Maintenance policy: degradation laws versus hidden Markov model availability indicator

Today, maintenance strategies and their analyses remain a worrying problem for companies. Socio-economic stakes depending on the competitiveness of each strategy are more than ever linked to the activity and quality of maintenance interventions. A series of specific events can eventually warn the expert of an imminent breakdown. This study aims at understanding such a signature thanks to hidden Markov models. For that purpose, two methods for damage level estimation of a maintained system are proposed. The first consists in using non-parametric and semi-parametric degradation laws (which will be used as references). The second method consists in using a Markovian approach. All proposals are illustrated on two studies corresponding to two real industrial situations (a continuous system for food processing and moulded products in aluminium alloys for the automotive industry).

[1]  Daoud Aït-Kadi,et al.  Performance evaluation of multi-state degraded systems with minimal repairs and imperfect preventive maintenance , 2010, Reliab. Eng. Syst. Saf..

[2]  Charles E Ebeling,et al.  An Introduction to Reliability and Maintainability Engineering , 1996 .

[3]  C. Berridge.  An Introduction to Reliability and Maintainability. , 1984 .

[4]  Maurice Bryson,et al.  Probability, Statistics, and Reliability for Engineers , 1997, Technometrics.

[5]  Nicolas Monmarché,et al.  Hidden Markov Models Training Using Population-based Metaheuristics , 2008, Advances in Metaheuristics for Hard Optimization.

[6]  Antoine Grall,et al.  Sequential condition-based maintenance scheduling for a deteriorating system , 2003, Eur. J. Oper. Res..

[7]  Hoang Pham,et al.  Handbook of reliability engineering , 2013 .

[8]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.

[9]  N. Hastings.  The Repair Limit Replacement Method , 1969 .

[10]  J. Kalbfleisch,et al.  The Statistical Analysis of Failure Time Data , 1980 .

[11]  W. Hopp,et al.  Multiaction maintenance under Markovian deterioration and incomplete state information , 1988 .

[12]  Thomas Welte,et al.  Deterioration and Maintenance Models for Components in Hydropower Plants , 2008 .

[13]  L. Baum,et al.  An inequality and associated maximization technique in statistical estimation of probabilistic functions of a Markov process , 1972 .

[14]  R. I. Phelps.  Replacement Policies under Minimal Repair , 1981 .

[15]  Frédéric Kratz,et al.  Use of HMM for evaluation of maintenance activities , 2010 .

[16]  Howard Kunreuther,et al.  Near‐Miss Incident Management in the Chemical Process Industry , 2003, Risk analysis : an official publication of the Society for Risk Analysis.

[17]  David R. Cox,et al.  Regression models and life tables (with discussion , 1972 .

[18]  Laurent Doyen,et al.  Classes of imperfect repair models based on reduction of failure intensity or virtual age , 2004, Reliab. Eng. Syst. Saf..

[19]  Pierre Dehombreux,et al.  Identification of reliability models for non repairable and repairable systems with small samples , 2004 .

[20]  Antoine Grall,et al.  A sequential condition‐based repair/replacement policy with non‐periodic inspections for a system subject to continuous wear , 2003 .

[21]  Zineb Simeu-Abazi,et al.  Maintenance integration in manufacturing systems by using stochastic Petri nets , 1999 .

[22]  A. Birolini.  Quality and reliability of technical systems , 1994 .

[23]  Christophe Bérenguer,et al.  Maintenance cost study for deteriorating systems: age-replacement policy vs. condition-based maintenance policy , 2008 .

[24]  G. Celeux,et al.  An alternative competing risk model to the Weibull distribution for modelling aging in lifetime data analysis , 2006, Lifetime data analysis.

[25]  Frédéric Kratz,et al.  Towards a Maintenance and Servicing Indicator , 2009, APMS.

[26]  Christopher Jennison,et al.  Repeated confidence intervals for the median survival time , 1985 .

[27]  Zbigniew Michalewicz,et al.  Advances in Metaheuristics for Hard Optimization , 2008, Advances in Metaheuristics for Hard Optimization.

[28]  Hongzhou Wang,et al.  A survey of maintenance policies of deteriorating systems , 2002, Eur. J. Oper. Res..

[29]  M. Kijima.  SOME RESULTS FOR REPAIRABLE SYSTEMS WITH GENERAL REPAIR , 1989 .

[30]  Andrew J. Viterbi,et al.  Error bounds for convolutional codes and an asymptotically optimum decoding algorithm , 1967, IEEE Trans. Inf. Theory.

[31]  Pascal Massart,et al.  A Dvoretzky-Kiefer-Wolfowitz type inequality for the Kaplan-Meier estimator , 1999 .

[32]  G Riboulet,et al.  Maintenance optimization for a system with a gamma deterioration process and intervention delay: Application to track maintenance , 2009 .

[33]  Christophe Bérenguer,et al.  Maintenance policy for a deteriorating system evolving in a stressful environment , 2008 .

[34]  Michael Tortorella,et al.  A point process model for the reliability of a maintained system subject to general repair , 1996 .

[35]  Ron Brookmeyer,et al.  A Confidence Interval for the Median Survival Time , 1982 .

[36]  Carlos Guedes Soares,et al.  New insight into PFDavg and PFH , 2008 .

[37]  J. Kalbfleisch,et al.  The Statistical Analysis of Failure Time Data: Kalbfleisch/The Statistical , 2002 .

[38]  Peter Herbison,et al.  Survival over 5 years in the initial hospital survivors with acute coronary syndrome: a comparison between a community hospital and a tertiary hospital in New Zealand. , 2007, The New Zealand medical journal.

[39]  Jane-Ling Wang,et al.  Density and hazard rate estimation for censored data via strong representation of the Kaplan-Meier estimator , 1985 .

[40]  E. Muth.  An Optimal Decision Rule for Repair vs Replacement , 1977, IEEE Transactions on Reliability.

[41]  C. Bérenguer,et al.  On the mathematical condition-based maintenance modelling for continuously deteriorating systems , 2008 .

[42]  J. Moubray.  Reliability-Centered Maintenance , 1991 .

[43]  Richard M. Feldman,et al.  A survey of preventive maintenance models for stochastically deteriorating single-unit systems , 1989 .