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Robot selection based on grey‐MULTIMOORA approach

Saurav Datta (Department of Mechanical Engineering, National Institute of Technology, Rourkela, India)
Nitin Sahu (Department of Mechanical Engineering, National Institute of Technology, Rourkela, India)
Siba Mahapatra (Department of Mechanical Engineering, National Institute of Technology, Rourkela, India)

Grey Systems: Theory and Application

ISSN: 2043-9377

Article publication date: 23 August 2013

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Abstract

Purpose

The purpose of this paper is to report an efficient decision‐support system for industrial robot selection. It seeks to analyze potential robot selection attributes with a relatively new MCDM approach which employs grey set theory coupled with MULTIMOORA method.

Design/methodology/approach

Use of interval‐valued grey numbers (IVGN) adapted from grey theory has been explored to tackle subjective evaluation information collected from an expert group; finally MULTIMOORA (multi‐objective optimization by ratio analysis) method has been applied in order to aggregate individual criterion/attribute scores into an equivalent evaluation index towards evaluating feasible ranking order of candidate alternative robots.

Findings

An empirical study has also been shown here for better understanding of the said selection‐module; effectively applicable to any other decision‐making scenarios.

Originality/value

This method is computationally very simple, easily comprehensible, and robust which can simultaneously consider numerous subjective attributes. Grey MULTIMOORA ranking is expected to provide a good guidance to the managers of an organization to select the feasible robot. It will also provide a good insight to the robot manufacturer so that it can improve its product or introduce a new product to satisfy customer needs.

Keywords

Citation

Datta, S., Sahu, N. and Mahapatra, S. (2013), "Robot selection based on grey‐MULTIMOORA approach", Grey Systems: Theory and Application, Vol. 3 No. 2, pp. 201-232. https://doi.org/10.1108/GS-05-2013-0008

Publisher

:

Emerald Group Publishing Limited

Copyright © 2013, Emerald Group Publishing Limited

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