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QICID: 19622
Title: Identifying Spatial Variation Patterns in Multivariate Manufacturing Processes: A Blind Separation Approach
Copyright: 2003, ASA/ASQ
Author: Apley, Daniel W.; Lee, Ho Young
Organization: Texas A&M University, College Station, TX
Subject: Factor analysis,Manufacturing,Variation,Analytical modeling,Principal components,Measurement and control,Multivariate quality control;
Series: Technometrics, Vol. 45, No. 3, August 2003, pp. 220-234
Abstract: [This abstract is based on the authors' abstract.] Multivariate measurement data available through automated in-process measurement in manufacturing industries contains valuable information regarding the source of process variation. Assuming that each variation causes a distinct spatial variation pattern in the measurement data, a model is constructed based on the blind source separation problem found in many sensor-array signal processing applications. It is argued that these methods can be used to identify spatial variation patterns in manufacturing data and to diagnose manufacturing variation.
Number of pages: 15
Price for ASQ Members: $5.00
Price for List/Forum/Division: $10.00
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