Intuitionistic fuzzy-based model for failure detection
In identifying to-be-improved product component(s), the customer/user requirements which are mainly considered, and achieved through customer surveys using the quality function deployment (QFD) tool, often fail to guarantee or cover aspects of the product reliability. Even when they do, there are al...
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| Format: | Online |
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Springer International Publishing
2016
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5101249/ |
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pubmed-5101249 |
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pubmed-51012492016-12-08 Intuitionistic fuzzy-based model for failure detection Aikhuele, Daniel O. Turan, Faiz B. M. Research In identifying to-be-improved product component(s), the customer/user requirements which are mainly considered, and achieved through customer surveys using the quality function deployment (QFD) tool, often fail to guarantee or cover aspects of the product reliability. Even when they do, there are always many misunderstandings. To improve the product reliability and quality during product redesigning phase and to create that novel product(s) for the customers, the failure information of the existing product, and its component(s) should ordinarily be analyzed and converted to appropriate design knowledge for the design engineer. In this paper, a new intuitionistic fuzzy multi-criteria decision-making method has been proposed. The new approach which is based on an intuitionistic fuzzy TOPSIS model uses an exponential-related function for the computation of the separation measures from the intuitionistic fuzzy positive ideal solution (IFPIS) and intuitionistic fuzzy negative ideal solution (IFNIS) of alternatives. The proposed method has been applied to two practical case studies, and the result from the different cases has been compared with some similar computational approaches in the literature. Springer International Publishing 2016-11-09 /pmc/articles/PMC5101249/ /pubmed/27933231 http://dx.doi.org/10.1186/s40064-016-3446-0 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
| repository_type |
Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
Aikhuele, Daniel O. Turan, Faiz B. M. |
| spellingShingle |
Aikhuele, Daniel O. Turan, Faiz B. M. Intuitionistic fuzzy-based model for failure detection |
| author_facet |
Aikhuele, Daniel O. Turan, Faiz B. M. |
| author_sort |
Aikhuele, Daniel O. |
| title |
Intuitionistic fuzzy-based model for failure detection |
| title_short |
Intuitionistic fuzzy-based model for failure detection |
| title_full |
Intuitionistic fuzzy-based model for failure detection |
| title_fullStr |
Intuitionistic fuzzy-based model for failure detection |
| title_full_unstemmed |
Intuitionistic fuzzy-based model for failure detection |
| title_sort |
intuitionistic fuzzy-based model for failure detection |
| description |
In identifying to-be-improved product component(s), the customer/user requirements which are mainly considered, and achieved through customer surveys using the quality function deployment (QFD) tool, often fail to guarantee or cover aspects of the product reliability. Even when they do, there are always many misunderstandings. To improve the product reliability and quality during product redesigning phase and to create that novel product(s) for the customers, the failure information of the existing product, and its component(s) should ordinarily be analyzed and converted to appropriate design knowledge for the design engineer. In this paper, a new intuitionistic fuzzy multi-criteria decision-making method has been proposed. The new approach which is based on an intuitionistic fuzzy TOPSIS model uses an exponential-related function for the computation of the separation measures from the intuitionistic fuzzy positive ideal solution (IFPIS) and intuitionistic fuzzy negative ideal solution (IFNIS) of alternatives. The proposed method has been applied to two practical case studies, and the result from the different cases has been compared with some similar computational approaches in the literature. |
| publisher |
Springer International Publishing |
| publishDate |
2016 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5101249/ |
| _version_ |
1613718852210786304 |