Abstract
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.
Chapter PDF
Similar content being viewed by others
References
Vrignat, P., Avila, M., Duculty, F., Kratz, F.: Conventional approaches to the modelling of a dysfunctional process in the context of maintenance activity. IEEE Melecon Region 8, t1-sf0008 (2008)
Zille, V., Bérenguer, C., Grall, A.: Modelling and simulation of complex maintenance strategies for multi-component systems. Maintenance and Facility Management (2007)
Rabiner, L.R.: A tutorial on hidden Markov models and selected applications in speech recognition. Proceeding of the IEEE 77(2), 257–286 (1989)
Baum, L.E., Petrie, T.: Statistical inference for probabilistic functions of Markov chains. Annals Math. Stat. 37, 1554–1563 (1966)
Baum, L.E.: An inequality and associated maximisation technique in statistical estimation for probabilistic functions. Inequalities 3, 1–8 (1972)
Viterbi, A.J.: Error bounds for conventionnal codes and asymptotically optimum decoding algorithm. IEEE Trans. on Information Theory 13, 260–269 (1967)
Doss, M.M.: Using Auxiliary Sources of Knowledge for Automatic Speech Recognition, Thèse de doctorat, Ecole Polytechnique Fédérale, Lausanne (2005)
Grundy, W.N., Bailey, T.L., Baker, M.E.: Meta-MEME: Motif-based Hidden Markov Models of protein families. Computer Applications in the Biosciences 13(4), 397 (1997)
Schbath, S.: Les chaînes de Markov cachées: présentation et usage en analyse de séquences bioliques. In: Unité Mathématique, Informatique & Génome, INRA (2007)
Hugues, J.P., Guttorp, P.: A hidden Markov model for downscalling synoptic atmospheric patterns to precipitation amounts. Climate Research 15(1), 1 (2000)
Avila, M.: Optimisation de modèles Markoviens pour la reconnaissance de l’écrit, Thèse de doctorat, Université, Rouen (1996)
Belaïd, A., Anigbogu, J.: Hidden Markov Models in Text Recognition. International Journal of Pattern Recognition 9(6) (1995)
Schalapbach, A., Bunke, H.: Using HMM-based recognizers for writer identification and verification. In: Proc. 9th Int. Workshop on Frontiers in Handwriting Recognition, pp. 167–172 (2004)
Vialatte, F.B.: Aide au diagnostic d’anomalies cardiaques, mémoire de DEA de Sciences Cognitives, Paris VI, Paris (2002)
Rabiner, L.R., Juang, B.H., Levinson, S.E., Sondhi, M.M.: Recognition of isolated digits using hidden Markov models with continuous mixture densities. AT&T Technical Journal 64, 1211–1222 (1986)
Brouard, T.: Hybridation de Chaînes de Markov Cachées: conception d’algorithmes d’apprentissage et applications, Thèse de doctorat, Université François Rabelais, Tours (1999)
Vrignat, P., Avila, M., Duculty, F., Kratz, F.: Modélisation des dysfonctionnements d’un système dans le cadre d’activités de maintenance. Communication 4A-1, lm16 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 IFIP International Federation for Information Processing
About this paper
Cite this paper
Vrignat, P., Avila, M., Duculty, F., Kratz, F. (2010). Towards a Maintenance and Servicing Indicator. In: Vallespir, B., Alix, T. (eds) Advances in Production Management Systems. New Challenges, New Approaches. APMS 2009. IFIP Advances in Information and Communication Technology, vol 338. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16358-6_15
Download citation
DOI: https://doi.org/10.1007/978-3-642-16358-6_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16357-9
Online ISBN: 978-3-642-16358-6
eBook Packages: Computer ScienceComputer Science (R0)