EWMA and industrial applications to feedback adjustment and control
AbstractIn his book 'Out of the Crisis' the late Dr Edwards Deming asserted that 'if anyone adjusts a stable process to try to compensate for a result that is undesirable, or for a result that is extra good, the output will be worse than if he had left the process alone'. His famous funnel experiments supported this assertion. The development of the control chart by Dr Walter Shewhart stemmed from an approach made to him by the management of a Western Electric Company plant because of their awareness that adjustments made to processes often made matters worse. However, many industrial processes are such that the mean values of product quality characteristics shift and drift over time so that, instead of sequences of independent observations to which Deming's assertion applies, process owners are faced with autocorrelated data. The truth of Dr Deming's assertion is demonstrated, both theoretically and via computer simulation. The use of the Exponentially Weighted Moving Average (EWMA) for process monitoring is demonstrated and, for situations where process data exhibit autocorrelation, its use for feedback adjustment is discussed and demonstrated. Finally, successful applications of process improvements using EWMA-based control algorithms is discussed.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Taylor and Francis Journals in its journal Journal of Applied Statistics.
Volume (Year): 28 (2001)
Issue (Month): 3-4 ()
Contact details of provider:
Web page: http://taylorandfrancis.metapress.com/link.asp?target=journal&id=100411
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Petros Maravelakis & John Panaretos & Stelios Psarakis, 2004.
"EWMA Chart and Measurement Error,"
Journal of Applied Statistics,
Taylor and Francis Journals, vol. 31(4), pages 445-455.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
If references are entirely missing, you can add them using this form.