Construction of fuzzy X-S control charts with an unbiased estimation of standard deviation for a triangular fuzzy random variable
Statistical process control and Shewhart control charts are used by organizations to aid in process understanding, assessing process stability, and identifying changes to improve the quality of the product. Shewhart control charts only considered uncertainty caused by randomness while in practice,...
| Huvudupphovsmän: | , , , |
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| Materialtyp: | Artikel |
| Språk: | English |
| Publicerad: |
IOS Press
2015
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| Länkar: | http://psasir.upm.edu.my/id/eprint/44175/1/FUZZY.pdf |
| _version_ | 1825929500065529856 |
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| author | Mohd Ariffin, Mohd Khairol Anuar Ahmad, Siti Azfanizam Tang, Sai Hong S., Mojtaba Zabihinpour |
| author_facet | Mohd Ariffin, Mohd Khairol Anuar Ahmad, Siti Azfanizam Tang, Sai Hong S., Mojtaba Zabihinpour |
| author_sort | Mohd Ariffin, Mohd Khairol Anuar |
| collection | UPM |
| description | Statistical process control and Shewhart control charts are used by organizations to aid in process understanding,
assessing process stability, and identifying changes to improve the quality of the product. Shewhart control charts only considered uncertainty caused by randomness while in practice, uncertainty caused by vagueness, ambiguity, and/or incomplete information are also observed. In this article, fuzzy X¯ − S control charts which handle both kinds of uncertainty simultaneously are developed using fuzzy random variables. For this purpose, the unbiased estimation of standard deviation for a triangular fuzzy random variable is introduced and utilized to construct the fuzzy X¯ − S control charts. Then, a detailed average run length study is performed to evaluate the decisions regarding sample size and accepted out-of-control level (�). A comparison study is performed to verify the proposed technique by comparing its performance based on average run length with previous technique in the literature. The result shows that the proposed technique could improve the detection of abnormal shift in process mean 0.1% to 30% depending on sample size and shift. Finally, the proposed fuzzy control charts are validated through a case study of noodle production in food industry. |
| first_indexed | 2024-03-06T08:57:39Z |
| format | Article |
| id | upm.eprints-44175 |
| institution | Universiti Putra Malaysia |
| language | English |
| last_indexed | 2024-03-06T08:57:39Z |
| publishDate | 2015 |
| publisher | IOS Press |
| record_format | dspace |
| spelling | upm.eprints-441752021-01-23T21:16:49Z http://psasir.upm.edu.my/id/eprint/44175/ Construction of fuzzy X-S control charts with an unbiased estimation of standard deviation for a triangular fuzzy random variable Mohd Ariffin, Mohd Khairol Anuar Ahmad, Siti Azfanizam Tang, Sai Hong S., Mojtaba Zabihinpour Statistical process control and Shewhart control charts are used by organizations to aid in process understanding, assessing process stability, and identifying changes to improve the quality of the product. Shewhart control charts only considered uncertainty caused by randomness while in practice, uncertainty caused by vagueness, ambiguity, and/or incomplete information are also observed. In this article, fuzzy X¯ − S control charts which handle both kinds of uncertainty simultaneously are developed using fuzzy random variables. For this purpose, the unbiased estimation of standard deviation for a triangular fuzzy random variable is introduced and utilized to construct the fuzzy X¯ − S control charts. Then, a detailed average run length study is performed to evaluate the decisions regarding sample size and accepted out-of-control level (�). A comparison study is performed to verify the proposed technique by comparing its performance based on average run length with previous technique in the literature. The result shows that the proposed technique could improve the detection of abnormal shift in process mean 0.1% to 30% depending on sample size and shift. Finally, the proposed fuzzy control charts are validated through a case study of noodle production in food industry. IOS Press 2015 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/44175/1/FUZZY.pdf Mohd Ariffin, Mohd Khairol Anuar and Ahmad, Siti Azfanizam and Tang, Sai Hong and S., Mojtaba Zabihinpour (2015) Construction of fuzzy X-S control charts with an unbiased estimation of standard deviation for a triangular fuzzy random variable. Journal of Intelligent and Fuzzy Systems, 28. pp. 2735-2747. ISSN 1875-8967; ESSN: 1064-1246 https://www.researchgate.net/publication/282885611 10.3233/IFS-151551 |
| spellingShingle | Mohd Ariffin, Mohd Khairol Anuar Ahmad, Siti Azfanizam Tang, Sai Hong S., Mojtaba Zabihinpour Construction of fuzzy X-S control charts with an unbiased estimation of standard deviation for a triangular fuzzy random variable |
| title | Construction of fuzzy X-S control charts with an unbiased estimation of standard deviation for a triangular fuzzy random variable |
| title_full | Construction of fuzzy X-S control charts with an unbiased estimation of standard deviation for a triangular fuzzy random variable |
| title_fullStr | Construction of fuzzy X-S control charts with an unbiased estimation of standard deviation for a triangular fuzzy random variable |
| title_full_unstemmed | Construction of fuzzy X-S control charts with an unbiased estimation of standard deviation for a triangular fuzzy random variable |
| title_short | Construction of fuzzy X-S control charts with an unbiased estimation of standard deviation for a triangular fuzzy random variable |
| title_sort | construction of fuzzy x s control charts with an unbiased estimation of standard deviation for a triangular fuzzy random variable |
| url | http://psasir.upm.edu.my/id/eprint/44175/1/FUZZY.pdf |
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