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Fault detection based on statistical multivariate analysis and microarray visualization
Journal article

Fault detection based on statistical multivariate analysis and microarray visualization

Ming-Da Ma, David Shan-Hill Wong, Shi-Shang Jang and Sheng-Tsaing Tseng
IEEE Transactions on Industrial Informatics, Vol.6(1), pp.18-24
02/2010

Abstract

Fault detection Microarray Quality improvement Semiconductor manufacturing Wilcoxon rank-sum test
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. © 2009 IEEE.

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