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Selection of industrial robots using compromise ranking method
Author(s) -
Vijay Manikrao Athawale,
Prasenjit Chatterjee,
Shankar Chakraborty
Publication year - 2012
Publication title -
international journal of industrial and systems engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.273
H-Index - 27
eISSN - 1748-5045
pISSN - 1748-5037
DOI - 10.1504/ijise.2012.046651
Subject(s) - robot , simplicity , vikor method , selection (genetic algorithm) , compromise , ranking (information retrieval) , task (project management) , computer science , multiple criteria decision analysis , industrial robot , rank (graph theory) , artificial intelligence , risk analysis (engineering) , operations research , engineering , systems engineering , mathematics , business , social science , philosophy , epistemology , combinatorics , sociology
Many advanced manufacturers are now extensively using robots to perform repetitious, difficult and hazardous tasks with precision. Selection of industrial robots to suit a particular application and production environment from among a large number of alternatives available in the market is a difficult task in real-time manufacturing environment. This has become more and more complicated due to increase complexity, advanced features and facilities that are continuously being incorporated into the robots by different vendors. The decision maker needs to select the most appropriate industrial robot to achieve the desired performance with minimum cost and specific application ability. This paper mainly focuses on solving the industrial robot selection problems using VIse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) method, which has already become a quite popular multi-criteria decision-making (MCDM) tool. It evaluates and ranks the alternative candidate robots, while proposing a compromise solution to the robot selection problem. Two real-time examples are illustrated to demonstrate and validate the effectiveness and applicability of VIKOR method, which also prove the computational simplicity of this method.

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