A review on fuzzy control charts for monitoring attribute data
Up to now, several methods have been proposed for monitoring processes with attribute data. These methods can be categorized into two major group; statistical methods and fuzzy methods. In this paper current fuzzy methods are introduced and the performance of fuzzy methods and statistical methods ar...
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2012
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my.upm.eprints.513362017-07-04T03:56:37Z http://psasir.upm.edu.my/id/eprint/51336/ A review on fuzzy control charts for monitoring attribute data Jahromi, Seyed Mojtaba Zabihinpour Saghaei, Abbas Mohd Ariffin, Mohd Khairol Anuar Up to now, several methods have been proposed for monitoring processes with attribute data. These methods can be categorized into two major group; statistical methods and fuzzy methods. In this paper current fuzzy methods are introduced and the performance of fuzzy methods and statistical methods are compared together based on the Average Run Length (ARL). The comparison shows that the statistical method has the best performance. We show the necessity of using fuzzy method in case of attribute data. Then the critiques towards fuzzy methods are reviewed which show the usage of fuzzy set theory in these methods have some restriction. As a result we indicate a study gap about the usage of fuzzy set theory for monitoring processes with attribute data and at the end some guideline for the next study are proposed. Trans Tech Publications 2012 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/51336/1/A%20review%20on%20fuzzy%20control%20charts%20for%20monitoring%20attribute%20data.pdf Jahromi, Seyed Mojtaba Zabihinpour and Saghaei, Abbas and Mohd Ariffin, Mohd Khairol Anuar (2012) A review on fuzzy control charts for monitoring attribute data. Applied Mechanics and Materials, 159. pp. 23-28. ISSN 1660-9336; ESSN: 1662-7482 https://www.scientific.net/AMM.159.23 10.4028/www.scientific.net/AMM.159.23 |
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Up to now, several methods have been proposed for monitoring processes with attribute data. These methods can be categorized into two major group; statistical methods and fuzzy methods. In this paper current fuzzy methods are introduced and the performance of fuzzy methods and statistical methods are compared together based on the Average Run Length (ARL). The comparison shows that the statistical method has the best performance. We show the necessity of using fuzzy method in case of attribute data. Then the critiques towards fuzzy methods are reviewed which show the usage of fuzzy set theory in these methods have some restriction. As a result we indicate a study gap about the usage of fuzzy set theory for monitoring processes with attribute data and at the end some guideline for the next study are proposed. |
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Article |
author |
Jahromi, Seyed Mojtaba Zabihinpour Saghaei, Abbas Mohd Ariffin, Mohd Khairol Anuar |
spellingShingle |
Jahromi, Seyed Mojtaba Zabihinpour Saghaei, Abbas Mohd Ariffin, Mohd Khairol Anuar A review on fuzzy control charts for monitoring attribute data |
author_facet |
Jahromi, Seyed Mojtaba Zabihinpour Saghaei, Abbas Mohd Ariffin, Mohd Khairol Anuar |
author_sort |
Jahromi, Seyed Mojtaba Zabihinpour |
title |
A review on fuzzy control charts for monitoring attribute data |
title_short |
A review on fuzzy control charts for monitoring attribute data |
title_full |
A review on fuzzy control charts for monitoring attribute data |
title_fullStr |
A review on fuzzy control charts for monitoring attribute data |
title_full_unstemmed |
A review on fuzzy control charts for monitoring attribute data |
title_sort |
review on fuzzy control charts for monitoring attribute data |
publisher |
Trans Tech Publications |
publishDate |
2012 |
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http://psasir.upm.edu.my/id/eprint/51336/1/A%20review%20on%20fuzzy%20control%20charts%20for%20monitoring%20attribute%20data.pdf http://psasir.upm.edu.my/id/eprint/51336/ https://www.scientific.net/AMM.159.23 |
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