会议通知
工程院院刊《工程管理前沿（英文）》和华中科技大学管理学院将于10月28日下午14:00-16:00在腾讯会议（ID：904 198 747，密码：1028），举办工程管理公益讲坛（四十七）——质量控制与系统维护。
本期讲坛由西北工业大学司书宾教授主持，特别邀请西北工业大学朱文金副教授和天津大学何迎东副研究员做主题报告。
工程院院刊《工程管理前沿（英文）》
华中科技大学管理学院
2024年10月25日
会议议程
会议时间：10月28日下午14:00-16:00（北京时间）
腾讯会议ID：904 198 747，密码：1028
主持人：司书宾，西北工业大学
· 14:00-14:45
Allocating redundancy, maintenance and spare parts for minimizing system cost under decentralized repairs
· 14:45-15:30
· 15:30-16:00
Q&A
嘉宾简介
Wenjin Zhu, associate Professor in Northwestern Polytechnical University. She is mainly engaged in the research of complex system reliability modeling and maintenance decision-making, and the dual-action mechanism of inventory strategy and maintenance decision-making. In the past five years, she has held two research funding supported by the National Natural Science Foundation of China and three provincial and ministerial projects. She has published 15 academic papers in Reliability Engineering and System Safety, Frontiers of Engineering Management and other journals. She has served as a peer reviewer of the top journals in the field of engineering and reliability, such as IISE Transactions, Reliability Engineering and System Safety, IEEE Transactions on Reliability, and Computer & Industrial Engineering and so on.
Reliability-redundancy allocation, preventive maintenance, and spare parts logistics are crucial for achieving system reliability and availability goal. Existing methods often concentrate on specific scopes of the system’s lifetime. This paper proposes a joint redundancy maintenance-inventory allocation model that simultaneously optimizes redundant component, replacement time, spares stocking, and repair capacity. Under reliability and availability criteria, our objective is to minimize the system’s lifetime cost, including design, manufacturing, and operational phases. We develop a unified system availability model based on ten performance drivers, serving as the foundation for the establishment of the lifetime-based resource allocation model. Superimposed renewal theory is employed to estimate spare part demand from proactive and corrective replacements. A bisection algorithm, enhanced by neighborhood exploration, solves the complex mixed-integer, nonlinear optimization problem. The numerical experiments show that component redundancy is preferred and necessary if one of the following situations occurs: extremely high system availability is required, the fleet size is small, the system reliability is immature, the inventory holding is too costly, or the hands-on replacement time is prolonged. The joint allocation model also reveals that there exists no monotonic relation between spares stocking level and system availability.
Yingdong He is an associate research fellow with the College of Management & Economics, Tianjin University, Tianjin, China. He was an Eberly Research Fellow with the Department of Statistics at the Pennsylvania State University during 2018-2020, USA, a visiting scholar with the Department of IMAE at the POSTECH, Korea. His current research interests include quality management and quality engineering, decision analysis and robust optimization. He has published over twenty articles to professional journals, such as Frontiers of Engineering Management, IISE Transactions, IEEE Transactions on Reliability, IEEE Transactions on Cybernetics, IEEE Transactions on Fuzzy Systems, Reliability Engineering & System Safety, International Journal of Production Research, Applied Soft Computing, Information Sciences, Computers & Industrial Engineering, Journal of the Operational Research Society, etc.
The joint optimization of production, maintenance, and quality control has shown effectiveness in reducing long-term operational costs in production systems. However, existing studies often assume that changes in the mean value of product quality characteristics in a deteriorating system follow a specific distribution while keeping variance constant. To address this limitation, we propose an innovative method based on the continuous ranking probability score (CRPS). This method enables the simultaneous detection of changes in mean and variance in nonconformities, thus removing the assumption of a specific distribution for quality characteristics. Our approach focuses on developing optimal strategies for production, maintenance, and quality control to minimize cost per unit of time. Additionally, we employ a stochastic model to optimize the production time allocated to the inventory buffer, resulting in significant cost reductions. The effectiveness of our proposed joint optimization method is demonstrated through comprehensive numerical experiments, sensitivity analysis, and a comparative study. The results show that our method can achieve cost reductions compared to several other related methods, highlighting its practical applicability for manufacturing companies aiming to reduce costs.
主持人简介
背景介绍
Frontiers of Engineering Management
工程管理公益讲坛
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E-mail：fem@hust.edu.cn
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