contributor author | Cheng, Yao | |
contributor author | Conrad, Daniel C. | |
contributor author | Du, Xiaoping | |
date accessioned | 2017-11-25T07:20:35Z | |
date available | 2017-11-25T07:20:35Z | |
date copyright | 2017/16/5 | |
date issued | 2017 | |
identifier issn | 1530-9827 | |
identifier other | jcise_017_04_041007.pdf | |
identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4236544 | |
description abstract | Incomplete component information may lead to wide bounds for system reliability prediction, making decisions difficult in the system design stage. The missing information is often the component dependence, which is a crucial source for the exact system reliability estimation. Component dependence exists due to the shared environment and operating conditions. But it is difficult for system designers to model component dependence because they may have limited information about component design details if outside suppliers designed and manufactured the components. This research intends to produce narrow system reliability bounds 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 bounds, which are narrower than those from the traditional method with independent component assumption and completely dependent component assumption. Examples are provided to demonstrate the proposed method. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Narrower System Reliability Bounds With Incomplete Component Information and Stochastic Process Loading | |
type | Journal Paper | |
journal volume | 17 | |
journal issue | 4 | |
journal title | Journal of Computing and Information Science in Engineering | |
identifier doi | 10.1115/1.4035530 | |
journal fristpage | 41007 | |
journal lastpage | 041007-11 | |
tree | Journal of Computing and Information Science in Engineering:;2017:;volume( 017 ):;issue: 004 | |
contenttype | Fulltext | |