Towards a Maintenance and Servicing Indicator

This paper deals with a tool which may help maintenance manager to schedule maintenance activities. To help him, we show that by using events which can be observed on a process, like maintenance events, we can predict failures before they occur. Principles are based on the hypothesis that failure is preceded by a typical sequence of events. We also show that Hidden Markov Models can be used according to a good choice of parameters.

[1]  Pascal Vrignat,et al.  Modélisation des dysfonctionnements d'un système dans le cadre d'activités de maintenance , 2008 .

[2]  F. Kratz,et al.  Conventional approaches to the modelling of a dysfunctional process in the context of maintenance activity , 2008, MELECON 2008 - The 14th IEEE Mediterranean Electrotechnical Conference.

[3]  L. R. Rabiner,et al.  Recognition of isolated digits using hidden Markov models with continuous mixture densities , 1985, AT&T Technical Journal.

[4]  L. Baum,et al.  Statistical Inference for Probabilistic Functions of Finite State Markov Chains , 1966 .

[5]  Horst Bunke,et al.  Using HMM based recognizers for writer identification and verification , 2004, Ninth International Workshop on Frontiers in Handwriting Recognition.

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

[7]  Abdel Belaïd,et al.  Hidden Markov Models in Text Recognition , 1995, Int. J. Pattern Recognit. Artif. Intell..

[8]  James P. Hughes,et al.  A hidden Markov model for downscaling synoptic atmospheric patterns to precipitation amounts , 2000 .

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

[10]  Manuel Avila Optimisation de modèles markoviens pour la reconnaissance de l'écrit , 1996 .

[11]  Mathew Magimai.-Doss,et al.  Using Auxiliary Sources of Knowledge for Automatic Speech Recognition , 2005 .

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

[13]  William Noble Grundy,et al.  Meta-MEME: motif-based hidden Markov models of protein families , 1997, Comput. Appl. Biosci..