题 目：Nonparametric CUSUM and EWMA Control Charts for Detecting Mean Shifts
主讲人：李苏一博士 （管理工程系）
时 间：2013年3月18日（星期二） 中午12:00-13:00
地 点：主楼418会议室
主讲人简介：
    李苏一博士，男，2013年11月加入12BET管理与经济学院管理工程系。2004年至2011年于新加坡国立大学工业与系统工程系硕博连读，并获得博士学位。1998年至2002年于天津大学12BET工业工程系学习，并获得学士学位。李博士曾在世界知名电子制造及半导体企业质量部门工作，并获得六西格玛黑带资格，在企业质量管理与六西格玛培训方面具有丰富的实践经验；同时，对风险分析与管理也有所研究。近年来，部分研究成果已发表于国际知名期刊：Journal of Quality Technology, Risk Analysis, Accident Analysis and Prevention.
内容简介：
Nonparametric control charts are useful when the underlying process distribution is not likely to be normal or is unknown. We propose two nonparametric analog of the CUSUM and EWMA control charts based on the Wilcoxon rank-sum test for detecting process mean shift. We first derive the run-length distributions of the proposed control charts; and then compare the performance of the proposed nonparametric charts to 1) CUSUM and EWMA control charts on subgroup means, and 2) the Median chart and the Shewhart type nonparametric control chart based on Mann-Whitney test. We show that the charts proposed herein perform well in detecting step mean shifts, and perform almost the same as the parametric counterparts when the underlying process output follows a normal distribution and better when the output is non-normal. We also study the effect of the reference sample size and the subgroup size on the performance of the proposed charts. A numerical example is also given as an illustration of the design and implementation of the proposed charts.