题 目：Estimation of Field Reliability Based on Aggregate Lifetime Data（基于聚合寿命数据的外场可靠性分析）

演 讲 人：陈飘博士，荷兰代尔夫特理工大学

主 持 人：翟庆庆博士，上海大学管理学院

时 间：2020年10月27日（周二），下午4:00

地 点：校本部东区管理学院467室

主办单位：上海大学管理学院、上海大学管理学院青年教师联谊会

演讲人简介：

陈飘博士现为荷兰代尔夫特理工大学代尔夫特应用数学中心助理教授。陈飘博士2013年本科毕业于上海交通大学工业工程专业，2017年博士毕业于新加坡国立大学工业系统工程与管理系。当前主要的研究领域为统计分析方法、传染病传播建模、生存分析与退化建模等，发表多篇高水平研究论文，包括工业统计与工程的顶级刊物如Technometrics, Journal of Quality Technology, Statistics in Medicine, Naval Research Logistics, IISE Transactions, European Journal of Operational Research, IEEE Transactions on Reliability, Reliability Engineering & System Safety等。

演讲内容简介：

Many large organizations have developed ambitious programs to build reliability databases by collecting field failure data from a large variety of components. To make the database concise, the component lifetime data are recorded in an aggregate way in these databases. The data format is different from traditional lifetime data and the statistical inference is challenging. In this talk, we propose a general parametric estimation framework for the aggregate data. We first address the failure-censored aggregate data, where each data point is a summation of a series of collective failures representing the cumulative operating time of one component position from system commencement to the last component replacement. Then, we consider the time-censored aggregate data, where only the number of component replacements in a component position during an operation time interval is reported. An approximate Bayesian computation algorithm that does not require evaluating the likelihood function is proposed, and a model selection procedure is proposed to identify an appropriate model for the time-censored aggregate data.

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