1. On t and EWMA t Charts for Monitoring Changes in the Process Mean
- Author
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Gemai Chen, Lingyun Zhang, Philippe Castagliola, Institut de Recherche en Communications et en Cybernétique de Nantes (IRCCyN), Mines Nantes (Mines Nantes)-École Centrale de Nantes (ECN)-Ecole Polytechnique de l'Université de Nantes (EPUN), and Université de Nantes (UN)-Université de Nantes (UN)-PRES Université Nantes Angers Le Mans (UNAM)-Centre National de la Recherche Scientifique (CNRS)
- Subjects
Engineering ,021103 operations research ,business.industry ,X-bar chart ,0211 other engineering and technologies ,02 engineering and technology ,Management Science and Operations Research ,01 natural sciences ,\bar x and s chart ,Standard deviation ,010104 statistics & probability ,Chart ,Control limits ,Statistics ,EWMA chart ,0101 mathematics ,Safety, Risk, Reliability and Quality ,Shewhart individuals control chart ,business ,\bar x and R chart ,ComputingMilieux_MISCELLANEOUS - Abstract
The performance of an X-bar chart is usually studied under the assumption that the process standard deviation is well estimated and does not change. This is, of course, not always the case in practice. We find that X-bar charts are not robust against errors in estimating the process standard deviation or changing standard deviation. In this paper we discuss the use of a t chart and an exponentially weighted moving average (EWMA) t chart to monitor the process mean. We determine the optimal control limits for the EWMA t chart and show that this chart has the desired robustness property. Copyright © 2009 John Wiley & Sons, Ltd.
- Published
- 2009