Cargando…

Hybridized fuzzy analytic hierarchy process and fuzzy weighted average for identifying optimal design concept

In this article, a novel hybridized Multi-Attribute Decision Model (MADM) is developed to identify an optimal design of a Reconfigurable Assembly Fixture (RAF) from a set of alternative design concepts. The model combines the comparative advantage of Fuzzy Analytic Hierarchy Process (FAHP) and the c...

Descripción completa

Detalles Bibliográficos
Autores principales: Olabanji, Olayinka Mohammed, Mpofu, Khumbulani
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6992994/
https://www.ncbi.nlm.nih.gov/pubmed/32021922
http://dx.doi.org/10.1016/j.heliyon.2020.e03182
_version_ 1783492944641130496
author Olabanji, Olayinka Mohammed
Mpofu, Khumbulani
author_facet Olabanji, Olayinka Mohammed
Mpofu, Khumbulani
author_sort Olabanji, Olayinka Mohammed
collection PubMed
description In this article, a novel hybridized Multi-Attribute Decision Model (MADM) is developed to identify an optimal design of a Reconfigurable Assembly Fixture (RAF) from a set of alternative design concepts. The model combines the comparative advantage of Fuzzy Analytic Hierarchy Process (FAHP) and the computational strength of the Fuzzy Weighted Average (FWA) based on left and right scores in order to obtain aggregates for the design alternatives considering the relative importance of the design criteria as needed in the optimal design. The model was applied to evaluate four design concepts of a RAF with six design features having numerous sub-features. Results obtained from the evaluation process shows that there are differences in final values of the design alternatives. However, a close variation exists between these values. These differences can be accrued to the interrelationships between the design features and sub-features obtained from the Fuzzy Synthetic Extent (FSE) of the FAHP and an unambiguity judgment of the FWA when aggregating availability of the design features and sub-features in the design alternatives.
format Online
Article
Text
id pubmed-6992994
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-69929942020-02-04 Hybridized fuzzy analytic hierarchy process and fuzzy weighted average for identifying optimal design concept Olabanji, Olayinka Mohammed Mpofu, Khumbulani Heliyon Article In this article, a novel hybridized Multi-Attribute Decision Model (MADM) is developed to identify an optimal design of a Reconfigurable Assembly Fixture (RAF) from a set of alternative design concepts. The model combines the comparative advantage of Fuzzy Analytic Hierarchy Process (FAHP) and the computational strength of the Fuzzy Weighted Average (FWA) based on left and right scores in order to obtain aggregates for the design alternatives considering the relative importance of the design criteria as needed in the optimal design. The model was applied to evaluate four design concepts of a RAF with six design features having numerous sub-features. Results obtained from the evaluation process shows that there are differences in final values of the design alternatives. However, a close variation exists between these values. These differences can be accrued to the interrelationships between the design features and sub-features obtained from the Fuzzy Synthetic Extent (FSE) of the FAHP and an unambiguity judgment of the FWA when aggregating availability of the design features and sub-features in the design alternatives. Elsevier 2020-01-22 /pmc/articles/PMC6992994/ /pubmed/32021922 http://dx.doi.org/10.1016/j.heliyon.2020.e03182 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Olabanji, Olayinka Mohammed
Mpofu, Khumbulani
Hybridized fuzzy analytic hierarchy process and fuzzy weighted average for identifying optimal design concept
title Hybridized fuzzy analytic hierarchy process and fuzzy weighted average for identifying optimal design concept
title_full Hybridized fuzzy analytic hierarchy process and fuzzy weighted average for identifying optimal design concept
title_fullStr Hybridized fuzzy analytic hierarchy process and fuzzy weighted average for identifying optimal design concept
title_full_unstemmed Hybridized fuzzy analytic hierarchy process and fuzzy weighted average for identifying optimal design concept
title_short Hybridized fuzzy analytic hierarchy process and fuzzy weighted average for identifying optimal design concept
title_sort hybridized fuzzy analytic hierarchy process and fuzzy weighted average for identifying optimal design concept
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6992994/
https://www.ncbi.nlm.nih.gov/pubmed/32021922
http://dx.doi.org/10.1016/j.heliyon.2020.e03182
work_keys_str_mv AT olabanjiolayinkamohammed hybridizedfuzzyanalytichierarchyprocessandfuzzyweightedaverageforidentifyingoptimaldesignconcept
AT mpofukhumbulani hybridizedfuzzyanalytichierarchyprocessandfuzzyweightedaverageforidentifyingoptimaldesignconcept