چکیده مقاله
Statistical process monitoring is an essential need for industrial processes Many of these processes apply principal component analysis to perform statistical process monitoring as its simplicity in computations The PCA is used in this study to reduce dimension for monitoring high dimensional process which has complex computations Fault detection charts that are commonly employed with the PCA method are the Hotelling T2 statistic which are used for monitoring the process which is reduced by PCA This study has two steps; first, the high dimensional process is reduced by applying PCA, and then, the reduced process is monitored
کلیدواژهها
نویسندگان
Zahra Jalilibal
Department of Industrial Engineering, Shahed University Tehran, Iran
Seyed Meysam Mousavi
Department of Industrial Engineering, Shahed University Tehran, Iran
Amirhossein Amiri
Department of Industrial Engineering, Shahed University Tehran, Iran
شیوه ارجاع
Jalilibal, Zahra and Mousavi, Seyed Meysam and Amiri, Amirhossein,1398,High dimensional process monitoring using Principle Component Analysis and T2 chart,5th International Conference on Industrial and Systems Engineering,Mashhad
ارائهشده در
مجموعه مقالات پنجمین کنفرانس بین المللی مهندسی صنایع و سیستمها (ICISE ۲۰۱۹)13 شهریور 1398 · مشهد