Open Science Research Excellence
%0 Journal Article
%A Tai-Yue Wang and  Hui-Min Chiang and  Su-Ni Hsieh and  Yu-Min Chiang
%D 2013 
%J  International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering
%B World Academy of Science, Engineering and Technology
%I International Science Index 78, 2013
%T Support Vector Machines Approach for Detecting the Mean Shifts in Hotelling-s T2 Control Chart with Sensitizing Rules
%U http://waset.org/publications/5065
%V 78
%X In many industries, control charts is one of the most
frequently used tools for quality management. Hotelling-s T2 is used
widely in multivariate control chart. However, it has little defect when
detecting small or medium process shifts. The use of supplementary
sensitizing rules can improve the performance of detection. This study
applied sensitizing rules for Hotelling-s T2 control chart to improve the
performance of detection. Support vector machines (SVM) classifier
to identify the characteristic or group of characteristics that are
responsible for the signal and to classify the magnitude of the mean
shifts. The experimental results demonstrate that the support vector
machines (SVM) classifier can effectively identify the characteristic
or group of characteristics that caused the process mean shifts and the
magnitude of the shifts.
%P 1261 - 1265