A FBWM-PROMETHEE approach for industrial robot selection

In recent years, the selection of a robot for particular industrial purposes is one of the most challenging problems in the manufacturing environment based on automation and smartness for real-time decision-making. At present, several types of industrial robots with various capabilities, features, f...

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Main Authors: Mahdi Nasrollahi, Javaneh Ramezani, Mahmoud Sadraei
Format: Article
Language:English
Published: Elsevier 2020-05-01
Series:Heliyon
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844020307040
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spelling doaj-c692ea28712d48b39045c5084ee63eb82020-11-25T03:00:34ZengElsevierHeliyon2405-84402020-05-0165e03859A FBWM-PROMETHEE approach for industrial robot selectionMahdi Nasrollahi0Javaneh Ramezani1Mahmoud Sadraei2Imam Khomeini International University (IKIU), Faculty of Social Sciences, Qazvin, Iran; Corresponding author.NOVA University of Lisbon, Faculty of Sciences and Technology and UNINOVA-CTS, Campus da Caparica, 2829-516, Monte Caparica, PortugalBusiness Consultant, Sydney, AustraliaIn recent years, the selection of a robot for particular industrial purposes is one of the most challenging problems in the manufacturing environment based on automation and smartness for real-time decision-making. At present, several types of industrial robots with various capabilities, features, facilities, and specifications are available in the market. This makes the decision-making process more and more complicated due to the increase in complexity, advanced technologies, and features that are continually being incorporated into the robots by several manufacturers. The decision-maker needs to identify and select the best-suited robot to attain the desired output with precise application ability, and minimum cost. This paper tries to solve the robot selection problem using Fuzzy Best-Worst Method and PROMETHEE as the two most appropriate multi-criteria decision-making (MCDM) methods for weighting criteria and ranking of decision alternatives, respectively.http://www.sciencedirect.com/science/article/pii/S2405844020307040Industrial engineeringMultidisciplinary design optimizationManufacturing engineeringTechnology managementOperations managementIndustry management
collection DOAJ
language English
format Article
sources DOAJ
author Mahdi Nasrollahi
Javaneh Ramezani
Mahmoud Sadraei
spellingShingle Mahdi Nasrollahi
Javaneh Ramezani
Mahmoud Sadraei
A FBWM-PROMETHEE approach for industrial robot selection
Heliyon
Industrial engineering
Multidisciplinary design optimization
Manufacturing engineering
Technology management
Operations management
Industry management
author_facet Mahdi Nasrollahi
Javaneh Ramezani
Mahmoud Sadraei
author_sort Mahdi Nasrollahi
title A FBWM-PROMETHEE approach for industrial robot selection
title_short A FBWM-PROMETHEE approach for industrial robot selection
title_full A FBWM-PROMETHEE approach for industrial robot selection
title_fullStr A FBWM-PROMETHEE approach for industrial robot selection
title_full_unstemmed A FBWM-PROMETHEE approach for industrial robot selection
title_sort fbwm-promethee approach for industrial robot selection
publisher Elsevier
series Heliyon
issn 2405-8440
publishDate 2020-05-01
description In recent years, the selection of a robot for particular industrial purposes is one of the most challenging problems in the manufacturing environment based on automation and smartness for real-time decision-making. At present, several types of industrial robots with various capabilities, features, facilities, and specifications are available in the market. This makes the decision-making process more and more complicated due to the increase in complexity, advanced technologies, and features that are continually being incorporated into the robots by several manufacturers. The decision-maker needs to identify and select the best-suited robot to attain the desired output with precise application ability, and minimum cost. This paper tries to solve the robot selection problem using Fuzzy Best-Worst Method and PROMETHEE as the two most appropriate multi-criteria decision-making (MCDM) methods for weighting criteria and ranking of decision alternatives, respectively.
topic Industrial engineering
Multidisciplinary design optimization
Manufacturing engineering
Technology management
Operations management
Industry management
url http://www.sciencedirect.com/science/article/pii/S2405844020307040
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