Application of response surface methodology and genetic algorithm for optimisation of electro-discharge diamond face grinding of tungsten carbide-cobalt composite

Yadav, Ravindra Nath; Yadava, Vinod; Singh, Gyanendra Kumar

doi:10.1504/ijise.2014.064342

Cited by 3 publications

(2 citation statements)

References 26 publications

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“…The suitability for selection of appropriate optimal solution from Pareto optimal set was appreciated. 25,26 ANN model of MRR and R a was developed for EDDFG of HSS. The effects of gap current, on-time, duty factor and RPM of wheel on MRR and R a were studied using the predicted results from developed ANN model.…”

Section: Introductionmentioning

confidence: 99%

Hybrid design-based modelling and multi-objective optimization of hybrid machining of hybrid metal matrix composites

Yadav

Yadava

2018

Proceedings of the Institution of Mechanical Engineers, Part C:

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Electrical discharge diamond face surface grinding (EDDFSG) is a hybrid machining technique consisting of face surface electrical discharge grinding and diamond face surface grinding. The machining of hybrid metal matrix composites (HMMCs) is still facing challenges for better machining performance. In the present article, an effort was made for hybrid design-based experimental modelling, performance prediction and multi-objective optimization of EDDFSG of Al/Al2O3p/B4Cp and Al/SiCp/B4Cp HMMCs. Gap current, on-time, off-time, abrasive grit number, revolutions per minute (RPM) of wheel and table speed are the process parameters whose effects on material removal rate and surface roughness ( Ra) were analysed. The machining characteristics of HMMCs were investigated using performance predictions. Binary coded modified distance-based Pareto genetic algorithm was integrated with hybrid design-based RSM models for multi-objective optimization of EDDFSG process. The surface texture and re-solidified layers were also analysed using scanning electron microscopy. The selected optimized results were found to have better material removal rate and surface finish along with negligible presence of re-solidified layers during verification experiments.

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Section: Introductionmentioning

confidence: 99%

Hybrid design-based modelling and multi-objective optimization of hybrid machining of hybrid metal matrix composites

Yadav

Yadava

2018

Proceedings of the Institution of Mechanical Engineers, Part C:

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“…The NSGA-II technique needs a mathematical equation or model to calculate the objective functions. Several researchers (Mandal et al 2007;Jain et al, 2007;Kanagarajan et al, 2008;Yadav et al, 2012) combined ANN model with NSGA-II to optimize the process parameters of different manufacturing processes. Thus, in the present study a combined approach of ANN-NSGA-II has been applied for optimization of process parameters of the S-EDAG process.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Methodology of ANN-NSGA-II for Optimization of the Process Parameters of Slotted-Electrical Discharge Abrasive Grinding Process

Yadav

Yadava

2014

International Journal of Materials Forming and Machining Processes

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Slotted-Electrical Discharge Abrasive Grinding (S-EDAG) is a new innovative hybrid machining process, which is developed by comprising the Electrical Discharge Grinding (EDG) and Abrasive Grinding (AG) where both the processes occur alternatively. The selection of the suitable combination of process parameters is much difficult due to non-linear relation between input and output. The aim of this study is to apply a hybrid approach of Artificial Neural Network (ANN) and Non-Dominated Sorting Genetic Algorithm (NSGA-II) to optimize the process parameters of S-EDAG process during machining of Al/SiC/B4C composite. ANN architecture with back propagation algorithm has been used for modeling, which is trained and tested with experimental data. The experimental data have been collected after exhaustive experimentation considering the effect of current, pulse duration, pulse interval, wheel RPM and abrasive grit number on material removal rate (MRR) and average surface roughness (Ra). The developed ANN model has been coupled with NSGA-II to generate the population and evaluate the objective functions during optimization. The results have been shown that hybrid approach of ANN-NSGA-II provides set of optimal solution that helps to manufacturer to select the appropriate combination of input parameters and reduce the product manufacturing cost.

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Electrical Discharge Diamond Grinding (EDDG): A Review

Sharma¹,

Gupta²,

Vates³

et al. 2019

Lecture Notes in Mechanical Engineering

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Application of response surface methodology and genetic algorithm for optimisation of electro-discharge diamond face grinding of tungsten carbide-cobalt composite

Cited by 3 publications

References 26 publications

Hybrid design-based modelling and multi-objective optimization of hybrid machining of hybrid metal matrix composites

Hybrid design-based modelling and multi-objective optimization of hybrid machining of hybrid metal matrix composites

A Hybrid Methodology of ANN-NSGA-II for Optimization of the Process Parameters of Slotted-Electrical Discharge Abrasive Grinding Process

Electrical Discharge Diamond Grinding (EDDG): A Review

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