Session: 14C, Thursday, 28 January 2010, 1015-1215 Moderator: Mike Silverman, Ops A La Carte
This session covers multi objective optimization, Reliability Based design Optimization, Robust Design, Markov Modeling, Shock base degradation systems, Software Reliability Predictions methods in several industrial applications.
Papers: 14C1 [0066] ACCURATE MODELING OF SHARED COMPONENTS IN HIGH RELIABILITY APPLICATIONSÂ by Julia V. Bukowski, Ph.D., Villanova University and Chris O’Brien, Exida International standards for safety system evaluation require that shared components either be accurately modeled or not be used. This paper shows how to accurately model shared components in safety instrumented systems.
14C2 [0209] COMMON CAUSE FAILURES: IMPLEMENTATION OF A SIMPLIFIED ALPHA FACTOR MODELÂ by Colie Warren, Lockheed Martin Space Systems Company
The selected methodology used to quantify the risk of common cause failures can have a large impact on both probabilistic risk assessment (PRA) model complexity and the resulting estimation of risk. This paper is intended to provide PRA analysts in space and other industries with practical guidance for implementing a simplification of the common cause Alpha Factor method that reduces model complexity while allowing the analyst to tailor risk to specific component failure criteria.
14C3 [0079] A MULTI-OBJECTIVE MEMETIC ALGORITHM FOR RBDO AND ROBUST DESIGN by Xiaotian Zhuang and Rong Pan, Ph.D., Arizona State University Reliability and Robustness are two important attributes of product design under uncertainty. So it is necessary to establish a probabilistic multi-objective problem to combine reliability and robustness considerations, where the products performance and the variation of performance are simultaneously optimized, subject to probabilistic constraints for design feasibility. An efficient Multi-Objective Memetic Algorithm (MOMA) is presented here to optimize reliability and robustness simultaneously.
14C4 [0104] DEGRADED SYSTEMS WITH MULTIPLE PERFORMANCE PARAMETERS SUBJECT TO SHOCKS by Chun-yang Li, Xun Chen, Xiao-shan Yi, Institution of Mechatronics Engineering, and Jun-yong Tao, National University of Defense Technology The reliability of degraded systems with multiple performance parameters subject to random shocks is predicted in this paper when the degradation processes of performance parameters are independent and dependent. The system performance and shock magnitude must be not less than zero, so the effect caused by ranges of the system performance and shock magnitude is discussed.
Performance-Based Reliability Modeling Methods
Session: 14C, Thursday, 28 January 2010, 1015-1215
Moderator: Mike Silverman, Ops A La Carte
This session covers multi objective optimization, Reliability Based design Optimization, Robust Design, Markov Modeling, Shock base degradation systems, Software Reliability Predictions methods in several industrial applications.
Papers:
14C1 [0066] ACCURATE MODELING OF SHARED COMPONENTS IN HIGH RELIABILITY APPLICATIONSÂ by Julia V. Bukowski, Ph.D., Villanova University and Chris O’Brien, Exida
International standards for safety system evaluation require that shared components either be accurately modeled or not be used. This paper shows how to accurately model shared components in safety instrumented systems.
14C2 [0209] COMMON CAUSE FAILURES: IMPLEMENTATION OF A SIMPLIFIED ALPHA FACTOR MODELÂ by Colie Warren, Lockheed Martin Space Systems Company
The selected methodology used to quantify the risk of common cause failures can have a large impact on both probabilistic risk assessment (PRA) model complexity and the resulting estimation of risk. This paper is intended to provide PRA analysts in space and other industries with practical guidance for implementing a simplification of the common cause Alpha Factor method that reduces model complexity while allowing the analyst to tailor risk to specific component failure criteria.
14C3 [0079] A MULTI-OBJECTIVE MEMETIC ALGORITHM FOR RBDO AND ROBUST DESIGN
by Xiaotian Zhuang and Rong Pan, Ph.D., Arizona State University
Reliability and Robustness are two important attributes of product design under uncertainty. So it is necessary to establish a probabilistic multi-objective problem to combine reliability and robustness considerations, where the products performance and the variation of performance are simultaneously optimized, subject to probabilistic constraints for design feasibility. An efficient Multi-Objective Memetic Algorithm (MOMA) is presented here to optimize reliability and robustness simultaneously.
14C4 [0104] DEGRADED SYSTEMS WITH MULTIPLE PERFORMANCE PARAMETERS SUBJECT TO SHOCKS by Chun-yang Li, Xun Chen, Xiao-shan Yi, Institution of Mechatronics Engineering, and Jun-yong Tao, National University of Defense Technology
The reliability of degraded systems with multiple performance parameters subject to random shocks is predicted in this paper when the degradation processes of performance parameters are independent and dependent. The system performance and shock magnitude must be not less than zero, so the effect caused by ranges of the system performance and shock magnitude is discussed.