Wu, Shaomin (2005) Joint Importance of Multistate Systems. Computers and Industrial Engineering, 49 (1). pp. 63-75. ISSN 0360-8352. (doi:10.1016/j.cie.2005.02.001) (KAR id:31025)
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Official URL: http://dx.doi.org/10.1016/j.cie.2005.02.001 |
Abstract
Importance measures in reliability engineering are used to identify weak areas of a system and signify the roles of components in either causing or contributing to proper functioning of the system. Traditional importance measures for multistate systems mainly concern reliability importance of an individual component and seldom consider the utility performance of the systems. This paper extends the joint importance concepts of two components from the binary system case to the multistate system case. A joint structural importance and a joint reliability importance are defined on the basis of the performance utility of the system. The joint structural importance measures the relationship of two components when the reliabilities of components are not available. The joint reliability importance is inferred when the reliabilities of the components are given. The properties of the importance measures are also investigated. A case study for an offshore electrical power generation system is given. © 2005 Elsevier Ltd. All rights reserved.
Item Type: | Article |
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DOI/Identification number: | 10.1016/j.cie.2005.02.001 |
Additional information: | Unmapped bibliographic data: PY - 2005/// [EPrints field already has value set] AD - School of Construction Management and Engineering, University of Reading, Whiteknights, Reading, RG6 6AW, United Kingdom [Field not mapped to EPrints] JA - Comput Ind Eng [Field not mapped to EPrints] |
Uncontrolled keywords: | Birnbaum importance, Joint reliability importance, Joint structural importance, Multistate system, Structural importance, Electric power generation, Industrial engineering, Performance, Reliability, Birnbaum importance, Joint reliability importance, Joint structural importance, Multistate systems, Structural importance, Systems analysis |
Subjects: |
H Social Sciences H Social Sciences > HA Statistics > HA33 Management Science |
Divisions: | Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Depositing User: | Shaomin Wu |
Date Deposited: | 26 Sep 2012 16:21 UTC |
Last Modified: | 16 Nov 2021 10:08 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/31025 (The current URI for this page, for reference purposes) |
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