Harbin Institute of Technology, China
Title: A New Class of Multi-stress Acceleration Models with Interaction Effects and Its Extension
to Accelerated Degradation Modelling
Abstract: Most products operate under multiple stresses. The influences of multi-stress factors on products are commonly not independent and promote a more violent degradation through interactions, referred to as stress interaction effects. This presentation brings a new class of multi-stress acceleration models with interaction effects to extrapolate more accurate reliability metrics under multi-stress operating conditions. Furthermore, this multi-stress acceleration model is extended to an accelerated degradation model by integrating a generalized Wiener process with nonlinear time scale functions and random effects. The acceleration factor constant principle is utilized to identify the stress-dependent parameters, facilitating a more appropriate model development. A real-world case is performed to validate the effectiveness and practical values of the proposed model in reliability assessment under multi-stress operating conditions.
Biodata: Professor Xuerong Ye is the Vice Dean of School of Electrical Engineering and Automation, Harbin Institute of Technology. He is also the Vice Director of the Key Laboratory of Electric Apparatus and Electronics Reliability Technology of Heilongjiang Province. Now, he is a Fellow of IET, the associate editor of IEEE Access and Journal of Power Electronics. He received his Ph.D. degree in electrical engineering in 2009 from Harbin Institute of Technology. His main research interests include failure analysis, reliability assessment and robust design of electric apparatus and electronics. He has won the first and second award of the ministerial Science and Technology Progress in 2021 and 2018, respectively. He has also been awarded national youth talent. He has chaired 20 research projects, published more than 100 papers, and owned more than 40 authorized patents.
Nanjing University Of Science and Technology
Title: Reliability models and Maintenance Planning for Systems with Dependent Auxiliary
Abstract: In many engineering systems, aside from the main components fulfilling the essential functions, some components are configured to protect the main components and improve the reliability of the system. Failures of these protective components (named as auxiliary components) do not halt the system directly like the main components, but may influence the failure process of the main components or even the auxiliary subsystem itself. Such dependence is commonly observed but has seen limited research. In this talk, recent studies on the systems with dependent auxiliary components are introduced. Firstly, mechanism of the system dynamic features and dependence abstracted from the actual background and the existing literature is discussed. Based on the discussions, two reliability models are developed: In model I the auxiliary components are regarded as a whole and only the dependence between the main and auxiliary subsystems are taken into consideration, while in Model II the structure of the auxiliary components and their dependence are further considered. Mathematical methods are proposed to evaluate the system reliability of such systems. Moreover, considering most of the auxiliary component failures are hidden, different inspection and maintenance policies are designed for such systems, based on which some optimization problems are formulated and solved. Finally, some numerical examples, together with sensitivity studies of some model parameters, are presented to show the efficiency of the models and how the evolution of the parameters influences the optimal strategies.
Biodata: Jingyuan Shen is an associate professor in the School of Economics & Management at Nanjing University of Science & Technology. She received her B.S. degree in Information and Computing Science from Minzu University of China in 2012 and Ph.D. degree in the School of Management & Economics from Beijing Institute of Technology of China in 2018. She was a research fellow with the Department of Industrial Systems Engineering and Management, National University of Singapore from 2018 to 2019. Her research interests include system reliability, maintenance optimization, stochastic modeling and applications of probability. Her work has appeared in journals including IISE Transactions, IEEE Transactions on Reliability, Reliability Engineering & System Safety.
University of Alberta, Canada
Title: Condition Based Maintenance Optimization for Wind Power Systems
Abstract: By utilizing condition monitoring and prediction information for wind turbines, condition based maintenance (CBM) strategy can be used to reduce the operation and maintenance costs and enhance system reliability. There are economic dependencies among wind turbines and their subassemblies. That is, once a maintenance team is sent to the wind farm, it may be more economical to take the opportunity to maintain multiple turbines, and when a turbine is stopped for maintenance, it may be more cost-effective to simultaneously maintain multiple subassemblies which show relatively high risks. A CBM approach is presented to consider the economic dependency. Furthermore, a CBM approach is developed considering component level repairs and economic dependency. There are multiple components in a subassembly, e.g. the generator consists of components like generator rotor, generator bearings, contactor, etc. Component level major and minor repairs and their costs can be modeled explicitly in a more realistic and accurate way. Examples are used to demonstrate the proposed approach.
Biodata: Dr. Tian’s research is focused on Prognostics, Pipeline integrity management, Reliability, Condition based maintenance, Renewable energy systems, Condition monitoring, Signal processing, and Finite element modeling. His research papers have appeared in IEEE Transactions on Reliability, Mechanical Systems and Signal Processing, Renewable Energy, and IIE Transactions, among others. He received the Best Paper Award of “Quality Control and Reliability” in the 2005 IIE Industrial Engineering Research Conference. He is also the recipient of the 2011 Petro-Canada Young Innovator Award (Technology, Industry, and the Environment). (More)
Northwestern Polytechnical University, China
Title: Title: Recent Works in System Reliability Optimization Driven by Importance Measures
Abstract: Reliability optimization has been widely discussed for complex systems to maximize system reliability with resource constraints. However, it is usually a NP-hard combinatorial optimization problem which is difficult to find the optimal assignment within reasonable time. Importance measure (IM) is a well-known method for evaluating the effect of component reliability on system reliability. Many IMs are proposed for binary, multistate, and continuous systems by considering different points of interest. Recently, these IMs have been applied in allocating limited resources to the component to optimize system performance. The optimization rules for simple systems are summarized which enhance system reliability by using IMs ranking directly. The optimization algorithms for complex or large-scale systems are also developed to obtain remarkable solutions by introducing IMs-based local search. Finally, a general framework for reliability optimization driven by IM is established and some practical applications are demonstrated. Furthermore, some challenges in system reliability optimization that need to be solved in the future are presented.
Biodata: Mr. Zhiqiang Cai received B.S. degree (2003), M.S. degree (2006), and Ph.D. degree (2010) from Northwestern Polytechnical University (NPU) in China, with 1-year joint doctoral study in Ecole Centrale Paris, France (2007-2008) under China Scholarship Council. Currently, he is the Professor and Chair of Department of Industrial Engineering (NPU), the secretary-general of Industrial Engineering and Management Branch (Shaanxi Provincial Institute of Mechanical Engineering).
Dr. Cai's research focuses on reliability modelling, importance measures and reliability optimization for complex systems. He have launched a research group as principal investigator under the support of National Natural Science Foundation of China, Foreign Experts Project of Ministry of Science and Technology, Aeronautical Science Foundation of China, Key R&D Program of Shaanxi Province and Basic Research Project of Natural Science of Shaanxi Province. In recent 5 years, he has published more than 40 papers in top international journals, including ITR, RESS, TII, AMM and AMC. He has also been granted 8 Chinese invention patents and awarded the Best Paper of 2022 IEEE PHM, the Outstanding Paper of 2019 IEEE IEEM, and the Best Paper of 2019 QR2MSE.
© SRSE 2019-2023 | Beijing, China | Email: email@example.com