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A parameter estimation method for machine tool reliability analysis using expert judgement

Author

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  • Bhupesh Kumar Lad
  • Makarand S. Kulkarni

Abstract

This paper aims at providing a parameter estimation method for the machine tool reliability analysis to overcome the problem of unavailability of a well-defined failure data collection mechanism. It uses the knowledge and experience of maintenance personnel to obtain the parameters of lifetime distribution of the repairable as well as non-repairable components/subassemblies. It is further developed for the cases where the knowledge available with the expert is with reference to the preventive repair/replacement policy used in the field. In case of imperfect repairs, the methodology also helps in estimating the value of restoration factor. The goodness of the proposed methodology at a given accuracy level in expert judgements are tested against the maximum likelihood estimates of the parameters. It is concluded that the expert judgement method provides a satisfactory alternative to statistical methods when no or very few historical time to failure data points are available.

Suggested Citation

  • Bhupesh Kumar Lad & Makarand S. Kulkarni, 2010. "A parameter estimation method for machine tool reliability analysis using expert judgement," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 2(2), pages 155-169.
    • Handle: RePEc:ids:injdan:v:2:y:2010:i:2:p:155-169
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    Citations

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    Cited by:

    1. Rajkumar Bhimgonda Patil & Basavraj S Kothavale & Laxman Yadu Waghmode, 2019. "Selection of time-to-failure model for computerized numerical control turning center based on the assessment of trends in maintenance data," Journal of Risk and Reliability, , vol. 233(2), pages 105-117, April.
    2. Sharma, Pankaj & Kulkarni, Makarand S & Yadav, Vikas, 2017. "A simulation based optimization approach for spare parts forecasting and selective maintenance," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 274-289.

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