Preliminary risk analysis of dynamic systems

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Preliminary risk analysis of dynamic systems

Author : Jean-Pierre SIGNORET

Publication date: April 10, 2005 | Lire en français

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AUTHOR

  • Jean-Pierre SIGNORET : Master of Science. Reliability engineer Total - Former President of the European Safety & Reliability Society (ESRA) - Leader of the IMdR-SdF "Methodological Research" working group

 INTRODUCTION

Lnalyse des risques des systèmes dynamiques: chosen to include only words from everyday language, such a title should generate no ambiguity as to its purpose. However, in the field of reliability, many terms are subject to a certain semantic drift that blurs the meaning even without the knowledge of the interlocutors.

We could have substituted Sûreté de fonctionnement (SdF) for Analyse des risques (risk analysis), but as this term still has a strong safety connotation, this would not have been entirely in keeping with the spirit of this article, in which we are also concerned with economic aspects such as production availability, for example. Indeed, defined as a two-dimensional quantity (probability × consequences), risk has the immense advantage of encompassing, within the same concept, risks of a completely different nature. In this preliminary presentation, we shall endeavour to show how the corpus of reliability methods and tools developed over the last fifty years enables us to deal with the various types of risk encountered.

Similarly, since all industrial systems are more or less "dynamic", the term "dynamic system" is shorthand for the reliability engineering methods and models we'll be using to represent the behavior of the systems under study. The work carried out by the reliability engineer is in fact part of a systematic, systemic and probabilistic analysis approach, using a whole battery of methods and tools that can be broadly divided into three main categories:

  • basic problem-solving methods ;

  • static methods for analyzing systems from a structural (topological) point of view ;

  • dynamic methods for understanding behavioral aspects.

This classification reflects a certain gradation in the degree of expertise required to implement methods and, above all, tools that are increasingly taking on the appearance of black boxes whose limitations often escape those who use them.

Note :

The aim of this introductory article is to briefly discuss the various classes of methods and tools, to highlight their respective roles and some of the problems associated with their limitations, and then to situate more precisely within this general approach the dynamic methods which will be the subject of specific articles later on:

  • Markov process (analytical method) ;

  • stochastic Petri nets (Monte Carlo simulation)

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