Reliability Assessment of Numerical Control Machine Tools Using Weibull Mixture Models

Abstract:

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Weibull distribution is one of the most widely used model in reliability analysis of NC machine tools. In order to assess the reliability of NC machine tool, Generalized Expectation Maximization (GEM) algorithm is used to estimate parameters of mixture Weibull models. Akaike information criterion (AIC) and Bayesian information criterion (BIC) are used as comprehensive criteria to select the number of subpopulations of mixture models. The results show that mixture models are more suitable to assess reliability of NC machine tools than that of single model. Root mean square errors (RMSE) of mixture models reduce by 87.5% than that of single model. Reliability evaluation results of machine tool, such as MTBF etc., are given.

Info:

Periodical:

Advanced Materials Research (Volumes 181-182)

Edited by:

Qi Luo and Yuanzhi Wang

Pages:

161-165

DOI:

10.4028/www.scientific.net/AMR.181-182.161

Citation:

Z. M. Wang and J. G. Yang, "Reliability Assessment of Numerical Control Machine Tools Using Weibull Mixture Models", Advanced Materials Research, Vols. 181-182, pp. 161-165, 2011

Online since:

January 2011

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Price:

$35.00

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