NDLI: Statistical process monitoring of between-part and within-part variations using independent component analysis

Content Provider	IEEE Xplore Digital Library
Author	Cheng, C.S. Cheng, H.P. Huang, K.K.
Copyright Year	2010
Description	Author affiliation: Department of Industrial Engineering and Management, Yuan-Ze University, Nei-Li, Taiwan, R.O.C. (Cheng, C.S.; Huang, K.K.) \|\| Department of Business Innovation and Development, Ming-Dao University, Peetow, Taiwan, R.O.C. (Cheng, H.P.)
Abstract	The data collected from in-process measurement usually contain useful information about the nature of the source of process variability. In this paper, each variation source is assumed to generate a different spatial variation pattern in the quality characteristics measurements. The variation source might also reveal interesting temporal pattern over the data sample. The spatial variation pattern and temporal pattern caused by a variation source may turn out to be the observed within- and between-part variations in the monitoring of product measurements. The study reported in this paper aimed at applying independent component analysis (ICA) to monitor within- and between-part variations. Various monitoring statistics obtained from ICA are used to construct the control procedure. The average run length (ARL) is used to measure the abnormalities detection performance. An extensive comparison based on simulation study indicates that the ICA-based control charts perform better than conventional control charts in terms of ARL. The paper contributes to the monitoring of within- and between-part variations.
Starting Page	111
Ending Page	115
File Size	457293
Page Count	5
File Format	PDF
ISBN	9781424464838
e-ISBN	9781424464845
DOI	10.1109/ICIEEM.2010.5646625
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-29
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Within and between variations ICA Monitoring
Content Type	Text
Resource Type	Article

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