Analysis and Optimization of Wire EDM Process of Titanium by Using GRA Methodology

Article Preview

Abstract:

In this research work, an efficient optimization technique, grey relational analysis (GRA) has been used to for optimization of wire electrical discharge machining process of Titanium (grade 2) by considering multiple output parameters. This technique combines Taguchi’s orthogonal array with grey relational analysis for the design of the experiment. The central focus of this research is to achieve improved Kerf width, surface roughness and cutting speed. GRA method is implemented to decide the best input parameter that optimizes the output parameters. This study has been conducted by applying Taguchi’s L9 orthogonal array. Each experiment has been conducted in altered conditions of input variables. For the optimization of multiple criteria, GRA is suggested as a suitable technique for the optimization of complex interrelationships between multi-performance characteristics. By analysis of variance (ANOVA) it is found that the percentage of contribution of peak current on overall performance is maximum i.e.73.1%.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

678-684

Citation:

Online since:

August 2019

Export:

Price:

* - Corresponding Author

[1] R. Garg and H. Singh (2008), Effects of process parameters on output characteristics in WEDM, International Journal of Manufacturing Science and Technology, Vol.2, No.2, Dec.2008, pp.103-112.

Google Scholar

[2] H. Singh and R. Garg (2009), Effects of process parameters on material removal rate in WEDM, Journal of Achievements in Materials and Manufacturing Engineering, Vol. 32, Issue-1, Jan., pp.70-74.

Google Scholar

[3] R. M. Arunachalam, M. A. Mannan and A. C. Spowage (2004), Residual stress and surface roughness when facing age hardened Inconel718 with CBN and ceramic cutting tools. Int J Mach Tools Manuf44(9):879–887.

DOI: 10.1016/j.ijmachtools.2004.02.016

Google Scholar

[4] R. Bobbili, V. Madhu and A.K. Gogia (2015), Multi-response optimization of Wire-EDM process parameters of ballistic grade aluminum alloy, Engineering science and technology, an international journal, 18, 720-726.

DOI: 10.1016/j.jestch.2015.05.004

Google Scholar

[5] A. Goswami and J. Kumar (2014), Optimization in wire-cut EDM of Nimonic-80A using taguchi approach and utility concept, Engineering science and technology, an international journal, 17, 236-246.

DOI: 10.1016/j.jestch.2014.07.001

Google Scholar

[6] S. S. Nain, D. Garg and S. Kumar (2017), Modeling and optimization of process variable of Wire-cut electric discharge machining of super alloy Udimet-L605, Engineering science and technology, an international journal,20, 247-264.

DOI: 10.1016/j.jestch.2016.09.023

Google Scholar

[7] A. Bara, S. K. Sahoo and S. S. Naik (2017), Multi-response Optimization of Nd:YAG Laser for Micro-drilling of 304 Stainless Steel Using Grey Relational Analysis, In: Advances in 3D Printing & Additive Manufacturing Technologies. Springer, 2017, pp.101-110.

DOI: 10.1007/978-981-10-0812-2_9

Google Scholar

[8] A. K. Sahu, P. P. Mohanty and S. K. Sahoo (2017), Electro discharge machining of Ti-alloy (Ti6Al4V) and 316LStainless Steel and Optimization of process parameters by Grey relational analysis (GRA) method, In: Advances in 3D Printing & Additive Manufacturing Technologies, Springer, pp.65-78.

DOI: 10.1007/978-981-10-0812-2_6

Google Scholar

[9] G. Rajyalashmi and P. V. Ramaiah (2013), Multiple process parameter optimization of wire electrical discharge machining on Inconel 825 using Taguchi grey relation analysis, Int J AdvManufTechnol, 69, 1249-1262.

DOI: 10.1007/s00170-013-5081-z

Google Scholar

[10] V. S. Gadakh (2012) Parametric optimization of wire electrical discharge machining using TOPSIS method, Advances in Production Engineering & Management, Vol. 7, 157-164.

DOI: 10.14743/apem2012.3.138

Google Scholar

[11] A. P. Tiwary, B B. Pradhan and B. Bhattacharyya (2014) Application of multi-criteria decision making methods for selection of micro-EDM process parameters, Adv. Manuf. 2, 251-258.

DOI: 10.1007/s40436-013-0050-1

Google Scholar

[12] A. Bara, S. K. Sahoo, S. S. Naik, A. K. Sahu and S. S. Mahapatra (2018), Multi Response Optimization of Nd:YAG Laser Micro Drilling Characteristics of 304 Stainless Steel using Desirability Function Approach, Materials Today: Proceedings, 5,18975–18982.

DOI: 10.1016/j.matpr.2018.06.248

Google Scholar

[13] S. K. Sahoo, S. S. Naik and J. Rana (2019), Experimental Analysis of Wire EDM Process Parameters for Micromachining of High Carbon High Chromium Steel by Using MOORA Technique, In: Micro and Nano Machining of Engineering Materials, Materials Forming, Machining and Tribology, Springer, https://doi.org/10.1007/978-3-319-99900-5_7.

DOI: 10.1007/978-3-319-99900-5_7

Google Scholar

[14] R. S. Pawade, S. S. Joshi (2011,) Multi-objective optimization of surface roughness and cutting forces in high-speed turning of Inconel 718 using Taguchi grey relational analysis (TGRA). Int J Adv Manuf Technol 56, 47–62.

DOI: 10.1007/s00170-011-3183-z

Google Scholar

[15] A. K. Sahu and S. S. Mahapatra (2018), Performance Analysis of Rapid Tool in Electrical Discharge Machining During Machining of Titanium Alloy (Ti6Al4V). ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers.

DOI: 10.1115/detc2018-85489

Google Scholar

[16] N. Tosun (2006), Determination of optimum parameters for multi performance characteristics in drilling by using grey relational analysis. Int J Adv Manuf Technol 28, 450–455.

DOI: 10.1007/s00170-004-2386-y

Google Scholar

[17] A. K. Sahu and S. S. Mahapatra (2018), Electrical Discharge Coating by Copper-Tungsten Composite Electrode Prepared by Powder Metallurgy Route, In: Soft Computing Techniques and Applications in Mechanical Engineering IGI Global, 2018, pp.195-224.

DOI: 10.4018/978-1-5225-3035-0.ch010

Google Scholar