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Article Citation - WoS: 14Citation - Scopus: 15Dynamic Modeling of General Three-State k-out-of-n< Systems: Permanent-Based Computational Results(Elsevier Science Bv, 2014) Eryilmaz, Serkan; Xie, MinThis paper is concerned with dynamic reliability analysis of three-state k-out-of-n:G systems. It is assumed that the components and the systems can be in three states: perfect functioning, partial performance and complete failure. Using the concept of permanent, we study marginal and joint survival functions for the lifetime of two different three-state k-out-of-n:G systems that consist of independent and nonidentical components. Illustrative examples are also provided for the components which follow the Markov degradation process. (C) 2014 Elsevier B.V. All rights reserved.Article Citation - WoS: 22Citation - Scopus: 24Computing reliability indices of repairable systems via signature(Elsevier Science Bv, 2014) Eryilmaz, SerkanThe purpose of this paper is to show the usefulness of system signature for computing some important reliability indices of repairable systems. In particular, we obtain signature-based expressions for stationary availability, rate of occurrence of failure, and mean time to the first failure of repairable systems. Using these expressions we compute corresponding reliability indices of all systems with three and four components. Computational results are also presented for consecutive-k-within-m-out-of-n:F and m-consecutive-k-out-of-n:F systems. (C) 2013 Elsevier B.V. All rights reserved.Article Citation - WoS: 11Citation - Scopus: 12A New Mixed Δ-Shock Model With a Change in Shock Distribution(Springer, 2023) Chadjiconstantinidis, Stathis; Tuncel, Altan; Eryilmaz, SerkanIn this paper, reliability properties of a system that is subject to a sequence of shocks are investigated under a particular new change point model. According to the model, a change in the distribution of the shock magnitudes occurs upon the occurrence of a shock that is above a certain critical level. The system fails when the time between successive shocks is less than a given threshold, or the magnitude of a single shock is above a critical threshold. The survival function of the system is studied under both cases when the times between shocks follow discrete distribution and when the times between shocks follow continuous distribution. Matrix-based expressions are obtained for matrix-geometric discrete intershock times and for matrix-exponential continuous intershock times, as well.Article Citation - WoS: 43Citation - Scopus: 50On the lifetime behavior of a discrete time shock model(Elsevier, 2013) Eryilmaz, SerkanIn 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.Article Citation - WoS: 56Citation - Scopus: 58Reliability Analysis Under Marshall-Olkin Run Shock Model(Elsevier, 2019) Ozkut, Murat; Eryilmaz, SerkanIn this paper, a new shock model called Marshall-Olkin run shock model is defined and studied. According to the model, two components are subject to shocks that may arrive from three different sources, and component i fails when it is subject to k consecutive critical shocks from source i or k consecutive critical shocks from source 3, i = 1, 2. Reliability and mean residual life functions of such components are studied when the times between shocks follow phase-type distribution. (C) 2018 Elsevier B.V. All rights reserved.Article Citation - WoS: 5Citation - Scopus: 5Estimating the Parameter of a Geometric Distribution From Series System Data(Elsevier, 2024) Eryilmaz, Serkan; Kateri, MariaIn a traditional setup of estimation of an unknown parameter of component lifetime distribution, system's continuous lifetime data is used. In this paper, we propose a simple and competitive estimator that is based on discrete lifetime data, i.e., the number of failed components at the time when the system fails. In particular, we consider the estimation of the parameter of a geometric distribution based on the system's lifetime data, and the number of failed components upon the failure of the system when the system has a series structure. Two moment estimators that are based on the system lifetime data and the number of failed components at the moment of system failure are obtained and their performances are compared in terms of the mean square error. The associated Bayesian estimators with non -informative priors are also discussed.Article Citation - WoS: 55Citation - Scopus: 60Reliability Evaluation of a System Under a Mixed Shock Model(Elsevier Science Bv, 2019) Eryilmaz, Serkan; Tekin, MustafaA new mixed shock model is introduced and studied. According to the model, for two fixed critical values d(1) and d(2) such that d(1) < d(2), the system under concern fails upon the occurrence of k consecutive shocks of size at least d(1) or a single large shock of size at least d(2). The new model combines run and extreme shock models. Reliability properties of the system are studied under two cases: when the interarrival time X-i between the (i - 1)th and ith shock, and the magnitude of the ith shock Y-i are independent for all i, and when the interarrival time between the (i - 1)th and ith shock, and the magnitude of the ith shock are dependent for all i. (C) 2018 Elsevier B.V. All rights reserved.
