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Reduction of System Reliability Model Uncertainty by Considering Dependent Components With Stochastic Process Loading

[+] Author Affiliations
Yao Cheng, Xiaoping Du

Missouri University of Science and Technology, Rolla, MO

Paper No. DETC2016-59260, pp. V01AT02A021; 10 pages
doi:10.1115/DETC2016-59260
From:
  • ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 1A: 36th Computers and Information in Engineering Conference
  • Charlotte, North Carolina, USA, August 21–24, 2016
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5007-7
  • Copyright © 2016 by ASME

abstract

When component dependence is ignored, a system reliability model may have large model (epistemic) uncertainty with wide reliability bounds. This makes decision making difficult during the system design. Component dependence exists due to the shared environment and operation conditions. It is difficult for system designers to model component dependence because they may not have access to component design details if the components are designed and manufactured by outside suppliers. This research intends to reduce the system reliability model uncertainty with a new way for system designers to consider the component dependence implicitly and automatically without knowing component design details. The proposed method is applicable for a wide range of applications where the time-dependent system stochastic load is shared by components of the system. Simulation is used to obtain the extreme value of the system load for a given period of time, and optimization is employed to estimate the system reliability interval. As a result, the epistemic uncertainty in system reliability can be reduced.

Copyright © 2016 by ASME

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