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Stochastic model of reliability for use in the evaluation of the economic impact of a failure using life cycle cost analysis. Case studies on the rail freight and oil industries

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  • Carlos Parra
  • Adolfo Crespo
  • Fredy Kristjanpoller
  • Pablo Viveros

Abstract

This paper aims to investigate the technical and economic factors related to failure costs (non-reliability costs) within the life cycle cost analysis (LCCA) of a production asset. Life cycle costing is a well-established method for the evaluation of alternative asset options. It is a structured approach that addresses all the elements of this cost and can be used to produce a spend profile for an asset over its anticipated life-span. The results of an LCCA are used to assist management in the decision-making process when there is a choice of options. The main costs can be classified as the capital expenditure incurred when the asset is purchased, and the operating expenditure incurred during the asset’s life. This paper explores different aspects related to the failure costs within the LCCA, and describes the most important aspects of the stochastic model: a non-homogeneous Poisson process. This model is used to estimate the frequency of failures and their impact which can cause various failures in the total costs of a production asset. This paper also contains a case study for the rail freight industry (Chile) and the oil industry (Petronox, Venezuela) where the proposed model and concepts are applied, and respectively compared in terms of results. Finally, the presented model provides maintenance managers with a decision tool that optimizes the LCCA of an asset and increases the efficiency of the decision-making process related to the control of failures.

Suggested Citation

  • Carlos Parra & Adolfo Crespo & Fredy Kristjanpoller & Pablo Viveros, 2012. "Stochastic model of reliability for use in the evaluation of the economic impact of a failure using life cycle cost analysis. Case studies on the rail freight and oil industries," Journal of Risk and Reliability, , vol. 226(4), pages 392-405, August.
    • Handle: RePEc:sae:risrel:v:226:y:2012:i:4:p:392-405
    DOI: 10.1177/1748006X12441880
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    References listed on IDEAS

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    1. Louit, D.M. & Pascual, R. & Jardine, A.K.S., 2009. "A practical procedure for the selection of time-to-failure models based on the assessment of trends in maintenance data," Reliability Engineering and System Safety, Elsevier, vol. 94(10), pages 1618-1628.
    2. Veber, B. & Nagode, M. & Fajdiga, M., 2008. "Generalized renewal process for repairable systems based on finite Weibull mixture," Reliability Engineering and System Safety, Elsevier, vol. 93(10), pages 1461-1472.
    3. J. I. Ansell & M. J. Phillips, 1989. "Practical Problems in the Statistical Analysis of Reliability Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 38(2), pages 205-231, June.
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    Cited by:

    1. Orlando Durán & Paulo Andrés Durán, 2019. "Prioritization of Physical Assets for Maintenance and Production Sustainability," Sustainability, MDPI, vol. 11(16), pages 1-17, August.

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