題 目：Nonparametric CUSUM and EWMA Control Charts for Detecting Mean Shifts
主講人：李蘇一博士 （管理工程系）
時 間：2013年3月18日（星期二） 中午12:00-13:00
地 點：主樓418會議室
主講人簡介：
李蘇一博士，男，2013年11月加入偉德國際1946bv官網(wǎng)管理與經(jīng)濟學院管理工程系。2004年至2011年于新加坡國立大學工業(yè)與系統(tǒng)工程系碩博連讀，并獲得博士學位。1998年至2002年于天津大學偉德國際1946bv官網(wǎng)工業(yè)工程系學習，并獲得學士學位。李博士曾在世界知名電子制造及半導體企業(yè)質(zhì)量部門工作，并獲得六西格瑪黑帶資格，在企業(yè)質(zhì)量管理與六西格瑪培訓方面具有豐富的實踐經(jīng)驗；同時，對風險分析與管理也有所研究。近年來，部分研究成果已發(fā)表于國際知名期刊：Journal of Quality Technology, Risk Analysis, Accident Analysis and Prevention.
內(nèi)容簡介：
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.
