Key Subsystem Identification of the CNC Machine Tools

Abstract:

In order to find the key subsystems which affect the reliability of the CNC machine tools is an important and yet harder problem due to the lack of failure data and statistical analysis. A novel method based on posterior probability function for identifying the key subsystems of the CNC machine tools was proposed. Firstly, subsystem reliability of the CNC machine tools was estimated using the John estimator, since the failure data were censored. Secondly, parametric fitting was conduct with Weibull distribution using the maximum likelihood estimation (MLE) or the least square estimation (LSE). Thirdly, the probability function of each subsystems were attained by the reliability modes of the systems and the whole system. Finally, a case study was given, which proved that the proposed method could find out the key subsystems rapidly and accurately.

• Periodical: Applied Mechanics and Materials (Volume 329)
• Pages: 157-162
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.329.157
• Online since: June 2013
• Authors: Xiao Cui Zhu, Fei Chen, Xiao Bing Li, Zhao Jun Yang, Ying Nan Kan, Li Ding Wang
• Keywords: CNC Machine Tool, Key Subsystems, Posterior Probability Function, Weibull Distribution

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