Dynamic Behavior of <i>k</I>-out-of-<i>n< Systems

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2011

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Elsevier

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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.

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In 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.

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k-out-of-n:G system, Weighted k-out-of-n:G system, Optimal replacement time, Order statistics, Reliability

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23

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Q4

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Volume

39

Issue

2

Start Page

155

End Page

159

URI

https://doi.org/10.1016/j.orl.2011.02.008
 https://hdl.handle.net/20.500.14411/1332

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