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Application of three-parameter Weibull mixture model for reliability assessment of NC machine tools: a case study

To analyse the reliability of numerical control (NC) machine tools, a three-parameter Weibull mixture model is proposed in this case study. Negative log-likelihood function is used as an optimal objective instead of solving complex system of equations; the problem of parameter estimation of mixture model is solved by a non-linear programming method. A comprehensive criteria, which include Akaike information criterion, Bayesian information criterion, and root mean squared error, is presented for selecting the number of components of mixture model. The field failure data of three NC machine tools are analysed and the results of reliability assessment, such as the reliability, maintainability, availability, etc., are all presented. The results show that the mixture model of three-parameter Weibull distribution, with advantages over other Weibull models, is suitable for modelling failure data of multiple NC machine tools with multiple failure modes and causes.