Abstract
T 2 Hotelling have been used succesfully as a multivariate statistical process control tool for detecting fault in processes with correlated variabels. In the present work, principal component analysis (PCA) is proposed for improvement of monitoring performance, i.e. PCA finds linier combination of variabels that describe major trends in data set, furthermore PCA can be used ro reduced dimensionality. The number of principal component used for contruction is usually smaller than that original variabels. The result show that althought the reability of PCA is the same as T 2 Hotelling methode in many cases or simulation data, but reduction variabels make the process be simple.
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