Abstract
Multistate systems (MSS) are systems in which the system and its components are characterized by multiple states or performance levels. Component importance or sensitivity analysis facilitates the identification of vulnerabilities within the system, and aids in the quantification of criticalities of the system components. Multistate component importance analysis poses unique challenges to existing methods that are primarily based on binary-state applications. This paper presents an analytical method based on multistate multivalued decision diagrams (MMDD) for multistate component importance analysis. The contribution of this work is two-fold: 1) a novel, efficient algorithm for directly generating an MMDD model from multistate capacity network specifications without inefficient enumeration of multistate minimal path or cut vectors; and 2) an efficient, exact MMDD-based approach for evaluating MSS reliability and importance measures. The advantages of the proposed method are illustrated through a comparison with existing methods, and through detailed analyses of three case studies.
| Original language | English (US) |
|---|---|
| Article number | 5524103 |
| Pages (from-to) | 581-592 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Reliability |
| Volume | 59 |
| Issue number | 3 |
| DOIs | |
| State | Published - Sep 1 2010 |
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All Science Journal Classification (ASJC) codes
- Safety, Risk, Reliability and Quality
- Electrical and Electronic Engineering
Keywords
- Composite importance measure
- Monte Carlo simulation
- multistate multivalued decision diagram
- multistate system
Cite this
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An efficient multistate multivalued decision diagram-based approach for multistate system sensitivity analysis. / Shrestha, Akhilesh; Xing, Liudong; Coit, David W.
In: IEEE Transactions on Reliability, Vol. 59, No. 3, 5524103, 01.09.2010, p. 581-592.Research output: Contribution to journal › Article
TY - JOUR
T1 - An efficient multistate multivalued decision diagram-based approach for multistate system sensitivity analysis
AU - Shrestha, Akhilesh
AU - Xing, Liudong
AU - Coit, David W.
PY - 2010/9/1
Y1 - 2010/9/1
N2 - Multistate systems (MSS) are systems in which the system and its components are characterized by multiple states or performance levels. Component importance or sensitivity analysis facilitates the identification of vulnerabilities within the system, and aids in the quantification of criticalities of the system components. Multistate component importance analysis poses unique challenges to existing methods that are primarily based on binary-state applications. This paper presents an analytical method based on multistate multivalued decision diagrams (MMDD) for multistate component importance analysis. The contribution of this work is two-fold: 1) a novel, efficient algorithm for directly generating an MMDD model from multistate capacity network specifications without inefficient enumeration of multistate minimal path or cut vectors; and 2) an efficient, exact MMDD-based approach for evaluating MSS reliability and importance measures. The advantages of the proposed method are illustrated through a comparison with existing methods, and through detailed analyses of three case studies.
AB - Multistate systems (MSS) are systems in which the system and its components are characterized by multiple states or performance levels. Component importance or sensitivity analysis facilitates the identification of vulnerabilities within the system, and aids in the quantification of criticalities of the system components. Multistate component importance analysis poses unique challenges to existing methods that are primarily based on binary-state applications. This paper presents an analytical method based on multistate multivalued decision diagrams (MMDD) for multistate component importance analysis. The contribution of this work is two-fold: 1) a novel, efficient algorithm for directly generating an MMDD model from multistate capacity network specifications without inefficient enumeration of multistate minimal path or cut vectors; and 2) an efficient, exact MMDD-based approach for evaluating MSS reliability and importance measures. The advantages of the proposed method are illustrated through a comparison with existing methods, and through detailed analyses of three case studies.
KW - Composite importance measure
KW - Monte Carlo simulation
KW - multistate multivalued decision diagram
KW - multistate system
UR - http://www.scopus.com/inward/record.url?scp=77956345142&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77956345142&partnerID=8YFLogxK
U2 - 10.1109/TR.2010.2055922
DO - 10.1109/TR.2010.2055922
M3 - Article
AN - SCOPUS:77956345142
VL - 59
SP - 581
EP - 592
JO - IEEE Transactions on Reliability
JF - IEEE Transactions on Reliability
SN - 0018-9529
IS - 3
M1 - 5524103
ER -