Component state-based integrated importance measure for multi-state systems

Importance measures in reliability engineering are used to identify weak components and/or states in contributing to the reliable functioning of a system. Traditionally, importance measures do not consider the possible effect of groups of transition rates among different component states, which, however, has great effect on the component probability distribution and should therefore be taken into consideration. This paper extends the integrated importance measure (IIM) to estimate the effect of a component residing at certain states on the performance of the entire multi-state systems. This generalization of IIM describes in which state it is most worthy to keep the component to provide the desired level of system performance, and which component is the most important to keep in some state and above for improving the performance of the system. An application to an oil transportation system is presented to illustrate the use of the suggested importance measure.

[1]  Bent Natvig,et al.  Simulation based analysis and an application to an offshore oil and gas production system of the Natvig measures of component importance in repairable systems , 2009, Reliab. Eng. Syst. Saf..

[2]  J. Sethuraman,et al.  Multistate Coherent Systems. , 1978 .

[3]  M. Cheok,et al.  Use of importance measures in risk-informed regulatory applications , 1998 .

[4]  Z W Birnbaum,et al.  ON THE IMPORTANCE OF DIFFERENT COMPONENTS IN A MULTICOMPONENT SYSTEM , 1968 .

[5]  Bent Natvig,et al.  Multistate Systems Reliability Theory with Applications , 2011 .

[6]  W. E. Vesely,et al.  A time-dependent methodology for fault tree evaluation , 1970 .

[7]  B. Natvig A suggestion of a new measure of importance of system components , 1979 .

[8]  David W. Coit,et al.  Composite importance measures for multi-state systems with multi-state components , 2005, IEEE Transactions on Reliability.

[9]  Bent Natvig Measures of Component Importance in Nonrepairable and Repairable Multistate Strongly Coherent Systems , 2011 .

[10]  David A. Butler A complete importance ranking for components of binary coherent systems, with extensions to multi-state systems , 1979 .

[11]  Anatoly Lisnianski,et al.  Extended block diagram method for a multi-state system reliability assessment , 2007, Reliab. Eng. Syst. Saf..

[12]  David W. Coit,et al.  Multi-state component criticality analysis for reliability improvement in multi-state systems , 2007, Reliab. Eng. Syst. Saf..

[13]  Shaomin Wu,et al.  Performance utility-analysis of multi-state systems , 2003, IEEE Trans. Reliab..

[14]  J. B. Fussell,et al.  How to Hand-Calculate System Reliability and Safety Characteristics , 1975, IEEE Transactions on Reliability.

[15]  Kishor S. Trivedi Probability and Statistics with Reliability, Queuing, and Computer Science Applications , 1984 .

[16]  Shenggui Zhang,et al.  Integrated Importance Measure of Component States Based on Loss of System Performance , 2012, IEEE Transactions on Reliability.

[17]  B. Natvig NEW LIGHT ON MEASURES OF IMPORTANCE OF SYSTEM COMPONENTS , 1984 .

[18]  Gregory Levitin,et al.  Multi-State System Reliability - Assessment, Optimization and Applications , 2003, Series on Quality, Reliability and Engineering Statistics.

[19]  Bent Natvig,et al.  Measures of component importance in repairable multistate systems - a numerical study , 2011, Reliab. Eng. Syst. Saf..

[20]  Shenggui Zhang,et al.  Integrated importance measures of multi-state systems under uncertainty , 2010, Comput. Ind. Eng..

[21]  Bent Natvig ON THE REDUCTION IN REMAINING SYSTEM LIFETIME DUE TO THE FAILURE OF A SPECIFIC COMPONENT , 1982 .

[22]  W. Griffith MULTISTATE RELIABILITY MODELS , 1980 .

[23]  Bent Natvig,et al.  New Results on the Barlow–Proschan and Natvig Measures of Component Importance in Nonrepairable and Repairable Systems , 2008 .

[24]  F. Proschan,et al.  Importance of System Components and Fault Tree Events. , 1975 .