Most industrial systems today are nonlinear and dynamic. Traditional fault detection techniques show their limits because they can hardly extract both dynamic features simultaneously. Canonical variate analysis (CVA) shows its excellent monitoring performance in for processes but is not applicable to processes. Inspired by the CVA method, a novel process namely, “canonical kernel analysis” (CVK...

2 TABLE OF FIGURES 5 INTRODUCTION 6 Problem Statement ...................................................................................................... 6 Deliverables................................................................................................................. 6 Scope ...........................................................................................................

In some statistical process control applications in the real world, quality of a process or a product is characterized by a relationship between two or more variables, which is referred to as profile. Understanding and checking the stability of process over time can be facilitated by monitoring the quality profile in phase I. Sometimes the quality characteristics may be linguistic, imprecise, v...

This paper presents a new nonlinear multivariate statistical process control technique for identifying and isolating the root cause of abnormal process behavior. The new technique is a nonlinear extension to the variables reconstruction technique by (Dunia et al., 1996), based on nonlinear principal component analysis (NLPCA). This work demonstrates that the variable reconstruction (i) affects ...