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A fully subjective approach to capital equipment replacement

Author

Listed:
  • S Apeland

    (Stavanger University College)

  • P A Scarf

    (University of Salford)

Abstract

The timing of replacement of equipment is dependent on factors like replacement costs, discount factors and differences in productivity, reliability and safety of existing and new equipment. Predictions related to these factors are, however, normally subject to uncertainties, and in this paper we discuss how two subjective approaches to representing uncertainties related to future events—the classical Bayesian approach and the fully subjective approach—can be used as a basis for decision-making about replacement. Some key features of the approaches are discussed, including integration of engineering judgements, uncertainty treatment and type of performance measures to be used. In the fully subjective approach, we advocate the direct subjective assessment of uncertainty in a quantity of interest, which should be observable, with decisions made on the basis of this uncertainty. The fully subjective approach is illustrated using an example in capital equipment replacement.

Suggested Citation

  • S Apeland & P A Scarf, 2003. "A fully subjective approach to capital equipment replacement," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(4), pages 371-378, April.
    • Handle: RePEc:pal:jorsoc:v:54:y:2003:i:4:d:10.1057_palgrave.jors.2601505
    DOI: 10.1057/palgrave.jors.2601505
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    References listed on IDEAS

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    1. Scarf, Philip A. & Martin, Harry H., 2001. "A framework for maintenance and replacement of a network structured system," International Journal of Production Economics, Elsevier, vol. 69(3), pages 287-296, February.
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    Cited by:

    1. Crevecoeur, Jonas & Antonio, Katrien & Verbelen, Roel, 2019. "Modeling the number of hidden events subject to observation delay," European Journal of Operational Research, Elsevier, vol. 277(3), pages 930-944.
    2. P Coolen-Schrijner & F P A Coolen, 2004. "Adaptive age replacement strategies based on nonparametric predictive inference," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(12), pages 1281-1297, December.
    3. Ferreira, Rodrigo J.P. & de Almeida, Adiel Teixeira & Cavalcante, Cristiano A.V., 2009. "A multi-criteria decision model to determine inspection intervals of condition monitoring based on delay time analysis," Reliability Engineering and System Safety, Elsevier, vol. 94(5), pages 905-912.
    4. P Coolen-Schrijner & F P A Coolen & S C Shaw, 2006. "Nonparametric adaptive opportunity-based age replacement strategies," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(1), pages 63-81, January.
    5. Kierulff, Herbert E., 2007. "The replacement decision: Getting it right," Business Horizons, Elsevier, vol. 50(3), pages 231-237.
    6. M Al-Marsumi, 2005. "Modelling some aspects of the maintenance management of the working refractory lining of small electric arc furnaces in the steel industry," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(3), pages 275-285, March.

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    Keywords

    Replacement; Bayesian;

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