often require high initial purchase cost which can be a burden for the procurement of a highly reliable system. In order to avoid the tendency of acquiring a less expensive weapon system with lower performance, a cost of ownership (COO) model can be applied to assess the lifetime cost of the weapon system. In many existing cost estimation models for weapon systems, the failure rate of the system is assumed to be constant and the functional relationship between the initial purchase cost and maintenance cost is not well defined. In this paper, we propose a revised COO model where random effects models are employed to accommodate the variations of the system failure frequency and repair time. It is expected that our model can contribute to the cost-effective procurement of spare engines for the Korean Navy acquisition programme within the limited national defence budget.

Suggested Citation

  • S Y Sohn & Y Kim & B T Kim, 2009. "Cost of ownership model for spare engines purchase for the Korean navy acquisition program," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(12), pages 1674-1682, December.
  • Handle: RePEc:pal:jorsoc:v:60:y:2009:i:12:d:10.1057_jors.2008.147
    DOI: 10.1057/jors.2008.147
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    References listed on IDEAS

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    1. S Y Sohn & H Choi, 2006. "Random effects logistic regression model for data envelopment analysis with correlated decision making units," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(5), pages 552-560, May.
    2. S Y Sohn, 2006. "Random effects logistic regression model for ranking efficiency in data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(11), pages 1289-1299, November.
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    4. Sohn, So Young & Kim, Hong Sik, 2007. "Random effects logistic regression model for default prediction of technology credit guarantee fund," European Journal of Operational Research, Elsevier, vol. 183(1), pages 472-478, November.
    5. K B Yoon & S Y Sohn, 2007. "Forecasting both time varying MTBF of fighter aircraft module and expected demand of minor parts," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(6), pages 714-719, June.
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    7. E Angelelli & M G Speranza, 2002. "The application of a vehicle routing model to a waste-collection problem: two case studies," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(9), pages 944-952, September.
    8. V Lotfi & J Sarkis & J H Semple, 1998. "Economic justification for incremental implementation of advanced manufacturing systems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 49(8), pages 829-839, August.
    9. Kim, Yoonseong & Sohn, So Young, 2008. "Random effects model for credit rating transitions," European Journal of Operational Research, Elsevier, vol. 184(2), pages 561-573, January.
    10. Sohn, So Young & Chang, In Sang & Moon, Tae Hee, 2007. "Random effects Weibull regression model for occupational lifetime," European Journal of Operational Research, Elsevier, vol. 179(1), pages 124-131, May.
    11. Gong, Zhejun, 2008. "An economic evaluation model of supply chain flexibility," European Journal of Operational Research, Elsevier, vol. 184(2), pages 745-758, January.
    12. Sungcheol Yun & So Young Sohn & Youngjo Lee, 2006. "Modelling and estimating heavy-tailed non-homogeneous correlated queues: Pareto-inverse gamma HGLM with covariates," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(4), pages 417-425.
    13. Sohn, So Young & Yoon, Kyung Bok & Chang, In Sang, 2006. "Random effects model for the reliability management of modules of a fighter aircraft," Reliability Engineering and System Safety, Elsevier, vol. 91(4), pages 433-437.
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    Cited by:

    1. Mauro Lizot & Flavio Trojan & Paulo Afonso, 2021. "Combining Total Cost of Ownership and Multi-Criteria Decision Analysis to Improve Cost Management in Family Farming," Agriculture, MDPI, vol. 11(2), pages 1-20, February.
    2. Andrea Bacchetti & Stefano Bonetti & Marco Perona & Nicola Saccani, 2018. "Investment and Management Decisions in Aluminium Melting: A Total Cost of Ownership Model and Practical Applications," Sustainability, MDPI, vol. 10(9), pages 1-36, September.

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