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Application of grey-fuzzy logic technique for parametric optimization of non-traditional machining processes

Application of grey-fuzzy logic technique for parametric optimization of non-traditional... PurposeThe purpose of this paper is to exploit the fullest potential and capability of different non-traditional machining (NTM) processes, it is often recommended to operate them at their optimal parametric combinations. There are several mathematical tools and techniques that have been effectively deployed for identifying the optimal parametric mixes for the NTM processes. Amongst them, grey relational analysis (GRA) has become quite popular due to its sound mathematical basis, ease to implement and apprehensiveness for multi-objective optimization of NTM processes.Design/methodology/approachIn this paper, GRA is integrated with fuzzy logic to present an efficient technique for multi-objective optimization of three NTM processes (i.e. abrasive water-jet machining, electrochemical machining and ultrasonic machining) while identifying their best parametric settings for enhanced machining performance.FindingsThe derived results are validated with respect to technique for order preference by similarity to ideal solution (TOPSIS), and analysis of variance is also performed so as to identify the most significant control parameters in the considered NTM processes.Practical implicationsThis grey-fuzzy logic approach provides better parametric combinations for all the three NTM processes with respect to the predicted grey-fuzzy relational grades (GFRG). The developed surface plots help the process engineers to investigate the effects of various NTM process parameters on the predicted GFRG values.Originality/valueThe adopted approach can be applied to various machining (both conventional and non-conventional) processes for their parametric optimization for achieving better response values. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Grey Systems: Theory and Application Emerald Publishing

Application of grey-fuzzy logic technique for parametric optimization of non-traditional machining processes

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
2043-9377
DOI
10.1108/GS-08-2017-0028
Publisher site
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Abstract

PurposeThe purpose of this paper is to exploit the fullest potential and capability of different non-traditional machining (NTM) processes, it is often recommended to operate them at their optimal parametric combinations. There are several mathematical tools and techniques that have been effectively deployed for identifying the optimal parametric mixes for the NTM processes. Amongst them, grey relational analysis (GRA) has become quite popular due to its sound mathematical basis, ease to implement and apprehensiveness for multi-objective optimization of NTM processes.Design/methodology/approachIn this paper, GRA is integrated with fuzzy logic to present an efficient technique for multi-objective optimization of three NTM processes (i.e. abrasive water-jet machining, electrochemical machining and ultrasonic machining) while identifying their best parametric settings for enhanced machining performance.FindingsThe derived results are validated with respect to technique for order preference by similarity to ideal solution (TOPSIS), and analysis of variance is also performed so as to identify the most significant control parameters in the considered NTM processes.Practical implicationsThis grey-fuzzy logic approach provides better parametric combinations for all the three NTM processes with respect to the predicted grey-fuzzy relational grades (GFRG). The developed surface plots help the process engineers to investigate the effects of various NTM process parameters on the predicted GFRG values.Originality/valueThe adopted approach can be applied to various machining (both conventional and non-conventional) processes for their parametric optimization for achieving better response values.

Journal

Grey Systems: Theory and Application – Emerald Publishing

Published: Feb 5, 2018

References

  • Grey relational analysis based optimization of underwater Nd:YAG laser micro-channeling on PMMA
  • Experimental investigations and multi-response optimisation of wire electric discharge machining of hypereutectic Al-Si alloys
  • Parameter optimization by using grey relational analysis of photochemical machining
  • Multi-objective optimization of electrochemical machining of EN31 steel by grey relational analysis
  • Application of grey fuzzy logic for the optimization of CNC milling parameters for Al-4.5%Cu-TiC MMCs with multi-performance characteristics
  • Introduction to grey system theory
  • Analysis of process parameters in wire EDM with stainless steel using single objective Taguchi method and multi objective grey relational grade