Nature-Inspired Metaheuristic Approach for Multi-Objective Optimization During WEDM Process

In this research paper Wire-Electric Discharge Machining (WEDM) is applied to machine AISI-D3 material in order to measure the performance of multi-objective responses like high material removal rate and low roughness. This contradictory objective is accomplished by the control parameters like Pulse on Time (Ton), Pulse off Time (Toff), Wire Feed (W/Feed) and Wire Tension (W/Ten) employing brass wire. Here the orthogonal array is used to developed 625 parametric combinations. The optimization of the contradictory responses is carried out in a metaheuristic environment. Artificial Neural Network is employed to train and validate the experimental result. Primarily the individual responses are optimized by employing Firefly algorithm (FA). This is followed by a multi-objective optimization through Genetic algorithm (GA) approach. As the results obtained through GA infer a domain of solutions, therefore Grey Relation Analysis (GRA) is applied where the weights are considered through Fuzzy set theory to ascertain the best parametric combination amongst the set of feasible alternatives.

[1]  Shankar Chakraborty,et al.  Selection of wire electrical discharge machining process parameters using non-traditional optimization algorithms , 2012, Appl. Soft Comput..

[2]  Basil Kuriachen,et al.  Multiresponse optimization of micro-wire electrical discharge machining process , 2015 .

[3]  Zhen Zhang,et al.  Integrated ANN-LWPA for cutting parameter optimization in WEDM , 2015 .

[4]  Mohd Azlishah Othman,et al.  A REVIEW OF FIREFLY ALGORITHM , 2014 .

[5]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[6]  Ravindranadh Bobbili,et al.  Effect of Wire-EDM Machining Parameters on Surface Roughness and Material Removal Rate of High Strength Armor Steel , 2013 .

[7]  J. Deng,et al.  Introduction to Grey system theory , 1989 .

[8]  Satvir Singh,et al.  The Firefly Optimization Algorithm: Convergence Analysis and Parameter Selection , 2013 .

[9]  Jianwen Guo,et al.  The multi-objective optimization of medium-speed WEDM process parameters for machining SKD11 steel by the hybrid method of RSM and NSGA-II , 2014 .

[10]  Richa Garg,et al.  Optimization by Genetic Algorithm , 2014 .

[11]  M. S. Shunmugam,et al.  Multi-objective optimization of wire-electro discharge machining process by Non-Dominated Sorting Genetic Algorithm , 2005 .

[12]  Thella Babu Rao,et al.  Selection of optimal process parameters in WEDM while machining Al7075/SiCp metal matrix composites , 2014 .

[13]  Yunn-Shiuan Liao,et al.  Study of machining parameters optimization for different materials in WEDM , 2014 .

[14]  P. K. Brahmankar,et al.  Determination of material removal rate in wire electro-discharge machining of metal matrix composites using dimensional analysis , 2010 .

[15]  Xin-She Yang,et al.  Firefly Algorithm: Recent Advances and Applications , 2013, ArXiv.

[16]  Didier Dubois,et al.  Operations in a Fuzzy-Valued Logic , 1979, Inf. Control..

[17]  Jose Mathew,et al.  Optimization of Material Removal Rate in Micro-EDM Using Artificial Neural Network and Genetic Algorithms , 2010 .