Eryılmaz, Serkan
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Eryilmaz, S
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Eryılmaz, Serkan
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Eryilmaz, Serkan
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Serkan, Eryılmaz
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Eryılmaz, Serkan
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Eryilmaz,S.
Eryilmaz, Serkan
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Serkan, Eryılmaz
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Serkan, Eryilmaz
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174 results
Scholarly Output Search Results
Now showing 1 - 10 of 174
Article Citation Count: 11A NEW SHOCK MODEL WITH A CHANGE IN SHOCK SIZE DISTRIBUTION(Cambridge Univ Press, 2021) Eryilmaz, Serkan; Eryılmaz, Serkan; Kan, Cihangir; Industrial EngineeringFor a system that is subject to shocks, it is assumed that the distribution of the magnitudes of shocks changes after the first shock of size at least d(1), and the system fails upon the occurrence of the first shock above a critical level d(2) (> d(1)). In this paper, the distribution of the lifetime of such a system is studied when the times between successive shocks follow matrix-exponential distribution. In particular, it is shown that the system's lifetime has matrix-exponential distribution when the intershock times follow Erlang distribution. The model is extended to the case when the system fails upon the occurrence of l consecutive critical shocks.Article Citation Count: 30Reliability Evaluation for a Multi-State System Under Stress-Strength Setup(Taylor & Francis inc, 2011) Eryilmaz, Serkan; Eryılmaz, Serkan; Iscioglu, Funda; Industrial EngineeringThe two most commonly used reliability models in engineering applications are binary k-out-of-n:G and consecutive k-out-of-n:G systems. Multi-state k-out-of-n:G and multi-state consecutive k-out-of-n:G systems have been proposed as an extension of these systems and they have been found to be more flexible tool for modeling engineering systems. In this article, multi-state systems, in particular, multi-state k-out-of-n:G and multi-state consecutive k-out-of-n:G, are considered in a stress-strength setup. The states of the system are classified considering the number of components whose strengths above (below) the multiple stresses available in an environment. The exact state probabilities are provided and the results are illustrated for various stress-strength distributions. Maximum likelihood estimators of state probabilities are also presented.Article Citation Count: 1DISTRIBUTIONS OF RANDOM VARIABLES INVOLVED IN DISCRETE CENSORED δ-SHOCK MODELS(Cambridge Univ Press, 2023) Chadjiconstantinidis, Stathis; Eryılmaz, Serkan; Eryilmaz, Serkan; Industrial EngineeringSuppose that a system is affected by a sequence of random shocks that occur over certain time periods. In this paper we study the discrete censored delta-shock model, delta <= 1 , for which the system fails whenever no shock occurs within a -length time period from the last shock, by supposing that the interarrival times between consecutive shocks are described by a first-order Markov chain (as well as under the binomial shock process, i.e., when the interarrival times between successive shocks have a geometric distribution). Using the Markov chain embedding technique introduced by Chadjiconstantinidis et al. (Adv. Appl. Prob. 32, 2000), we study the joint and marginal distributions of the system's lifetime, the number of shocks, and the number of periods in which no shocks occur, up to the failure of the system. The joint and marginal probability generating functions of these random variables are obtained, and several recursions and exact formulae are given for the evaluation of their probability mass functions and moments. It is shown that the system's lifetime follows a Markov geometric distribution of order (a geometric distribution of order under the binomial setup) and also that it follows a matrix-geometric distribution. Some reliability properties are also given under the binomial shock process, by showing that a shift of the system's lifetime random variable follows a compound geometric distribution. Finally, we introduce a new mixed discrete censored delta -shock model, for which the system fails when no shock occurs within a -length time period from the last shock, or the magnitude of the shock is larger than a given critical threshold . gamma > 0. Similarly, for this mixed model, we study the joint and marginal distributions of the system's lifetime, the number of shocks, and the number of periods in which no shocks occur, up to the failure of the system, under the binomial shock process.Article Citation Count: 5Computing Barlow-Proschan Importance in Combined Systems(Ieee-inst Electrical Electronics Engineers inc, 2016) Eryilmaz, Serkan; Eryılmaz, Serkan; Industrial EngineeringThis paper is concerned with the computation of the Barlow-Proschan importance measure for systems involving two common failure criteria, and consisting of statistically independent and identical components. The failure or survival of these systems generally depends on the number of consecutively failed or working components, or the total number of failed or working components in the whole system. The results are applied to (n, f, k) : F and < n, f, k >: F systems.Article Citation Count: 23On stress-strength reliability with a time-dependent strength(2013) Eryılmaz, Serkan; Industrial