Computing Optimal Replacement Time and Mean Residual Life in Reliability Shock Models

No Thumbnail Available

Date

2017

Authors

Journal Title

Journal ISSN

Volume Title

Publisher

Pergamon-elsevier Science Ltd

Open Access Color

OpenAIRE Downloads

OpenAIRE Views

Research Projects

Organizational Units

Thumbnail Image
Organizational Unit
Industrial Engineering
(1998)
Industrial Engineering is a field of engineering that develops and applies methods and techniques to design, implement, develop and improve systems comprising of humans, materials, machines, energy and funding. Our department was founded in 1998, and since then, has graduated hundreds of individuals who may compete nationally and internationally into professional life. Accredited by MÜDEK in 2014, our student-centered education continues. In addition to acquiring the knowledge necessary for every Industrial engineer, our students are able to gain professional experience in their desired fields of expertise with a wide array of elective courses, such as E-commerce and ERP, Reliability, Tabulation, or Industrial Engineering Applications in the Energy Sector. With dissertation projects fictionalized on solving real problems at real companies, our students gain experience in the sector, and a wide network of contacts. Our education is supported with ERASMUS programs. With the scientific studies of our competent academic staff published in internationally-renowned magazines, our department ranks with the bests among other universities. IESC, one of the most active student networks at our university, continues to organize extensive, and productive events every year.

Journal Issue

Abstract

In this paper, matrix-based methods are presented to compute the optimal replacement time and mean residual lifetime of a system under particular class of reliability shock models. The times between successive shocks are assumed to have a common continuous phase-type distribution. The system's lifetime is represented as a compound random variable and some properties of phase-type distributions are utilized. Extreme shock model, run shock model, and generalized extreme shock model are shown to be the members of this class. Graphical illustrations and numerical examples are presented for the run shock model when the interarrival times between shocks follow Erlang distribution. (C) 2016 Elsevier Ltd. All rights reserved.

Description

Eryilmaz, Serkan/0000-0002-2108-1781
ORCID
Eryilmaz, Serkan ORCID logo

Keywords

Mean residual lifetime, Optimal replacement time, Phase-type distributions, Reliability, Shock model

Turkish CoHE Thesis Center URL

Fields of Science

Citation

52

WoS Q

Q1

Scopus Q

Source

Volume

103

Issue

Start Page

40

End Page

45

URI

https://doi.org/10.1016/j.cie.2016.11.017
 https://hdl.handle.net/20.500.14411/585

Collections

WOS
Scopus