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Article Citation - WoS: 11Citation - Scopus: 13Geometric Distribution of Order k With a Reward(Elsevier Science Bv, 2014) Eryilmaz, SerkanIn this paper, we introduce and study geometric distribution of order k with a reward. In a sequence of binary trials, suppose that each time a success occurs a random reward is received. The distribution of the number of trials until the sum of consecutive rewards is equal to or exceeds the level k is called geometric distribution of order k with a reward. We obtain expressions for the probability mass function of this distribution. (C) 2014 Elsevier B.V. All rights reserved.Article Citation - WoS: 19Citation - Scopus: 21Revisiting Discrete Time Age Replacement Policy for Phase-Type Lifetime Distributions(Elsevier, 2021) Eryilmaz, SerkanFor a system (or unit) whose lifetime is measured by the number cycles, according to the discrete time age replacement policy, it is replaced preventively after n cycles or correctively at failure, whichever oc-curs first. In this paper, discrete time age replacement policy is revisited when the lifetime of the system is modeled by a discrete phase-type distribution. In particular, the necessary conditions for the unique and finite replacement cycle which minimizes the expected cost per unit of time are obtained. The nec-essary conditions are mainly based on the behavior of the hazard rate. The results are illustrated for some special discrete phase-type lifetime distributions. Computational results are also presented for the optimal replacement cycle under specific real life setups. (c) 2021 Elsevier B.V. All rights reserved.Article Citation - WoS: 11Citation - Scopus: 13Compound Markov Negative Binomial Distribution(Elsevier, 2016) Eryilmaz, SerkanLet {Y-i}(i >= 1) be a sequence of {0,1} variables which forms a Markov chain with a given initial probability distribution and one-step transition probability matrix. Define N-n to be the number of trials until the nth success ("1") in {Y-i}(i >= 1). In this paper, we study the distribution of the random variable T = Sigma(Nn)(i=1) X-i, where {X-i}(i >= 1) is a sequence of independent and identically distributed random variables having a common phase-type distribution. The distribution of T is obtained by means of phase-type distributions. (C) 2015 Elsevier B.V. All rights reserved.Article Citation - WoS: 32Citation - Scopus: 44The Number of Failed Components in a k-out-of-n< System Consisting of Multiple Types of Components(Elsevier Sci Ltd, 2018) Eryilmaz, SerkanThe number of failed components in a failed or operating system is a very useful quantity in terms of replacement and maintenance strategies. These quantities have been studied in several papers for a system consisting of identical components. In this paper, the number of failed components at the time when the system fails and the number of failed components when the system is working are considered for a well-known and widely applicable k-out-of-n structure. The system is assumed to have multiple types of components. That is, the system consists of components having nonidentical failure time distributions. Optimization problems are also formulated to find optimal values of the number of components of each type, and the optimal replacement time.Article Citation - WoS: 11Citation - Scopus: 12Discrete Time Shock Models Involving Runs(Elsevier Science Bv, 2015) Eryilmaz, SerkanIn this paper, three different discrete time shock models are studied. In the first model, the failure occurs when the additively accumulated damage exceeds a certain level while in the second model the system fails upon the local damage caused by the consecutively occurring shocks. The third model is a mixed model and combines the first and second models. The survival functions of the systems under these models are obtained when the occurrences of the shocks are independent, and when they are Markov dependent over the periods. (C) 2015 Elsevier B.V. All rights reserved.Article Citation - WoS: 4Citation - Scopus: 4On Success Runs in a Sequence of Dependent Trials With a Change Point(Elsevier Science Bv, 2018) Eryilmaz, SerkanLet {X-i}(i=1)(n) be a sequence of n dependent binary trials such that the first n(1) in {X-i}(i=1)(n) are of type 1 and follow an exchangeable joint distribution denoted by L-1, and the last n2 elements in {X-i}(i=1)(n) are of type 2 and follow an exchangeable joint distribution denoted by L-2, where n(1) + n(2) = n. That is, the trials within the same group are exchangeable dependent, and the trials in different groups are dependent in a general sense. The exact distributions of the number of success runs of length k in {X-i}(i=1)(n) are obtained under nonoverlapping and at least schemes. (C) 2017 Elsevier B.V. All rights reserved.Editorial Discussion of Signature-Based Models of Preventive Maintenance(Wiley, 2023) Eryilmaz, Serkan[No Abstract Available]Article Citation - WoS: 4Citation - Scopus: 2A New Class of Bivariate Lifetime Distributions(Taylor & Francis inc, 2017) Eryilmaz, SerkanThis paper introduces a new class of bivariate lifetime distributions. Let {X-i}(i 1) and {Y-i}(i 1) be two independent sequences of independent and identically distributed positive valued random variables. Define T-1 = min(X-1, ..., X-M) and T-2 = min(Y-1, ..., Y-N), where (M, N) has a discrete bivariate phase-type distribution, independent of {X-i}(i 1) and {Y-i}(i 1). The joint survival function of (T-1, T-2) is studied.Article Citation - WoS: 35Citation - Scopus: 43Reliability Analysis of Multi-State System With Three-State Components and Its Application To Wind Energy(Elsevier Sci Ltd, 2018) Eryilmaz, SerkanIn most real life situations, the system's components contribute differently in different performance levels. Such a situation can be modeled by systems with multi-state components having more than one working status, e.g. perfect functioning, and partial working. In this paper, a multi-state system that consists of two types of three-state components is defined and studied. An explicit formula for the probability that the performance of the system is at least a given level is obtained for the most general case when the components are statistically dependent. The model is applied to evaluate the wind power system that consists of two wind plants in different regions. An optimization problem is formulated to find the optimal number of wind turbines that must be installed in the wind plants by minimizing the total cost under specific power production. (C) 2017 Elsevier Ltd. All rights reserved.Article Citation - WoS: 8Citation - Scopus: 11Joint Distribution of Run Statistics in Partially Exchangeable Processes(Elsevier Science Bv, 2011) Eryilmaz, SerkanLet {X-i}(i >= 1) be an infinite sequence of recurrent partially exchangeable random variables with two possible outcomes as either "1" (success) or "0" (failure). In this paper we obtain the joint distribution of success and failure run statistics in {X-i}(i >= 1). The results can be used to obtain the joint distribution of runs in ordinary Markov chains, exchangeable and independent sequences. (C) 2010 Elsevier B.V. All rights reserved.
