Statistical quality control based on control charts and process efficiency index by the application of fuzzy approach (case study: Ha'il, Saudi Arabia)
Fuzzy methods using linguistic expressions and fuzzy numbers can provide a more accurate examination of manufacturing systems where data is not clear. Researchers expanded fuzzy control charts (CCs) using fuzzy linguistic statements and investigated the current process efficiency index to evaluate t...
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| Format: | Article |
| Language: | English |
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IWA Publishing
2023-06-01
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| Series: | Water Science and Technology |
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| Online Access: | http://wst.iwaponline.com/content/87/12/3146 |
| _version_ | 1797745552905994240 |
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| author | Nidhal Ben Khedher Attia Boudjemline Walid Aich Mohamed Ali Zeddini Jorge E. Calderon-Madero |
| author_facet | Nidhal Ben Khedher Attia Boudjemline Walid Aich Mohamed Ali Zeddini Jorge E. Calderon-Madero |
| author_sort | Nidhal Ben Khedher |
| collection | DOAJ |
| description | Fuzzy methods using linguistic expressions and fuzzy numbers can provide a more accurate examination of manufacturing systems where data is not clear. Researchers expanded fuzzy control charts (CCs) using fuzzy linguistic statements and investigated the current process efficiency index to evaluate the performance, precision, and accuracy of the production process in a fuzzy state. Compared to nonfuzzy data mode, fuzzy linguistic statements provided decision makers with more options and a more accurate assessment of the quality of products. The fuzzy index of the actual process efficiency analyzed the process by considering mean, target value, and variance of the process simultaneously. Inspection of household water meters in Ha'il, Saudi Arabia showed the actual process index values were less than 1, indicating unfavorable production conditions. Fuzzy methods enhance the accuracy and effectiveness of statistical quality control in real-world systems where precise information may not be readily available. In addition, to provide a new perspective on the comparison of urban water and sewage systems, the results obtained from fuzzy-CC were compared with various machine learning methods such as artificial neural network and M5 model tree, in order to identify and understand their respective advantages and limitations.
HIGHLIGHTS
This research shows that fuzzy methods, which use appropriate linguistic expressions and fuzzy numbers, can provide a more accurate examination of the state of the production process.;
This article evaluates the performance of the fuzzy-CC, which was developed by benefiting the fuzzy linguistic statements, the current procedure, and the actual process efficiency index (Cpm) in the production process.; |
| first_indexed | 2024-03-12T15:24:56Z |
| format | Article |
| id | doaj.art-a6fdc864866c4b339ad02d53d26358b7 |
| institution | Directory Open Access Journal |
| issn | 0273-1223 1996-9732 |
| language | English |
| last_indexed | 2024-03-12T15:24:56Z |
| publishDate | 2023-06-01 |
| publisher | IWA Publishing |
| record_format | Article |
| series | Water Science and Technology |
| spelling | doaj.art-a6fdc864866c4b339ad02d53d26358b72023-08-10T14:28:48ZengIWA PublishingWater Science and Technology0273-12231996-97322023-06-0187123146316310.2166/wst.2023.181181Statistical quality control based on control charts and process efficiency index by the application of fuzzy approach (case study: Ha'il, Saudi Arabia)Nidhal Ben Khedher0Attia Boudjemline1Walid Aich2Mohamed Ali Zeddini3Jorge E. Calderon-Madero4 Department of Mechanical Engineering, College of Engineering, University of Ha'il, Ha'il 81451, Saudi Arabia Industrial Engineering Department, College of Engineering, University of Ha'il, Ha'il 81451, Saudi Arabia Department of Mechanical Engineering, College of Engineering, University of Ha'il, Ha'il 81451, Saudi Arabia Electrical Engineering Department at Higher Institute of Technological Studies of Ksar Hellal Monastir, University of Monastir, Monastir 5000, Tunisia Department of Civil and Environmental, Universidad de la Costa, Calle 58 # 55-66, Barranquilla, Atlántico, Colombia Fuzzy methods using linguistic expressions and fuzzy numbers can provide a more accurate examination of manufacturing systems where data is not clear. Researchers expanded fuzzy control charts (CCs) using fuzzy linguistic statements and investigated the current process efficiency index to evaluate the performance, precision, and accuracy of the production process in a fuzzy state. Compared to nonfuzzy data mode, fuzzy linguistic statements provided decision makers with more options and a more accurate assessment of the quality of products. The fuzzy index of the actual process efficiency analyzed the process by considering mean, target value, and variance of the process simultaneously. Inspection of household water meters in Ha'il, Saudi Arabia showed the actual process index values were less than 1, indicating unfavorable production conditions. Fuzzy methods enhance the accuracy and effectiveness of statistical quality control in real-world systems where precise information may not be readily available. In addition, to provide a new perspective on the comparison of urban water and sewage systems, the results obtained from fuzzy-CC were compared with various machine learning methods such as artificial neural network and M5 model tree, in order to identify and understand their respective advantages and limitations. HIGHLIGHTS This research shows that fuzzy methods, which use appropriate linguistic expressions and fuzzy numbers, can provide a more accurate examination of the state of the production process.; This article evaluates the performance of the fuzzy-CC, which was developed by benefiting the fuzzy linguistic statements, the current procedure, and the actual process efficiency index (Cpm) in the production process.;http://wst.iwaponline.com/content/87/12/3146actual process efficiencycontrol chartsfuzzy logicquality controlwater meter |
| spellingShingle | Nidhal Ben Khedher Attia Boudjemline Walid Aich Mohamed Ali Zeddini Jorge E. Calderon-Madero Statistical quality control based on control charts and process efficiency index by the application of fuzzy approach (case study: Ha'il, Saudi Arabia) Water Science and Technology actual process efficiency control charts fuzzy logic quality control water meter |
| title | Statistical quality control based on control charts and process efficiency index by the application of fuzzy approach (case study: Ha'il, Saudi Arabia) |
| title_full | Statistical quality control based on control charts and process efficiency index by the application of fuzzy approach (case study: Ha'il, Saudi Arabia) |
| title_fullStr | Statistical quality control based on control charts and process efficiency index by the application of fuzzy approach (case study: Ha'il, Saudi Arabia) |
| title_full_unstemmed | Statistical quality control based on control charts and process efficiency index by the application of fuzzy approach (case study: Ha'il, Saudi Arabia) |
| title_short | Statistical quality control based on control charts and process efficiency index by the application of fuzzy approach (case study: Ha'il, Saudi Arabia) |
| title_sort | statistical quality control based on control charts and process efficiency index by the application of fuzzy approach case study ha il saudi arabia |
| topic | actual process efficiency control charts fuzzy logic quality control water meter |
| url | http://wst.iwaponline.com/content/87/12/3146 |
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