Probability box as a tool to model and control the effect of epistemic uncertainty in multiple dependent competing failure processes |
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| Affiliation: | 1. School of Reliability and Systems Engineering, Beihang University, Beijing, China;2. Chair on Systems Science and Energetic Challenge, Fondation Electricité de France (EDF), CentraleSupelec, Universite’ Paris-Saclay, Chatenay-Malabry, France;3. Energy Department, Politecnico di Milano, Italy;1. School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, Shaanxi, 710049, P.R. China;2. College of Material Management and Safety Engineering, Air Force Engineering University, Xi’an, Shaanxi, 710051, P.R. China;3. State Key Laboratory of Complex System Simulation, Beijing Institute of System Engineering, Beijing, P.R. China;1. State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, Hunan, People''s Republic of China;2. Institute for Computer Science in Civil Engineering, Leibniz University of Hannover, Callinstr. 34, 30167 Hannover, Germany;3. Institute for Risk & Uncertainty, School of Engineering, University of Liverpool, Brodie Tower, Brownlow Street, Liverpool L69 3GQ, United Kingdom;4. School of Civil Engineering & Shanghai Institute of Disaster Prevention and Relief, Tongji University, China;1. Department of Systems Engineering and Engineering Management, City University of Hong Kong, Kowloon, Hong Kong;2. Department of Industrial Management, National Taiwan University of Science and Technology, Taipei, Taiwan;3. College of Mechanical and Electronic Engineering, China University of Petroleum, Qingdao, Shandong 266580, China |
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| Abstract: | Engineering components and systems are often subject to multiple dependent competing failure processes (MDCFPs). MDCFPs have been well studied in literature and various models have been developed to predict the reliability of MDCFPs. In practice, however, due to the limited resource, it is often hard to estimate the precise values of the parameters in the MDCFP model. Hence, the predicted reliability is affected by epistemic uncertainty. Probability box (P-box) is applied in this paper to describe the effect of epistemic uncertainty on MDCFP models. A dimension-reduced sequential quadratic programming (DRSQP) method is developed for the construction of P-box. A comparison to the conventional construction method shows that DRSQP method reduces the computational costs required for P-box constructions. Since epistemic uncertainty reflects the unsureness in the predicted reliability, a decision maker might want to reduce it by investing resource to more accurately estimate the value of each model parameter. A two-stage optimization framework is developed to allocate the resource among the parameters and ensure that epistemic uncertainty is reduced in a most efficient way. Finally, the developed methods are applied on a real case study, a spool valve, to demonstrate their validity. |
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| Keywords: | Reliability modeling Multiple dependent competing failure process Epistemic uncertainty Reliability box SQP method |
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