Dependability assessment models and evaluation techniques

Journal of Statistical Planning and Inference, 1996

The 5th International …, 2008

Abstract. Many stochastic models have been used in solving reliability problems, motivated by a high degree of variability or randomness of the studied phenomena. Therefore different types of stochastic laws derived from the basic distributions are proposed for modelling a ...

HAL (Le Centre pour la Communication Scientifique Directe), 2018

International Journal of Systems Science, 2001

The objective of the paper is to lay down a foundation for imprecise system reliability assessments based on coherent imprecise probabilities that are a particular case of coherent imprecise previsions. Previous attempts of wide implementation of other theories of imprecise probabilities in reliability analyses have not succeeded. The recent theory of coherent imprecise previsions appeared to be a promising tool for reliability and risk assessments and devoid of drawbacks of its predecessors. This paper describes an approach how the coherent imprecise reliabilities of series and parallel systems can be calculated. A set of theorems is proven to allow calculating the imprecise reliability of a system of an arbitrary structure, in particular with fault trees. An approach to calculate imprecise reliability based on purely comparative judgements is described.

Communications in Statistics - Theory and Methods, 2005

The reliability polynomial R p of a collection of subsets of a finite set X has been extensively studied in the context of network theory. There, X is the edge set of a graph V X and the collection of the edge sets of certain subgraphs. For example, we may take to be the collection of edge sets of spanning trees. In that case, R p is the probability that, when each edge is included with the probability p, the resulting subgraph is connected. The second author defined R p in an entirely different way enabling one to glean additional information about the collection from R p. Illustrating the extended information available in the reliability polynomial is the main focus of this article while demonstrating the equivalence of these two definitions is the main theoretical result.

2004

In this paper, we describe an experience of dependability assessment of a typical industrial Programmable Logic Controller (PLC). The PLC is based on a two out of three voting policy and it is intended to be used for safety functions. Safety assessment of computer based systems performing safety functions is regulated by standards and guidelines. In all of them there is a common agreement that no single method can be considered sufficient to achieve and assess safety. The paper addresses the PLC assessment by probabilistic methods to determine its dependability attributes related to Safety Integrity Levels as defined by IEC61508 standard. The assessment has been carried out by independent teams, starting from the same basic assumptions and data. Diverse combinatorial and state space probabilistic modelling techniques, implemented by public tools, have been used. Even if the isolation of teams was not formally granted, the experience has shown different topics worthwhile to be described. First of all, the usage of different modelling techniques has led to diverse models. Moreover models focus on different system details also due the diverse teams skill. Also slight differences in understanding PLC assumptions have been occurred. In spite of all, the numerical results of the diverse models are comparable. The experience has also allowed a comparison of the different modelling techniques as implemented by the considered public tools.

Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2016

In reliability analysis, comparing system reliability is an essential task when designing safe systems. When the failure probabilities of the system components (assumed to be independent) are precisely known, this task is relatively simple to achieve, as system reliabilities are precise numbers. When failure probabilities are ill-known (known to lie in an interval) and we want to have guaranteed comparisons (i.e., declare a system more reliable than another when it is for any possible probability value), there are different ways to compare system reliabilities. We explore the computational problems posed by such extensions, providing first insights about their pros and cons.

1986

According to Knezevic [1] the purpose of the existence of any functional system is to do work. The work is done when the expected measurable function is performed through time. However, experience teaches us that expected work is frequently beset by failures, some of which result in hazardous consequences to: the users; the natural environment; the general population and businesses. During the last sixty years, Reliability Theory has been used to create failure predictions and try to identify where reductions in failures could be made throughout the life cycle phases of maintainable systems. However, mathematically and scientifically speaking, the accuracy of these predictions, at best, were only ever valid to the time of occurrence of the first failure, which is far from satisfactory in the respect of its expected life. Consequently, the main objective of this paper is to raise the question how reliable are reliability predictions of maintainable systems based on the Reliability Function.

1997

is charge de recherche at CNRS. He joined the LAAS-CNRS's Fault Tolerance and Dependable Computing group in 1988. His current research interests include dependability modeling and computing systems evaluation with a focus on software reliability growth evaluation and operational systems' security assessment. He also works on the definition of process models for the development of dependable systems. Kaâniche received a CE from the French National School of Civil Aviation and a PhD in computer science and automation from the University of Toulouse. He is a member of AFCET.