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Keywords = fuzzy EWMA charts

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13 pages, 499 KiB  
Article
A Fuzzy EWMA Attribute Control Chart to Monitor Process Mean
by Muhammad Zahir Khan, Muhammad Farid Khan, Muhammad Aslam, Seyed Taghi Akhavan Niaki and Abdur Razzaque Mughal
Information 2018, 9(12), 312; https://doi.org/10.3390/info9120312 - 7 Dec 2018
Cited by 20 | Viewed by 3798
Abstract
Conventional control charts are one of the most important techniques in statistical process control which are used to assess the performance of processes to see whether they are in- or out-of-control. As traditional control charts deal with crisp data, they are not suitable [...] Read more.
Conventional control charts are one of the most important techniques in statistical process control which are used to assess the performance of processes to see whether they are in- or out-of-control. As traditional control charts deal with crisp data, they are not suitable to study unclear, vague, and fuzzy data. In many real-world applications, however, the data to be used in a control charting method are not crisp since they are approximated due to environmental uncertainties and systematic ambiguities involved in the systems under investigation. In these situations, fuzzy numbers and linguistic variables are used to grab such uncertainties. That is why the use of a fuzzy control chart, in which fuzzy data are used, is justified. As an exponentially weighted moving average (EWMA) scheme is usually used to detect small shifts, in this paper a fuzzy EWMA (F-EWMA) control chart is proposed to detect small shifts in the process mean when fuzzy data are available. The application of the newly developed fuzzy control chart is illustrated using real-life data. Full article
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<p>Triangular Fuzzy Number.</p>
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