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Optimal tool replacement with product quality deterioration and random tool failure

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  • Weigang Xu
  • Le Cao

Abstract

Operating the machine with a deteriorated cutting tool often leads to poor product quality performance and high risk of tool failure. Replacing the degraded tool is an effective measure to reduce product quality loss and chance of tool failure. Excessive tool replacements, however, may increase the production capacity loss and tool replacement cost. Taking these factors into consideration, this paper presents an approach for determining the optimal tool replacement time for cutting process. It assumes that the product quality deteriorates as cutting tool wears and tool failure occurs randomly during the cutting process. A product quality failure rate model is developed to characterise the deterioration of product quality during the cutting process, and the product quality loss is estimated based on this model. Weibull distribution is employed to describe the stochastic tool life. A tool replacement model is proposed based on balancing the product quality loss, penalty cost for possible tool failure, production capacity loss and tool replacement cost. Sensitivity analysis of the optimal tool replacement decision is presented.

Suggested Citation

  • Weigang Xu & Le Cao, 2015. "Optimal tool replacement with product quality deterioration and random tool failure," International Journal of Production Research, Taylor & Francis Journals, vol. 53(6), pages 1736-1745, March.
    • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:6:p:1736-1745
    DOI: 10.1080/00207543.2014.957878
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    Cited by:

    1. de Jonge, Bram & Jakobsons, Edgars, 2018. "Optimizing block-based maintenance under random machine usage," European Journal of Operational Research, Elsevier, vol. 265(2), pages 703-709.
    2. Lu, Biao & Chen, Zhen & Zhao, Xufeng, 2021. "Data-driven dynamic predictive maintenance for a manufacturing system with quality deterioration and online sensors," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    3. Liu, Bin & Wu, Shaomin & Xie, Min & Kuo, Way, 2017. "A condition-based maintenance policy for degrading systems with age- and state-dependent operating cost," European Journal of Operational Research, Elsevier, vol. 263(3), pages 879-887.

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