On a Mixed Transient–Asymptotic Result for the Sequential Interval Reliability for Semi-Markov Chains

Guglielmo D’Amico () and Thomas Gkelsinis
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Guglielmo D’Amico: Department of Economics, University “G. d’Annunzio” of Chieti-Pescara, 65127 Pescara, Italy
Thomas Gkelsinis: Laboratory of Mathematics Raphaël Salem, University of Rouen-Normandy, UMR 6085, 76801 Saint-Étienne-du-Rouvray, France

Mathematics, 2024, vol. 12, issue 12, 1-18

Abstract: In this paper, we are concerned with the study of sequential interval reliability, a measure recently introduced in the literature. This measure represents the probability of the system working during a sequence of nonoverlapping time intervals. In the cited work, the authors proposed a recurrent-type formula for computing this indicator in the transient case and investigated the asymptotic behavior as all the time intervals go to infinity. The purpose of the present work is to further explore the asymptotic behavior when only some of the time intervals are allowed to go to infinity while the remaining ones are not. In this way, we provide a unique indicator that is able to describe the process evolution in the transient and asymptotic cases as well. It is important to mention that this is not a straightforward result since, in order to achieve it, we need to develop several mathematical ingredients that generalize the classical renewal and Markov renewal frameworks. A numerical example illustrates our theoretical results.

Keywords: sequential measures; convolution product; semi-Markov processes; asymptotic results (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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