Multi-response Optimization of Hybrid Machining Processes Using Evaluation Based on Distance from Average Solution Metho
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ORIGINAL RESEARCH PAPER
Multi-response Optimization of Hybrid Machining Processes Using Evaluation Based on Distance from Average Solution Method in Intuitionistic Fuzzy Environment Partha Protim Das 1 & Shankar Chakraborty 2 Received: 17 June 2020 / Revised: 9 August 2020 / Accepted: 27 August 2020 # Springer Nature Singapore Pte Ltd. 2020
Abstract Hybrid non-traditional machining processes have established their dominance over the naive machining processes because of their ability to have better machining performance as compared with the individual constituent processes. However, efficiency of any machining process is supposed to be affected by the poor machining environment resulting in uncertain and vague performance measures. Hence, this paper contributes in finding out the optimal parametric mixes of two hybrid non-traditional machining processes, i.e. laser-assisted jet electrochemical machining and electrochemical discharge drilling processes using evaluation based on distance from average solution method while removing uncertainty and vagueness in the dataset under intuitionistic fuzzy environment. The derived optimal parametric mixes are then validated with the help of developed regression equations which indicate superiority of the adopted technique over the other popular optimization approaches. Analysis of variance results further help in singling out the most influential input parameters for the considered hybrid non-traditional machining processes. Finally, the corresponding surface plots are developed to assist the process engineers in selecting the most appropriate combination of process parameters for achieving the desired response values. Keywords Hybrid NTM process . EDAS method . Intuitionistic fuzzy sets . Optimization . LA-JECM . ECDD . Response
Abbreviations NTM Non-traditional machining LBM Laser beam machining ECM Electrochemical machining EDM Electrical discharge machining AJM Abrasive jet machining WJM Water jet machining ECDM Electrochemical discharge machining LA-JECM Laser-assisted jet electrochemical machining AWJM Abrasive water jet machining T W Travelling wire electrochemical spark ECSM machining
* Shankar Chakraborty [email protected] 1
Department of Mechanical Engineering, Sikkim Manipal Institute of Technology, Sikkim Manipal University, Majitar, Sikkim, India
2
Department of Production Engineering, Jadavpur University, Kolkata, West Bengal, India
WEDM GRA TOPSIS PCA IFS EDAS MCDM PDA NDA VIKOR ECDD RSM MRR ROC HAZ SR KW GA
Wire electrical discharge machining Grey relational analysis Technique for order of preference by similarity to ideal solution Principal component analysis Intuitionistic fuzzy sets Evaluation based on distance from average solution Multi-criteria decision-making Positive distance from average Negative distance from average VIseKriterijumska Optimizacija I Kompromisno Resenje Electrochemical discharge drilling Response surface methodology Material removal rate Radial overcut Heat-affected zone Surface roughness Kerf width Genetic algorithm
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