Generalized Accelerated Failure Time Frailty Model for Systems Subject to Imperfect Preventive Maintenance

Imperfect preventive maintenance (PM) activities are very common in industrial systems. For condition-based maintenance (CBM), it is necessary to model the failure likelihood of systems subject to imperfect PM activities. In this paper, the models in the field of survival analysis are introduced into CBM. Namely, the generalized accelerated failure time (AFT) frailty model is investigated to model the failure likelihood of industrial systems. Further, on the basis of the traditional maximum likelihood (ML) estimation and expectation maximization (EM) algorithm, the hybrid ML-EM algorithm is investigated for the estimation of parameters. The hybrid iterative estimation procedure is analyzed in detail. In the evaluation experiment, the generated data of a typical degradation model are verified to be appropriate for the real industrial processes with imperfect PM activities. The estimates of the model parameters are calculated using the training data. Then, the performance of the model is analyzed through the prediction of remaining useful life (RUL) using the testing data. Finally, comparison between the results of the proposed model and the existing model verifies the effectiveness of the generalized AFT frailty model.

[1]  Jiajia Zhang,et al.  An alternative estimation method for the accelerated failure time frailty model , 2007, Comput. Stat. Data Anal..

[2]  H. Pham,et al.  Invited reviewImperfect maintenance , 1996 .

[3]  D. Clayton,et al.  Multivariate generalizations of the proportional hazards model , 1985 .

[4]  N. Balakrishnan,et al.  Remaining Useful Life Estimation Based on a Nonlinear Diffusion Degradation Process , 2012 .

[5]  Zhanshan Ma,et al.  Survival Analysis Approach to Reliability, Survivability and Prognostics and Health Management (PHM) , 2008, 2008 IEEE Aerospace Conference.

[6]  Donglin Zeng,et al.  Efficient Estimation for the Accelerated Failure Time Model , 2007 .

[7]  Andrew K. S. Jardine,et al.  Optimizing a mine haul truck wheel motors’ condition monitoring program Use of proportional hazards modeling , 2001 .

[8]  Lee-Jen Wei,et al.  The accelerated failure time model: a useful alternative to the Cox regression model in survival analysis. , 1992, Statistics in medicine.

[9]  W Pan,et al.  Using Frailties in the Accelerated Failure Time Model , 2001, Lifetime data analysis.

[10]  Rong Li,et al.  Residual-life distributions from component degradation signals: A Bayesian approach , 2005 .

[11]  David R. Cox,et al.  Some Remarks on the Analysis of Survival Data , 1997 .

[12]  Matthew Knuiman,et al.  A hybrid ML-EM algorithm for calculation of maximum likelihood estimates in semiparametric shared frailty models , 2002 .

[13]  Hongguang Li,et al.  Control-limit preventive maintenance policies for components subject to imperfect preventive maintenance and variable operational conditions , 2011, Reliab. Eng. Syst. Saf..

[14]  M-Y You,et al.  Residual life prediction of repairable systems subject to imperfect preventive maintenance using extended proportional hazards model , 2012 .

[15]  Daming Lin,et al.  A review on machinery diagnostics and prognostics implementing condition-based maintenance , 2006 .

[16]  Xiao-Sheng Si,et al.  Nonlinear Degradation Process Modeling and Remaining Useful Life Estimation Subject to Measurement Error: Nonlinear Degradation Process Modeling and Remaining Useful Life Estimation Subject to Measurement Error , 2014 .

[17]  Si Xiao,et al.  Nonlinear Degradation Process Modeling and Remaining Useful Life Estimation Subject to Measurement Error , 2013 .

[18]  Sami El-Ferik,et al.  Age-based hybrid model for imperfect preventive maintenance , 2006 .

[19]  Maarten-Jan Kallen,et al.  Modelling imperfect maintenance and the reliability of complex systems using superposed renewal processes , 2011, Reliab. Eng. Syst. Saf..

[20]  Dragan Banjevic,et al.  Using principal components in a proportional hazards model with applications in condition-based maintenance , 2006, J. Oper. Res. Soc..

[21]  J P Klein,et al.  Semiparametric estimation of random effects using the Cox model based on the EM algorithm. , 1992, Biometrics.

[22]  Huairui Guo,et al.  Predicting remaining useful life of an individual unit using proportional hazards model and logistic regression model , 2006, RAMS '06. Annual Reliability and Maintainability Symposium, 2006..

[23]  D.,et al.  Regression Models and Life-Tables , 2022 .