Timed automata for monitoring manufacturing systems

International audienc

Monitoring and predictive maintenance: modelling and analyse of fault latency

International audienc

Premiers pas vers le diagnostic de défaillances par exploitation d’un modèle SysML

National audienceCurrently systems become even more developed in order to bring some solutions for a more and more challenging society. By allying various technologies (mechanics, electronics, computer science), systems tend to be more complex. In this context, the functional safety community is continuously involved for making systems able to verify even higher quality constraints. These methods must be adapted to the growing complexity of these systems. Fault diagnosis community is not exempted. In this way, diagnosis methods are facing up to a huge difficulty: how to model these complex systems.This article shows our first results regarding the exploitation of the SysML language for fault diagnosis. A methodology of system modeling using the SysML formalism is detailed. It can be generalized to diverse application scopes. Furthermore, the first thoughts on a fault diagnosis method by exploiting a SysML model are explained.Les systèmes développés actuellement évoluent continuellement pour répondre aux demandes d’une société toujours plus exigeante. Ils ont tendance à se complexifier en alliant diverses technologies (mécanique, électronique, informatique). Dans ce contexte, le domaine de la sûreté de fonctionnement est de plus en plus sollicité pour que les systèmes puissent répondre à des contraintes de qualité toujours plus élevées. Les méthodes doivent s’adapter à la complexité de ces nouveaux systèmes. Et le diagnostic de défaillances ne fait pas exception. Ainsi, certaines méthodes de diagnostic se retrouvent confrontées à une difficulté importante : comment modéliser ces systèmes complexes.Cet article présente nos premiers résultats sur l’exploitation du langage SysML pour le diagnostic de défaillances. Une méthodologie de modélisation d’un système en langage SysML est proposée. Elle se veut généralisable pour être utilisée dans différents domaines d’application. De plus, les premières réflexions sur une méthode de diagnostic de défaillances par exploitation d’un modèle SysML sont développées

Decision support with a markovian approach for maintenance context activities

ABSTRACT: Today, maintenance strategies and their analyses remain a worrying problem for companies. Our study, presented in this paper, shows that our indicator can provide help for expert decision (maintenance manager) in the context of condition-based maintenance. The paper deals with the proposition of using Hidden Markov Models to track and estimate the degradation of a system, according to observations (maintenance activities registered in a database). In a first time, the degradation level of process was established by a "classical " degradation laws (statistical laws). In a second step, this level was established by Hidden Markov Model (probabilistic laws).Tests conducted on the synthesis model, for which degradation levels were known, allowed us to implement the method.

Failure root causes analysis of complex systems—Dynamic Fault Tree approach

International audienceIn this paper we propose a methodology for the identification of the root causes of the failures of a complex dynamic system based on its Dynamic Fault Tree (DFT) and the component’s execution traces leading to the system’s malfunction. The proposed method is decomposed as follows: each basic event in the DFT is associated to its execution trace and a post-order depth-first traversal of the DFT is applied. Computing the failure-time and the failure root causes of each node of the DFT is done during the traversal of the DFT. As result, the failure root causes of the dynamic complex system is obtained in the top event of the DFT. The methodology is illustrated on an academic example

Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction

Part 2: MAKE Smart FactorInternational audienceThe current trend of integrating machines and factories into cyber-physical systems (CPS) creates an enormous complexity for operators of such systems. Especially the search for the root cause of cascading failures becomes highly time-consuming. Within this paper, we address the question on how to help human users to better and faster understand root causes of such situations. We propose a concept of interactive alarm flood reduction and present the implementation of a first vertical prototype for such a system. We consider this prototype as a first artifact to be discussed by the research community and aim towards an incremental further development of the system in order to support humans in complex error situations