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The optimal control limit of a G-EWMAG control chart

Authors
Baik, Jae-WonKang, Hae-WoonKang, Chang-WookSong, Min
Issue Date
Sep-2011
Publisher
Springer Verlag
Keywords
Statistical process control; Average RUN LENGTH; High-quality process; G-EWMAG control chart; G control chart; EWMAG control chart; Geometric distribution
Citation
International Journal of Advanced Manufacturing Technology, v.56, no.1-4, pp.161 - 175
Indexed
SCIE
SCOPUS
Journal Title
International Journal of Advanced Manufacturing Technology
Volume
56
Number
1-4
Start Page
161
End Page
175
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/37210
DOI
10.1007/s00170-011-3179-8
ISSN
0268-3768
Abstract
The control chart is a widely used statistical process control tool that detects any process change and plays an important role in high-quality processes. In this paper, we design G-EWMAG control chart which is sensitive to both small and large shifts. G-EWMAG control chart combines G control chart with EWMAG control chart. The G control chart is based on a plot of the G statistic designed for quality control using attribute data. There is a drawback in G control chart. When it is applied to high-quality processes, it performs poorly in detecting small shifts. On the other hand, EWAMG control chart which apply the EWMA technique with attribute data to G statistics can quickly detect small shifts. G-EWMAG control chart have the alpha ratio which represent the combination ratio of G control chart and G-EWMAG control chart. A large alpha ratio makes the G-EWMAG control chart sensitive to detecting large shifts. On the other hand, a small alpha ratio makes it sensitive to detecting small shifts. But problems arise when the G-EWMAG control chart has an alpha ratio of 1. In this case, a slight numerical difference in average run-length between EWMAG and G-EWMAG appears to exist when detecting small shifts. We suggest optimal control limits for designing the G-EWMAG control chart which is sensitive both large and small shift for use in high-quality processes.
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COLLEGE OF ENGINEERING SCIENCES > DEPARTMENT OF INDUSTRIAL & MANAGEMENT ENGINEERING > 1. Journal Articles

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