Eryılmaz, Serkan
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Name Variants
E., Serkan
Eryilmaz, S
E.,Serkan
S., Eryilmaz
Eryılmaz, Serkan
Eryilmaz, S.
Eryilmaz,S.
Eryilmaz, Serkan
S.,Eryılmaz
Eryilmaz S.
Serkan, Eryılmaz
Erylmaz S.
Eryılmaz S.
Eryilmaz, SN
S., Eryılmaz
Eryılmaz,S.
Serkan, Eryilmaz
S.,Eryilmaz
EryIlmaz S.
Eryilmaz S., Professor,
Eryilmaz, S
E.,Serkan
S., Eryilmaz
Eryılmaz, Serkan
Eryilmaz, S.
Eryilmaz,S.
Eryilmaz, Serkan
S.,Eryılmaz
Eryilmaz S.
Serkan, Eryılmaz
Erylmaz S.
Eryılmaz S.
Eryilmaz, SN
S., Eryılmaz
Eryılmaz,S.
Serkan, Eryilmaz
S.,Eryilmaz
EryIlmaz S.
Eryilmaz S., Professor,
Job Title
Profesor Doktor
Email Address
serkan.eryilmaz@atilim.edu.tr
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Scholarly Output
174
Articles
163
Citation Count
2501
Supervised Theses
2
174 results
Scholarly Output Search Results
Now showing 1 - 10 of 174
Article Citation Count: 4Age based preventive replacement policy for discrete time coherent systems with independent and identical components(Elsevier Sci Ltd, 2023) Eryilmaz, Serkan; Eryılmaz, Serkan; Industrial EngineeringThe paper is concerned with an age based preventive replacement policy for an arbitrary coherent system that consists of components that are independent and have common discrete lifetime distribution. The system having an arbitrary structure is replaced preventively after a specific number of cycles or correctively at its failure time. The necessary conditions for the unique and finite replacement cycle that minimize the expected cost per unit of time are obtained. The policy is studied for some particular system models including the well-known k-out-of -n structure. The findings of the paper extend the results in the literature from single unit and parallel systems to an arbitrary coherent system. Numerical results are presented for particular discrete component lifetime distributions.Article Citation Count: 5Computing finite time non-ruin probability and some joint distributions in discrete time risk model with exchangeable claim occurrences(Elsevier, 2017) Eryilmaz, Serkan; Eryılmaz, Serkan; Gebizlioglu, Omer L.; Industrial EngineeringIn this paper, we study a discrete time risk model based on exchangeable dependent claim occurrences. In particular, we obtain expressions for the finite time non-ruin probability, and the joint distribution of the time to ruin, the surplus immediately before ruin, and the deficit at ruin. An illustration of the results is given and some implications of the results are provided. Comparisons are made with the corresponding results for the classical compound binomial model of independent and identically distributed claim occurrences. (C) 2016 Elsevier E.V. All rights reserved.Article Citation Count: 5DISCRETE SCAN STATISTICS GENERATED BY EXCHANGEABLE BINARY TRIALS(Cambridge Univ Press, 2010) Eryilmaz, Serkan; Eryılmaz, Serkan; Industrial EngineeringLet {X-i}(i=1)(n) be a sequence of random variables with two possible outcomes, denoted 0 and 1. Define a random variable S-n,S-m to be the maximum number of Is within any m consecutive trials in {X-i}(i=1)(n). The random variable S-n,S-m is called a discrete scan statistic and has applications in many areas. In this paper we evaluate the distribution of discrete scan statistics when {X-i}(i=1)(n) consists of exchangeable binary trials. We provide simple closed-form expressions for both conditional and unconditional distributions of S-n,S-m for 2m >= n. These results are also new for independent, identically distributed Bernoulli trials, which are a special case of exchangeable trials.Article Citation Count: 6Order statistics of dependent sequences consisting of two different sets of exchangeable variables(Elsevier Science Bv, 2015) Bayramoglu (Bairamov), Ismihan; Eryılmaz, Serkan; Eryilmaz, Serkan; Industrial EngineeringWe consider two different sets of exchangeable samples which are assumed to be dependent. A single set of observations is obtained from these two dependent samples. The distribution of single order statistic, and the joint distribution of the minimum and an arbitrary order statistic are derived. The results are illustrated in the context of reliability problem. (C) 2015 Elsevier B.V. All rights reserved.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: 1On Extreme Residual Lives after the Failure of the System(Hindawi Ltd, 2012) Eryilmaz, Serkan; Eryılmaz, Serkan; Bayramoglu, Ismihan; Industrial EngineeringThe concept of residual lifetime has attracted considerable research interest in reliability theory. It is useful for evaluating the dynamic behavior of a system. In this paper, we study the extreme residual lives, that is, the minimum and maximum residual lives of the remaining components after the failure of the system. The system is assumed to have an arbitrary structure. We obtain signature-based distributional and ordering results for the extreme residual lives.Article Citation Count: 6Generalized waiting time distributions associated with runs(Springer Heidelberg, 2016) Eryilmaz, Serkan; Eryılmaz, Serkan; Industrial EngineeringLet be a {X-t, t >= 1} sequence of random variables with two possible values as either "1" (success) or "0" (failure). Define an independent sequence of random variables {D-i, i >= 1}. The random variable is associated with the success when it occupies the ith place in a run of successes. We define the weight of a success run as the sum of the D values corresponding to the successes in the run. Define the following two random variables: is the number of trials until the weight of a single success run exceeds or equals k, and is the number of trials until the weight of each of r success runs equals or exceeds k in {X-t, t >= 1}. Distributional properties of the waiting time random variables and are studied and illustrative examples are presented.Article Citation Count: 0Estimating the parameter of a geometric distribution from series system data(Elsevier, 2024) Eryilmaz, Serkan; Eryılmaz, Serkan; Kateri, Maria; Industrial EngineeringIn 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 Count: 9Reliability of a mixed δ-shock model with a random change point in shock magnitude distribution and an optimal replacement policy(Elsevier Sci Ltd, 2023) Chadjiconstantinidis, Stathis; Eryılmaz, Serkan; Eryilmaz, Serkan; Industrial EngineeringA mixed delta-shock model when there is a change in the distribution of the magnitudes of shocks is defined and studied. Such a model which is a combination of the delta-shock model and the extreme shock model with a random change point (studied by Eryilmaz and Kan, 2019), is useful in practice since a sudden change in environmental conditions may cause a larger shock. In particular, the reliability and the mean time to failure of the system are evaluated by assuming that the random change point has a discrete phase-type distribution. Analytical results for evaluating the reliability function of the system for several joint distributions of the interarrival times and the magnitudes of shocks, are also given. The optimal replacement policy that is based on a control limit is also proposed when the number of shocks until the change point follows geometric distribution. The results are illustrated by numerical examples.Article Citation Count: 23Dynamic behavior of k-out-of-n:G systems(Elsevier, 2011) Eryilmaz, Serkan; Eryılmaz, Serkan; Industrial EngineeringIn this paper, we study the distribution and expected value of the number of working components at time t in usual and weighted k-out-of-n:G systems under the condition that they are working at time t. We evaluate the distribution of the corresponding conditional random variable and compute its expected value for the systems consisting of independent but nonidentical components. Illustrative examples are presented and an optimization problem which makes use of the conditional random variable is also formulated and solved numerically. (c) 2011 Elsevier B.V. All rights reserved.
