讲座时间：2025年11月7日(周五)  16:00-17:00

地点：综合楼615会议室

报告题目：Optimal Replacement Policy for K-out-of-N Systems with Periodic Imperfect Inspections

报告人简介：

胡家文，电子科技大学副研究员，四川省天府峨眉计划科技人才，TCL青年学者。围绕高端装备状态监测与智能运维开展研究，主持国家自然科学基金面上2项和青年1项，四川省重大科技专项2项（校内负责）、重点研发1项（校内负责）、面上项目1项，以及多项工业部门科研任务。以第一/通讯作者在OR、NRL、IISE Transactions、IEEE TII、ITR、RESS等本领域权威期刊发表SCI检索论文25篇；授权发明专利5项；获四川省科技进步三等奖，电子科技大学教学成果一等奖，电子科技大学学术新人奖等。

报告摘要：

The K-out-of-N system structure is widely used in industrial and military applications for its high reliability, and condition-based maintenance is a promising way to enhance maintenance efficiency. While existing studies on inspection and replacement policies often assume perfect inspections, real-world inspections can be imperfect due to noise and disturbances. This study investigates an optimal replacement policy for K-out-of-N systems with periodic imperfect inspections. We model component degradation with a three-state continuous-time Markov chain and use a state-observation matrix for imperfect inspections. We first analyze a 1-out-of-2: G system using a partially observable Markov decision process to derive the optimal policy that minimizes long-run discounted maintenance costs. The resulting maintenance policy is a two dimensional control-limit policy, determined using a value iteration algorithm. We then extend this model to a general K-out-of-N: G system and address the curse of dimensionality with a point-based value iteration method. A numerical study and sensitivity analysis demonstrate the effectiveness of our proposed policy.