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Article

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Title

Fusing Multi-Attribute Decision Models for Decision Making to Achieve Optimal Product Design

Authors

Year of publication

2020

Published in

Foundations of Computing and Decision Sciences

Journal year: 2020 | Journal volume: vol. 45 | Journal number: no. 4

Article type

scientific article

Publication language

english

Keywords
EN
  • hybridized Multi-Attribute Decision-making
  • Fuzzy AHP
  • Fuzzified Pugh Matrix
  • Fuzzy VIKOR
  • optimal conceptual design
Abstract

EN Manufacturers need to select the best design from alternative design concepts in order to meet up with the demand of customers and have a larger share of the competitive market that is flooded with multifarious designs. Evaluation of conceptual design alternatives can be modelled as a Multi-Criteria Decision Making (MCDM) process because it includes conflicting design features with different sub features. Hybridization of Multi Attribute Decision Making (MADM) models has been applied in various field of management, science and engineering in order to have a robust decision-making process but the extension of these hybridized MADM models to decision making in engineering design still requires attention. In this article, an integrated MADM model comprising of Fuzzy Analytic Hierarchy Process (FAHP), Fuzzy Pugh Matrix and Fuzzy VIKOR was developed and applied to evaluate conceptual designs of liquid spraying machine. The fuzzy AHP was used to determine weights of the design features and sub features by virtue of its fuzzified comparison matrix and synthetic extent evaluation. The fuzzy Pugh matrix provides a methodical structure for determining performance using all the design alternatives as basis and obtaining aggregates for the designs using the weights of the sub features. The fuzzy VIKOR generates the decision matrix from the aggregates of the fuzzified Pugh matrices and determine the best design concept from the defuzzified performance index. At the end, the optimal design concept is determined for the liquid spraying machine.

Pages (from - to)

305 - 337

DOI

10.2478/fcds-2020-0016

URL

https://sciendo.com/article/10.2478/fcds-2020-0016

License type

CC BY-NC-ND (attribution - noncommercial - no derivatives)

Full text of article

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public

Ministry points / journal

20

Ministry points / journal in years 2017-2021

40

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