Bozbulut, Ali Rıza

Profile URL
https://hdl.handle.net/20.500.14411/7685
Name Variants
A.,Bozbulut B.,Ali Riza Bozbulut,A.R. B.,Ali Rıza B., Ali Riza A., Bozbulut Ali Rıza, Bozbulut Ali Riza, Bozbulut Bozbulut, Ali Rıza Bozbulut, Ali Riza A.R.Bozbulut
Job Title
Doktor Öğretim Üyesi
Email Address
ali.bozbulut@atilim.edu.tr
Main Affiliation
Industrial Engineering
Status
Former Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
No research topics data found.

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Scholarly Output

5

Articles

5

Views / Downloads

3/0

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

127

Scopus Citation Count

142

Patents

0

Projects

0

WoS Citations per Publication

25.40

Scopus Citations per Publication

28.40

Open Access Source

1

Supervised Theses

0

JournalCount
Communications in Statistics - Simulation and Computation1
Computers & Industrial Engineering1
Dependence Modeling1
Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability1
Reliability Engineering & System Safety1
Current Page: 1 / 1

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2014 - 20195

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Author of Publication: search.filters.isAuthorOfPublication.054e58f5-490e-47ba-8d7d-30c492dd8766

Scholarly Output Search Results

Now showing 1 - 5 of 5
  • Article
    Citation - WoS: 7
    Citation - Scopus: 7
    A Generalized Class of Correlated Run Shock Models
    (de Gruyter Poland Sp Zoo, 2018-06-28) Yalcin, Femin; Eryilmaz, Serkan; Bozbulut, Ali Riza
    In this paper, a generalized class of run shock models associated with a bivariate sequence {(X-i, Y-i)}(i >= 1) of correlated random variables is defined and studied. For a system that is subject to shocks of random magnitudes X-1, X-2, ... over time, let the random variables Y-1, Y-2, ... denote times between arrivals of successive shocks. The lifetime of the system under this class is defined through a compound random variable T = Sigma(N)(t=1) Y-t, where N is a stopping time for the sequence {Xi}(i >= 1) and represents the number of shocks that causes failure of the system. Another random variable of interest is the maximum shock size up to N, i.e. M = max {X-i, 1 <= i <= N}Distributions of T and M are investigated when N has a phase-type distribution.
  • Article
    Citation - WoS: 30
    Citation - Scopus: 32
    Computing Marginal and Joint Birnbaum, and Barlow-Proschan Importances in Weighted-<i>k</I>-out-of-<i>n< Systems
    (Pergamon-elsevier Science Ltd, 2014-06) Eryilmaz, Serkan; Bozbulut, Ali Riza
    A weighted-k-out-of-n:G system is a system that consists of n binary components, each with its own positive weight, and operates only when the total weight of working components is at least k. Such a structure is useful when the components have different contributions to the performance of the entire system. This paper is concerned with both marginal and joint Birnbaum, and Barlow-Proschan (BP) importances of the components in weighted- k-out-of-n:G systems. The method of universal generating function is used for computing marginal and joint Birnbaum importances. The method for computing BP-importance is based on a direct probabilistic approach. Extensive numerical calculations are presented. By the help of these calculations and illustrations, it is possible to observe how the marginal and joint importances change with respect to the weights of components. (C) 2014 Elsevier Ltd. All rights reserved.
  • Article
    Citation - WoS: 38
    Citation - Scopus: 45
    An Algorithmic Approach for the Dynamic Reliability Analysis of Non-Repairable Multi-State Weighted <i>k</I>-out-of-<i>n< System
    (Elsevier Sci Ltd, 2014-11) Eryilmaz, Serkan; Bozbulut, Ali Riza; Riza Bozbulut, Ali
    In this paper, we study a multi-state weighted k-out-of-n:G system model in a dynamic setup. In particular, we study the random time spent by the system with a minimum performance level of k. Our method is based on ordering the lifetimes of the system's components in different state subsets. Using this ordering along with the Monte-Carlo simulation algorithm, we obtain estimates of the mean and survival function of the time spent by the system in state k or above. We present illustrative computational results when the degradation in the components follows a Markov process. (C) 2014 Elsevier Ltd. All rights reserved.
  • Article
    Citation - WoS: 28
    Citation - Scopus: 32
    Generalized Extreme Shock Models and Their Applications
    (Taylor & Francis inc, 2018-11-29) Bozbulut, Ali Riza; Eryilmaz, Serkan
    In the classical extreme shock model, the system fails due to a single catastrophic shock. In this paper, by assuming different arrival patterns of the shocks, two new types of extreme shock models are introduced. In these models, m possible sources may exert shocks on the system. Both models reduce to the classical extreme shock model when m = 1. Assuming phase-type distribution for times between successive shocks, we obtain survival functions and mean time to failure values of the system under new models. Two different optimization problems are also considered to determine the optimal number of sources.
  • Article
    Citation - WoS: 24
    Citation - Scopus: 26
    Reliability Analysis of Weighted-K System Consisting of Three-State Components
    (Sage Publications Ltd, 2019-05-30) Eryilmaz, Serkan; Bozbulut, Ali Riza
    The reliability of a weighted-k-out-of-n system that consists of three-state components is studied. The system is assumed to comprise n three-state components, namely, perfect functioning, partial working, and complete failure and functions if the total weight of all the working components is at least k. Reliability expressions are presented when the times spent by components in perfect functioning and partial working states are dependent with a given joint distribution. Sufficient conditions are also provided to compare the expected total weights of two systems.