TEACHING-LEARNING-BASED PARAMETRIC OPTIMIZATION OF AN ELECTRICAL DISCHARGE MACHINING PROCESS

Due to several unique features, electrical discharge machining (EDM) has proved itself as one of the efficient non-traditional machining processes for generating intricate shape geometries on various advanced engineering materials in order to fulfill the requirement of the present day manufacturing industries. In this paper, the machining capability of an EDM process is studied during standard hole making operation on pearlitic SG iron 450/12 grade material, while considering gap voltage, peak current, cycle time and tool rotation as input parameters. On the other hand, material removal rate, surface roughness, tool wear rate, overcut and circularity error are treated as responses. Based on single- and multi-objective optimization models, this process is optimized using the teaching-learning-based optimization (TLBO) algorithm, and its performance is contrasted against firefly algorithm, differential evolution algorithm and cuckoo search algorithm. It is revealed that the TLBO algorithm supersedes the others with respect to accuracy and consistency of the derived optimal solutions, and computational efforts.

[1]  Yan-Cherng Lin,et al.  Machining characteristics of magnetic force-assisted EDM , 2008 .

[2]  Sunny Diyaley,et al.  OPTIMIZATION OF MULTI-PASS FACE MILLING PARAMETERS USING METAHEURISTIC ALGORITHMS , 2019 .

[3]  Multi-objective optimization and analysis of electrical discharge machining process during micro-hole machining of D3 die steel employing salt mixed de-ionized water dielectric , 2013 .

[4]  Bibin K. Tharian,et al.  Multi-Objective Parametric Optimization In EDM Using Grey Relational Analysis , 2019, Materials Today: Proceedings.

[5]  T. Senthilvelan,et al.  Modeling and Optimization of EDM Process Parameters on Machining of Al 7075-B4C MMC Using RSM , 2012 .

[6]  Mohan Kumar Pradhan,et al.  Review on modelling and optimization of electrical discharge machining process using modern Techniques , 2017 .

[7]  Surjya K. Pal,et al.  Modeling of electrical discharge machining process using back propagation neural network and multi-objective optimization using non-dominating sorting genetic algorithm-II , 2007 .

[8]  Sachin Maheshwari,et al.  Multi-objective optimization of electric-discharge machining process using controlled elitist NSGA-II , 2012 .

[9]  H. El-Hofy.  Advanced Machining Processes: Nontraditional and Hybrid Machining Processes , 2005 .

[10]  B. Singh,et al.  Multi-Objective Optimization in Electrical Discharge Machining of 6061 Al/SiCp Using RSM and NSGA-II , 2017 .

[11]  Konstantinos Salonitis,et al.  Parametric Modelling and Multi-Objective Optimization of Electro Discharge Machining Process Parameters for Sustainable Production , 2019, Energies.

[12]  Bijoy Bhattacharyya,et al.  Investigation of electro-discharge micro-machining of titanium super alloy , 2009 .

[13]  Sohil Parsana,et al.  Multi-Objective Optimization of EDM Process Parameters by Using Passing Vehicle Search (PVS) Algorithm , 2018 .

[14]  R. Venkata Rao,et al.  Teaching-learning-based optimization: A novel method for constrained mechanical design optimization problems , 2011, Comput. Aided Des..

[15]  Ajay Batish,et al.  Electric discharge machining of titanium and its alloys: a review , 2012 .

[16]  N. Radhika,et al.  Multi-objective optimization in electric discharge machining of aluminium composite , 2014 .

[17]  Aiman Ziout,et al.  Electric discharge machining of titanium and its alloys: review , 2018, The International Journal of Advanced Manufacturing Technology.

[18]  M. Kiyak,et al.  Examination of machining parameters on surface roughness in EDM of tool steel , 2007 .

[19]  Siba Sankar Mahapatra,et al.  A particle swarm approach for multi-objective optimization of electrical discharge machining process , 2016, J. Intell. Manuf..

[20]  Abhay Sharma,et al.  Multi-objective optimization of electro-discharge machining (EDM) parameter for sustainable machining , 2017 .

[21]  G. Littlefair,et al.  Accuracy of duplex stainless steel feature generated by electrical discharge machining (EDM) , 2018, Measurement.

[22]  N. Senapati,et al.  Optimization of EDM process parameters for AlSiC- 20% SiC reinforced metal matrix composite with multi response using TOPSIS , 2017 .

[23]  Y. Wong,et al.  A study on the fine-finish die-sinking micro-EDM of tungsten carbide using different electrode materials , 2009 .

[24]  S. Laroiya,et al.  Multiobjective Optimization of Electrical Discharge Machining Process Using a Hybrid Method , 2013 .

[25]  Ushasta Aich,et al.  A simple procedure for searching pareto optimal front in machining process: electric discharge machining , 2014 .

[26]  S. K. Choudhury,et al.  Effect of Tool Rotation on MRR, TWR, and Surface Integrity of AISI-D3 Steel using the Rotary EDM Process , 2016 .