Fault Detection Based on Statistical Multivariate Analysis and Microarray Visualization

In this work, a statistical method is proposed to mine out key variables from a large set of variables recorded in a limited number of runs through a multistage multistep manufacturing process. The method employed well-known single variable or multivariable techniques of discrimination and regression but also presented a synopsis of analysis results in a colored map of p-values very similar to a DNA microarray. This framework provides a systematic method of drawing inferences from the available evidence without interrupting the normal process operation. The proposed concept is illustrated by two industrial examples.