TY - GEN
T1 - Reliability analysis of phased-mission systems
T2 - 2006 Annual Reliability and Maintainability Symposium, RAMS'06
AU - Alam, Mansoor
AU - Song, Min
AU - Hester, Steven L.
AU - Seliga, Thomas A.
PY - 2006
Y1 - 2006
N2 - This paper presents a novel and simple approach to reliability analysis of phased-mission systems. The technique presented in this paper transforms a phased-mission system into several non-phased-mission systems, and thus allows each phase to be modeled separately. The mission succeeds as long as every phase successively executes its requirements, and failed component(s) of any phase is(are) repaired so that the system is in a successful state before as well as after it begins the next phase. Alternative mission success scenarios are also readily definable within this context The benefit of this simplified approach is that it provides a practical implementation for the reliability analysis of phased-mission systems. The different phases of the system are computed independently, and the duration and the structure of the phases are left to the designer or manager. If the requirements of the mission change during execution of the mission (duration of a phase or the sequence of phases), the impact of the change in mission objectives is easily found without recomputing the applicable or operative Markov model. This is due to the fact that all of the reliability analysis data are presented over the entire mission duration consisting for all phases, and the initial and final probabilities can easily be found by examining the output reliability data instead of recomputing the model.
AB - This paper presents a novel and simple approach to reliability analysis of phased-mission systems. The technique presented in this paper transforms a phased-mission system into several non-phased-mission systems, and thus allows each phase to be modeled separately. The mission succeeds as long as every phase successively executes its requirements, and failed component(s) of any phase is(are) repaired so that the system is in a successful state before as well as after it begins the next phase. Alternative mission success scenarios are also readily definable within this context The benefit of this simplified approach is that it provides a practical implementation for the reliability analysis of phased-mission systems. The different phases of the system are computed independently, and the duration and the structure of the phases are left to the designer or manager. If the requirements of the mission change during execution of the mission (duration of a phase or the sequence of phases), the impact of the change in mission objectives is easily found without recomputing the applicable or operative Markov model. This is due to the fact that all of the reliability analysis data are presented over the entire mission duration consisting for all phases, and the initial and final probabilities can easily be found by examining the output reliability data instead of recomputing the model.
KW - Markov modeling
KW - Phased-mission systems
KW - Reliability
KW - State transition rate matrix
UR - http://www.scopus.com/inward/record.url?scp=34250210557&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=34250210557&partnerID=8YFLogxK
U2 - 10.1109/RAMS.2006.1677431
DO - 10.1109/RAMS.2006.1677431
M3 - Conference contribution
AN - SCOPUS:34250210557
SN - 1424400074
SN - 9781424400072
T3 - Proceedings - Annual Reliability and Maintainability Symposium
SP - 551
EP - 558
BT - Annual Reliability and Maintainability Symposium, RAMS'06 - 2006 Proceedings
Y2 - 23 January 2006 through 26 January 2006
ER -