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Fault Detection Based on Statistical Multivariate Analysis and Microarray Visualization

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4 Author(s)
Ming-Da Ma ; Center for Control & Guidance Technol., Harbin Inst. of Technol., Harbin, China ; Wong, D.S.-H. ; Shi-Shang Jang ; Sheng-Tsaing Tseng

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.

Published in:

Industrial Informatics, IEEE Transactions on  (Volume:6 ,  Issue: 1 )