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Neural Computing and Applications
Published in: Neural Computing and Applications 1/2018

05-07-2016 | Original Article

Proposing a graph ranking method for manufacturing system selection in high-tech industries

Authors: Alireza Hakimi-Asl, Mohsen Sadegh Amalnick, Mehdi Hakimi-Asl

Published in: Neural Computing and Applications | Issue 1/2018

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Abstract

All manufacturing centers are looking for the solutions to reduce costs and increase their competitive advantages. One of the practical solutions for cost reduction is to select a suitable manufacturing system in order to optimize usage of limited resources. In high-tech industries, the manufacturing system selection is extremely difficult because of the complex features and structures of their products. Generally, selecting the best manufacturing system of high-tech products is a multiple-criteria decision-making (MCDM) problem. Graph ranking method is one of the most used techniques among MCDM methods, which is originated from combinatorial mathematics. Simple computational procedure, ability to consider relationships between criteria, etc., are some perfect characteristics of this method for modeling and solving decision-making problems with complexity. Therefore, this study attempted to determine the most suitable manufacturing system in high-tech industries using graph ranking method. Moreover, because of vagueness and imprecision in human judgments, fuzzy set theory is utilized in the evaluation procedure. The suggested approach was used to select the most appropriate system for LCD manufacturing at Sanam Electronic Company. Finally, Obtained results indicated the efficiency of the proposed approach and selection of a cloud-based manufacturing system as the most suitable manufacturing system in high-tech industries.
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Footnotes
1
Analytical hierarchy process.
 
2
Preference ranking organization method for enrichment evaluations.
 
3
Technique for order preference by similarity to ideal solution.
 
4
Elimination ET choice translating reality.
 
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Metadata
Title
Proposing a graph ranking method for manufacturing system selection in high-tech industries
Authors
Alireza Hakimi-Asl
Mohsen Sadegh Amalnick
Mehdi Hakimi-Asl
Publication date
05-07-2016
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 1/2018
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-016-2420-7

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