Please use this identifier to cite or link to this item: https://doi.org/10.1080/00207540600792598
Title: A study of EWMA chart with transformed exponential data
Authors: Liu, J.Y.
Xie, M. 
Goh, T.N. 
Chan, L.Y.
Keywords: Average Run Length
EWMA
Exponential
Time-between-events
Transformation
Weibull
Issue Date: Feb-2007
Source: Liu, J.Y., Xie, M., Goh, T.N., Chan, L.Y. (2007-02). A study of EWMA chart with transformed exponential data. International Journal of Production Research 45 (3) : 743-763. ScholarBank@NUS Repository. https://doi.org/10.1080/00207540600792598
Abstract: The exponentially weighted moving average (EWMA) chart has been shown to be effective in detecting small process shifts and predicting the process level at the next time period. In this paper, a new EWMA chart is proposed to monitor exponentially-distributed time-between-events (TBE) data. The proposed EWMA chart is set up after transforming the TBE data to approximate normal using the double square root (SQRT) transformation. The average run length (ARL) properties of an EWMA chart with transformed exponential data are investigated based on which design procedures are developed. Subsequently, the performance of the EWMA chart with transformed exponential data is compared to that of the X-MR chart, the cumulative quantity control (CQC) chart and the exponential EWMA chart. Furthermore, the robustness of the proposed EWMA chart to Weibull-distributed TBE data is examined, followed by an example to illustrate the design and application procedures. The EWMA chart with transformed exponential data performs well in monitoring exponentially-distributed TBE data.
Source Title: International Journal of Production Research
URI: http://scholarbank.nus.edu.sg/handle/10635/72259
ISSN: 00207543
DOI: 10.1080/00207540600792598
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