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Multi-objective optimization and characterization of cylindricity and material removal rate in nanographene mixed dielectric EDM using ANFIS and MOSOA

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Abstract

The current study performed modeling, analysis, and optimization of electrical discharge machining (EDM) under nano graphene mixed dielectric machining of Inconel 718 using ANFIS and a newly developed multi-objective seagull optimization algorithm. The influence of three major EDM controlling parameters namely peak current (Ip), pulse on time (Ton), and pulse off time (Toff) have been studied on the output machining characteristics viz. material removal rate (MRR) and cylindricity (CY) deviation for each of the experiments. In this work, EDM performance was enhanced by dispersing nano-graphene powder into EDM Oil as a dielectric medium and improvement from conventional EDM was analysed. The Taguchi L27 orthogonal array was utilized for planning and conducting EDM experiments, while analysis of variance (ANOVA) tests and regression analysis were conducted for examining the influence of input process variables on machining response variables. From results, it was realized that nano graphene mixed dielectric EDM improved the machining performance in comparison to traditional EDM performance. The modeling of response variables in terms of input process variables and optimal process conditions were determined using efficient intelligent methods namely ANFIS model and the newly developed multi-objective seagull optimization algorithm (MOSOA), respectively. It was found that nanographene mixed EDM improved MRR and cylindricity deviation by 13.88% and 25.76% respectively in comparison to conventional EDM without nanographene mixed dielectric. The MOSOA algorithm provides a number of non-dominated pareto solutions and best machining conditions among 32 optimal sets for nanographene mixed EDM was selected as a pulse on time of 12 µs, pulse off time as 7 µs, and peak current at 9 A. Finally, the scanning electron microscopy image also shows the improvement in surface finish of nano graphene mixed dielectric EDM in comparison to traditional EDM.

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Abbreviations

EDM:

Electrical discharge machining

Ip:

Peak current

Ton:

Pulse on time

Toff:

Pulse off time

MRR:

Material removal rate

CL:

Cylindricity

FESEM:

Field emission scanning electron microscope

CMM:

Coordinate measuring machine

ANOVA:

Analysis of variance

S/N Ratio:

Signal to noise ratio

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Acknowledgements

The authors would like to express their sincere gratitude towards the School of Automobile, Mechanical and Mechatronics (SAMM) Engineering, Manipal University Jaipur for extending their support by providing machining and results testing equipment to carry out this research successfully. Furthermore, we would like to acknowledge BSDU Jaipur for providing Coordinate Measuring Machine (CMM) to analyse the form tolerance i.e., Cylindricity.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Manipal University Jaipur, Jaipur, Rajasthan, India

    Ashish Goyal, Deepesh Sharma, Arnab Bhowmick & Vimal Kumar Pathak

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  1. Ashish Goyal
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Correspondence to Vimal Kumar Pathak.

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Goyal, A., Sharma, D., Bhowmick, A. et al. Multi-objective optimization and characterization of cylindricity and material removal rate in nanographene mixed dielectric EDM using ANFIS and MOSOA. Sādhanā 47, 139 (2022). https://doi.org/10.1007/s12046-022-01914-2

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