Bayesian reliability modeling and assessment solution for NC machine tools under small-sample data

被引:0
作者
Zhaojun Yang
Yingnan Kan
Fei Chen
Binbin Xu
Chuanhai Chen
Chuangui Yang
机构
[1] Jilin University,College of Mechanical Science and Engineering
[2] Jilin University,Key Laboratory of CNC Equipment Reliability Technique of Machinery Industry
来源
Chinese Journal of Mechanical Engineering | 2015年 / 28卷
关键词
NC machine tools; reliability; Bayes; mean time between failures(MTBF); grid approximation; Markov chain Monte Carlo(MCMC);
D O I
暂无
中图分类号
学科分类号
摘要
Although Markov chain Monte Carlo(MCMC) algorithms are accurate, many factors may cause instability when they are utilized in reliability analysis; such instability makes these algorithms unsuitable for widespread engineering applications. Thus, a reliability modeling and assessment solution aimed at small-sample data of numerical control(NC) machine tools is proposed on the basis of Bayes theories. An expert-judgment process of fusing multi-source prior information is developed to obtain the Weibull parameters’ prior distributions and reduce the subjective bias of usual expert-judgment methods. The grid approximation method is applied to two-parameter Weibull distribution to derive the formulas for the parameters’ posterior distributions and solve the calculation difficulty of high-dimensional integration. The method is then applied to the real data of a type of NC machine tool to implement a reliability assessment and obtain the mean time between failures(MTBF). The relative error of the proposed method is 5.8020×10-4 compared with the MTBF obtained by the MCMC algorithm. This result indicates that the proposed method is as accurate as MCMC. The newly developed solution for reliability modeling and assessment of NC machine tools under small-sample data is easy, practical, and highly suitable for widespread application in the engineering field; in addition, the solution does not reduce accuracy.
引用
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页码:1229 / 1239
页数:10
相关论文
共 71 条
  • [1] Yang Z(2013)Progress in the research of reliability technology of machine tools[J] Journal of Mechanical Engineering 49 130-139
  • [2] Chen C(1982)Reliability analysis of CNC machine tools[J] Reliability Engineering 3 449-473
  • [3] Chen F(1995)Probability distribution of machining center failures[J] Reliability Engineering and System Safety 50 121-125
  • [4] Keller A Z(2013)Reliability analysis of machining center based on the field data[J] Eksploatacja i Niezawodnosc 15 147-155
  • [5] Kamath A R R(2012)Likelihood ratio test interval estimation of reliability indices for numerical control machine tools[J] Journal of Mechanical Engineering 48 9-15
  • [6] Perera U D(2013)Quantitative modeling and application of CNC machine failure distribution curve[J] Journal of Chongqing University 36 119-123
  • [7] Jia Y(2005)Sectional model involving two Weibull distributions for CNC lathe failure probability[J] Journal of Beijing University of Aeronautics and Astronautics 31 766-769
  • [8] Wang M(2006)Bias correction for the least squares estimator of Weibull shape parameter with complete and censored data[J] Reliability Engineering and System Safety 91 930-939
  • [9] Jia Z(1997)In search of convenient techniques for reducing bias in the estimation of Weibull parameters for uncensored tests[J] IEEE Transactions on Dielectrics and Electrical Insulation 4 306-313
  • [10] Yang Z(2004)Bayesian analysis of launch vehicle success rates[J] Journal of Spacecraft and Rockets 41 93-102