Optimization of Process Parameters of Wire Electric Discharge Machining Process for Machining AISI A2 Tool Steel
DOI:
https://doi.org/10.18311/jmmf/2024/38682Keywords:
AISI A2 Tool Steel, Design of Experiments, Material Removal Rate, Surface Roughness, Wire Electric Discharge MachiningAbstract
In this investigation, AISI A2 tool steel is considered as the workpiece material, which is typically used to manufacture blanking tools, punches die etc., due to its good toughness and wear resistance. In this work, the effect of controlling parameters of the Wire Electric Discharge Machining (WEDM) process is investigated. Molybdenum tool electrodes of 0.18mm diameter and de-ionized water dielectric medium are utilized. Peak current, on-time, off-time and voltage are considered as the controlling parameters. Surface roughness average and material erosion rate are considered as the response parameters. The type of design of experiments considered for this work is Taguchi’s L27 orthogonal array. Analysis of variance indicates the percentage contribution of each machining parameter on response parameters. The optimum combination of machining parameters yields a minimum surface roughness of 2.87 μm and the highest material removal rate obtained in this work is 774 mm3/hr.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Accepted 2024-03-29
Published 2024-04-22
References
Arunachalam R, Mannan MA. Machinability of nickel-based high-temperature alloys. Machining Science and Technology. 2000; 4(1):127-68. https://doi. org/10.1080/10940340008945703 DOI: https://doi.org/10.1080/10940340008945703
Patel KM, Pulak MP, Venkateswara RP. Determination of an optimum parametric combination using a surface roughness prediction model for EDM of Al2O3/SiCw/TiC Ceramic Composite. Materials and Manufacturing Processes. 2009; 24:675-82. https://doi. org/10.1080/10426910902769319 DOI: https://doi.org/10.1080/10426910902769319
Mahapatra SS, Amar Patnaik. Optimization of Wire Electrical Discharge Machining (WEDM) process parameters using Taguchi method. International Journal of Advanced Manufacturing Technology. 2007; 34:911- 25. https://doi.org/10.1007/s00170-006-0672-6 DOI: https://doi.org/10.1007/s00170-006-0672-6
Yan-Cherng L, Yuan-Feng C, Der-An W, Ho-Shiun L. Optimization of machining parameters in magnetic force assisted EDM based on Taguchi method. Journal of Materials Processing Technology. 2009; 209:3374-83. https://doi.org/10.1016/j.jmatprotec.2008.07.052 DOI: https://doi.org/10.1016/j.jmatprotec.2008.07.052
Tamura T. Development of on-the-machine surface modification technology in EDM. Procedia CIRP. 2013; 6:117-22. https://doi.org/10.1016/j.procir.2013.03.049 DOI: https://doi.org/10.1016/j.procir.2013.03.049
Sengottuvel P, Satishkumar S, Dinakaran D. Optimization of multiple characteristics of EDM parameters based on desirability approach and fuzzy modelling. Procedia Engineering. 2013; 64:1069-78. https://doi.org/10.1016/j. proeng.2013.09.185 DOI: https://doi.org/10.1016/j.proeng.2013.09.185
Sunil SB, Banwait SS, Laroiya SC. Multi-objective optimization of electrical discharge machining process using a hybrid method. Materials and Manufacturing Processes. 2013; 28:348-54. https://doi.org/10.1080/104 26914.2012.700152 DOI: https://doi.org/10.1080/10426914.2012.700152
Manjunath PGC, Sandeep K, Danil YP, Khaled G. Experimental analysis and optimization of EDM parameters on HcHcr steel in context with different electrodes and dielectric fluids using hybrid Taguchibased PCA-utility and critic-utility approaches. Metals. 2021; 11(419):1-23. https://doi.org/10.3390/ met11030419 DOI: https://doi.org/10.3390/met11030419
Arindam M, Pankaj KD, Abhishek M, Moutushee D. An approach to optimize the EDM process parameters using desirability-based multiobjective PSO. Production and Manufacturing Research. 2014; 2(1):228-40. https:// doi.org/10.1080/21693277.2014.902341 DOI: https://doi.org/10.1080/21693277.2014.902341
Pujari SR, Koona R, Beela S. Experimental investigation and optimization of wire EDM parameters for surface roughness, MRR and white layer in the machining of aluminium alloy. Procedia Materials Science. 2014; 5:2197-206. https://doi.org/10.1016/j.mspro.2014.07.426 DOI: https://doi.org/10.1016/j.mspro.2014.07.426
Satishkumar D, Kanthababu M, Vajjiravelu V, Anburaj R, Thirumalai SR, Arul H. Investigation of wire electrical discharge machining characteristics of Al6063/SiCp composites. The International Journal of Advanced Manufacturing Technology. 2011; 56:975-86. https://doi. org/10.1007/s00170-011-3242-5 DOI: https://doi.org/10.1007/s00170-011-3242-5
Zhen Z, Wuyi M, Hao H, Zhi C, Zhong X, Yu H, Guojun Z. Optimization of process parameters on surface integrity in wire electrical discharge machining of tungsten tool YG15. The International Journal of Advanced Manufacturing Technology. 2015; 81:1303- 17. https://doi.org/10.1007/s00170-015-7266-0 DOI: https://doi.org/10.1007/s00170-015-7266-0
Neeraj S, Rajesh K, Rahul DG. WEDM process variables investigation for HSLA by response surface methodology and genetic algorithm. Engineering Science and Technology, an International Journal. 2015; 18:171-7. https://doi.org/10.1016/j.jestch.2014.11.004 DOI: https://doi.org/10.1016/j.jestch.2014.11.004
Kamlesh P, Pramanik A, Chattopadhyaya S. Machining performance of Inconel 718 using graphene nanofluid in EDM. Materials and Manufacturing Processes. 2020; 35:33-42. https://doi.org/10.1080/10426914.2020.17119 24 DOI: https://doi.org/10.1080/10426914.2020.1711924
Amit K, Tarun S, Jitendra K. Optimisation of wirecut EDM process parameter by grey-based response surface methodology. Journal of Industrial Engineering International. 2018; 14:821-9. https://doi.org/10.1007/ s40092-018-0264-8 DOI: https://doi.org/10.1007/s40092-018-0264-8
Aldrin RJ, Balasubramanian K, Palanisamy D, Emmanuel AGS. Experimental investigations on WEDM process for machining high manganese steel. Materials and Manufacturing Processes. 2020; 35:1612-21. https://doi. org/10.1080/10426914.2020.1779941 DOI: https://doi.org/10.1080/10426914.2020.1779941