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Proceedings Paper

Statistical control for autocorrelated data
Author(s): Nien-Fan Zhang
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Paper Abstract

Recently, statistical process control methodologies have been developed to accommodate autocorrelated data. A primary method to deal with autocorrelated data is the use of residual charts. Although this methodology has the advantage that it can be applied to any autocorrelated data, it needs modeling effort in practice. In addition, the detection capabilities of the residual chart is not always great. Zhang proposed the EWMAST chart, which is constructed by charting the EWMA statistic for stationary processes to monitor the process mean. The performance among the EWMAST chart, the X chart, the residual X chart and other charts were compared in Zhang. In this article, I will compare the EWMAST chart with the residual CUSUM chart and residual EWMA chart as well as the residual X chart and X chart via the average run length.

Paper Details

Date Published: 23 April 1999
PDF: 6 pages
Proc. SPIE 3742, Process and Equipment Control in Microelectronic Manufacturing, (23 April 1999); doi: 10.1117/12.346251
Show Author Affiliations
Nien-Fan Zhang, National Institute of Standards and Technology (United States)


Published in SPIE Proceedings Vol. 3742:
Process and Equipment Control in Microelectronic Manufacturing
Kevin Yallup; Murali K. Narasimhan, Editor(s)

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