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A System-Approach for Recoverable Spare Parts Management Using the Discrete Weibull Distribution

Author

Listed:
  • Riccardo Patriarca

    (Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Via Eudossiana, 18-00184 Rome, Italy)

  • Tianya Hu

    (Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Via Eudossiana, 18-00184 Rome, Italy)

  • Francesco Costantino

    (Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Via Eudossiana, 18-00184 Rome, Italy)

  • Giulio Di Gravio

    (Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Via Eudossiana, 18-00184 Rome, Italy)

  • Massimo Tronci

    (Department of Mechanical and Aerospace Engineering, Sapienza University of Rome, Via Eudossiana, 18-00184 Rome, Italy)

Abstract

Optimal spare parts management strategies allow sustaining a system’s availability, while ensuring timely and effective maintenance. Following a systemic perspective, this paper starts from the Multi-Echelon Technique for Recoverable Item Control (METRIC) to investigate the potential use of a Weibull distribution for modelling items’ demand in case of failure. Adapting the analytic formulation of METRIC through a Discrete Weibull distribution, this study originally proposes a METRIC-based model (DW-METRIC) to be used for modelling the stochastic demand in multi-item systems, in order to ensure process sustainability. The DW-METRIC has been tested in a case study related to an industrial plant constituted by 98 items in a passive redundancy configuration. Comparing the results via a simulation model, the outcomes of the study allow defining applicability criteria for the DW-METRIC, in those settings where the DW-METRIC offers more accurate estimations than the traditional METRIC.

Suggested Citation

  • Riccardo Patriarca & Tianya Hu & Francesco Costantino & Giulio Di Gravio & Massimo Tronci, 2019. "A System-Approach for Recoverable Spare Parts Management Using the Discrete Weibull Distribution," Sustainability, MDPI, vol. 11(19), pages 1-15, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:19:p:5180-:d:269402
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    References listed on IDEAS

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    1. Craig C. Sherbrooke, 1968. "Metric: A Multi-Echelon Technique for Recoverable Item Control," Operations Research, INFORMS, vol. 16(1), pages 122-141, February.
    2. A A Syntetos & J E Boylan & J D Croston, 2005. "On the categorization of demand patterns," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(5), pages 495-503, May.
    3. Alessandro Barbiero, 2013. "Parameter Estimation for Type III Discrete Weibull Distribution: A Comparative Study," Journal of Probability and Statistics, Hindawi, vol. 2013, pages 1-10, September.
    4. Costantino, Francesco & Di Gravio, Giulio & Tronci, Massimo, 2013. "Multi-echelon, multi-indenture spare parts inventory control subject to system availability and budget constraints," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 95-101.
    5. Stephen C. Graves, 1985. "A Multi-Echelon Inventory Model for a Repairable Item with One-for-One Replenishment," Management Science, INFORMS, vol. 31(10), pages 1247-1256, October.
    6. Costantino, Francesco & Di Gravio, Giulio & Patriarca, Riccardo & Petrella, Lea, 2018. "Spare parts management for irregular demand items," Omega, Elsevier, vol. 81(C), pages 57-66.
    7. Romeijnders, Ward & Teunter, Ruud & van Jaarsveld, Willem, 2012. "A two-step method for forecasting spare parts demand using information on component repairs," European Journal of Operational Research, Elsevier, vol. 220(2), pages 386-393.
    8. Nowicki, David R. & Randall, Wesley S. & Ramirez-Marquez, Jose Emmanuel, 2012. "Improving the computational efficiency of metric-based spares algorithms," European Journal of Operational Research, Elsevier, vol. 219(2), pages 324-334.
    9. James D. Englehardt & Ruochen Li, 2011. "The Discrete Weibull Distribution: An Alternative for Correlated Counts with Confirmation for Microbial Counts in Water," Risk Analysis, John Wiley & Sons, vol. 31(3), pages 370-381, March.
    10. Patriarca, Riccardo & Costantino, Francesco & Di Gravio, Giulio & Tronci, Massimo, 2016. "Inventory optimization for a customer airline in a Performance Based Contract," Journal of Air Transport Management, Elsevier, vol. 57(C), pages 206-216.
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    Cited by:

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