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Planning performance based contracts considering reliability and uncertain system usage

Author

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  • T Jin

    (Texas State University, TX, USA)

  • P Wang

    (Hamilton Sundstrand Power Systems, CA, USA)

Abstract

This paper investigates a novel quantitative approach for planning and contracting performance-based logistics in the presence of uncertain system usage. Our efforts focus on an integrated service delivery environment where the manufacturer develops capital-intensive systems and also provides after-sales support. We propose an analytical model to characterize system operational availability by comprehending five performance drivers: inherent failure rate, usage rate, spare parts inventory, repair time, and the fleet size. This analytical insight into the system performance allows the service supplier to minimize the total cost across system design, production, maintenance, and repair. Two contracting schemes are investigated under cost minimization and profit maximization schemes. For the first time in literature, reliability design and service parts logistics are seamlessly integrated into one decision support model for improving operational availability while lowering the lifecycle cost. Numerical examples are provided to demonstrate the applicability and the effectiveness of the proposed decision support tool.

Suggested Citation

  • T Jin & P Wang, 2012. "Planning performance based contracts considering reliability and uncertain system usage," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 63(10), pages 1467-1478, October.
    • Handle: RePEc:pal:jorsoc:v:63:y:2012:i:10:p:1467-1478
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    Citations

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    Cited by:

    1. Jin, Tongdan & Tian, Zhigang & Xie, Min, 2015. "A game-theoretical approach for optimizing maintenance, spares and service capacity in performance contracting," International Journal of Production Economics, Elsevier, vol. 161(C), pages 31-43.
    2. Xian Zhao & Jing Zhang & Xiaoyue Wang, 2019. "Joint optimization of components redundancy, spares inventory and repairmen allocation for a standby series system," Journal of Risk and Reliability, , vol. 233(4), pages 623-638, August.
    3. Patra, Pradipta & Kumar, U. Dinesh & Nowicki, David R. & Randall, Wesley S., 2019. "Effective management of performance-based contracts for sustainment dominant systems," International Journal of Production Economics, Elsevier, vol. 208(C), pages 369-382.
    4. Yoo, Seung Ho & Cheong, Taesu, 2018. "Quality improvement incentive strategies in a supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 331-342.
    5. Wang, Jingjing & Zhao, Xian & Guo, Xiaoxin, 2019. "Optimizing wind turbine's maintenance policies under performance-based contract," Renewable Energy, Elsevier, vol. 135(C), pages 626-634.
    6. Qianru Ge & Willem van Jaarsveld & Zümbül Atan, 2020. "Optimal redesign decisions through failure rate estimates," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(4), pages 254-271, June.
    7. Korkeamäki, Lauri & Kohtamäki, Marko & Parida, Vinit, 2021. "Worth the risk? The profit impact of outcome-based service offerings for manufacturing firms," Journal of Business Research, Elsevier, vol. 131(C), pages 92-102.
    8. Ge, Qianru & Peng, Hao & van Houtum, Geert-Jan & Adan, Ivo, 2018. "Reliability optimization for series systems under uncertain component failure rates in the design phase," International Journal of Production Economics, Elsevier, vol. 196(C), pages 163-175.
    9. Qin, Xuwei & Jiang, Zhong-Zhong & Sun, Minghe & Tang, Liang & Liu, Xiaoran, 2021. "Repairable spare parts provisioning for multiregional expanding fleets of equipment under performance-based contracting," Omega, Elsevier, vol. 102(C).
    10. Kazemi Zanjani, Masoumeh & Nourelfath, Mustapha, 2014. "Integrated spare parts logistics and operations planning for maintenance service providers," International Journal of Production Economics, Elsevier, vol. 158(C), pages 44-53.

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