EngineeringThe study of stress-strength reliability in a time-dependent context needs to model at least one of the stress or strength quantities as dynamic. We study the stress-strength reliability for the case in which the strength of the system is decreasing in time and the stress remains fixed over time; that is, the strength of the system is modeled as a stochastic process and the stress is considered to be a usual random variable. We present stochastic ordering results among the lifetimes of the systems which have the same strength but are subjected to different stresses. Multicomponent form of the aforementioned stress-strength interference is also considered. We illustrate the results for the special case when the strength is modeled by a Weibull process. © 2013 Serkan Eryilmaz.Article Citation Count: 18Component importance for linear consecutive-k-Out-of-n and m-Consecutive-k-Out-of-n systems with exchangeable components(Wiley-blackwell, 2013) Eryilmaz, Serkan; Eryılmaz, Serkan; Industrial EngineeringMeasuring the relative importance of components in a mechanical system is useful for various purposes. In this article, we study Birnbaum and Barlow-Proschan importance measures for two frequently studied system designs: linear consecutive k -out-of- n and m -consecutive- k -out-of- n systems. We obtain explicit expressions for the component importance measures for systems consisting of exchangeable components. We illustrate the results for a system whose components have a Lomax type lifetime distribution. (c) 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013Book Citation Count: 7Discrete Stochastic Models and Applications for Reliability Engineering and Statistical Quality Control(CRC Press, 2022) Eryılmaz, Serkan; Industrial EngineeringDiscrete stochastic models are tools that allow us to understand, control, and optimize engineering systems and processes. This book provides real-life examples and illustrations of models in reliability engineering and statistical quality control and establishes a connection between the theoretical framework and their engineering applications. The book describes discrete stochastic models along with real-life examples and explores not only well-known models, but also comparatively lesser known ones. It includes definitions, concepts, and methods with a clear understanding of their use in reliability engineering and statistical quality control fields. Also covered are the recent advances and established connections between the theoretical framework of discrete stochastic models and their engineering applications. An ideal reference for researchers in academia and graduate students working in the fields of operations research, reliability engineering, quality control, and probability and statistics. © 2023 Serkan Eryilmaz.Article Citation Count: 51Generalized δ-shock model via runs(Elsevier Science Bv, 2012) Eryilmaz, Serkan; Eryılmaz, Serkan; Industrial EngineeringAccording to the delta-shock model, the system fails when the time between two consecutive shocks falls below a fixed threshold delta. This model has a potential application in various fields such as inventory, insurance and system reliability. In this paper, we study run-related generalization of this model such that the system fails when k consecutive interarrival times are less than a threshold delta. The survival function and the mean value of the failure time of the system are explicitly derived for exponentially distributed interarrival times. We also propose a new combined shock model which considers both the magnitudes of successive shocks and the interarrival times. (C) 2011 Elsevier B.V. All rights reserved.Article Citation Count: 10Joint Reliability Importance in Coherent Systems With Exchangeable Dependent Components(Ieee-inst Electrical Electronics Engineers inc, 2016) Eryilmaz, Serkan; Eryılmaz, Serkan; Oruc, Ozlem Ege; Oger, Volkan; Industrial EngineeringIn this paper, a general formula for computing the joint reliability importance of two components is obtained for a binary coherent system that consists of exchangeable dependent components. Using the new formula, the joint reliability importance can be easily calculated if the path sets of the system are known. As a special case, an expression for the joint reliability importance of two components is also obtained for a system consisting of independent and identical components. Illustrative numerical results are presented to compare the joint reliability importance of two components in the bridge system for the two cases when the components are exchangeable dependent and when the components are independent and identical.Article Citation Count: 33On the lifetime behavior of a discrete time shock model(Elsevier, 2013) Eryilmaz, Serkan; Eryılmaz, Serkan; Industrial EngineeringIn this article, we study a shock model in which the shocks occur according to a binomial process, i.e. the interarrival times between successive shocks follow a geometric distribution with mean 1/p. According to the model, the system fails when the time between two consecutive shocks is less than a prespecified level. This is the discrete time version of the so-called delta-shock model which has been previously studied for the continuous case. We obtain the probability mass function and probability generating function of the system's lifetime. We also present an extension of the results to the case where the shock occurrences are dependent in a Markovian fashion. (C) 2012 Elsevier B.V. All rights reserved.
