TY - GEN
T1 - A Fuzzy-Monte Carlo simulation approach for fault tree analysis
AU - Zonouz, Saman Aliari
AU - Miremadi, Seyed Ghassem
PY - 2006
Y1 - 2006
N2 - Fault tree analysis is one of the key approaches used to analyze the reliability of critical systems. Fault trees are usually analyzed using mathematical approaches or Monte Carlo simulation (MCS). This paper presents a Fuzzy-Monte Carlo simulation (FMCS) approach in which the uncertain data is generated by the MCS approach. The FMCS approach is applied to the Weibull probability distribution which is widely been used in the analysis of reliability, availability, maintainability and safety (RAMS). Using the fuzzy arithmetic, times to failure (TTF) of the components are generated. These results are processed by a kind of fault tree (e.g. time-to-failure tree) to produce the TTF of the whole system. The FMCS can estimate the TTF of the system which contains components that fail gradually (e.g. degradation). A comparison between the FMCS and the traditional MCS approaches shows that the time order of the FMCS approach is equal to the multiplication of the time order of the traditional MCS by a fuzzy number's representing the array length.
AB - Fault tree analysis is one of the key approaches used to analyze the reliability of critical systems. Fault trees are usually analyzed using mathematical approaches or Monte Carlo simulation (MCS). This paper presents a Fuzzy-Monte Carlo simulation (FMCS) approach in which the uncertain data is generated by the MCS approach. The FMCS approach is applied to the Weibull probability distribution which is widely been used in the analysis of reliability, availability, maintainability and safety (RAMS). Using the fuzzy arithmetic, times to failure (TTF) of the components are generated. These results are processed by a kind of fault tree (e.g. time-to-failure tree) to produce the TTF of the whole system. The FMCS can estimate the TTF of the system which contains components that fail gradually (e.g. degradation). A comparison between the FMCS and the traditional MCS approaches shows that the time order of the FMCS approach is equal to the multiplication of the time order of the traditional MCS by a fuzzy number's representing the array length.
KW - Fault tree
KW - Fuzzy logic
KW - Fuzzy probability
KW - Monte Carlo simulation
KW - Reliability analysis
KW - Time-to-failure tree
UR - http://www.scopus.com/inward/record.url?scp=34250200106&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34250200106&partnerID=8YFLogxK
U2 - 10.1109/RAMS.2006.1677412
DO - 10.1109/RAMS.2006.1677412
M3 - Conference contribution
AN - SCOPUS:34250200106
SN - 1424400074
SN - 9781424400072
T3 - Proceedings - Annual Reliability and Maintainability Symposium
SP - 428
EP - 433
BT - Annual Reliability and Maintainability Symposium, RAMS'06 - 2006 Proceedings
T2 - 2006 Annual Reliability and Maintainability Symposium, RAMS'06
Y2 - 23 January 2006 through 26 January 2006
ER -