Modeling and Optimization of Electric Discharge Machining Performances using Harmony Search Algorithm
Keywords:Harmony Search, Regression, Electric Discharge Machining, Surface Roughness, Electrode Wear Rate
Electric Discharge Machining (EDM) is one of the widely used non-conventional machining processes for complex and difficult-to-machine materials. EDM technology has been improve significantly and has been developed in many ideas especially in the manufacturing industries that yielded enormous benefits in economic as well as generating keen interest in research area. A major issue in EDM process is how to obtain accurate results of the machining performance measurement value at optimal point of cutting conditions. Thus, this study proposed harmony search algorithm approach for optimization of surface roughness (Ra) in die sinking electric discharge machining (EDM). The mathematical model was developed using regression analysis based on four machining parameters which are pulse on time, peak current, servo voltage and servo speed. The result shows that the optimal solutions for Ra can be found with the minimum values of 1.3031 Âµm.
Deris, A. M., Zain, A. M., & Sallehuddin, R. (2013). Hybrid GR-SVM for prediction of surface roughness in abrasive water jet machining. Meccanica, 48(8), 1937-1945.
Cole, J., Alzofiri, S., Gallardo, V., Pasillas, M., and James, S. (2017). Design and Fabrication of a Micro Electro Discharge Machining System.
Holmberg, J., Wretland, A., & Berglund, J. (2016). Grit blasting for removal of recast layer from EDM process on Inconel 718 Shaft: an evaluation of surface integrity. Journal of Materials Engineering and Performance, 25(12), 5540-5550.
Dewangan, S., Gangopadhyay, S., & Biswas, C. K. (2015). Multi-response optimization of surface integrity characteristics of EDM process using grey-fuzzy logic-based hybrid approach. Engineering Science and Technology, an International Journal, 18(3), 361-368.
Garg, H. K., Kumar, R., & Manna, A. (2017). Multi Response Optimization of Electric Discharge Machining (EDM) Parameters for Machining Hybrid Aluminum Metal Matrix Composite using Grey Relation Analysis (GRA).
Zain AM, Haron H, Sharif S. Estimation of the minimum machining performance in the abrasive waterjet machining using integrated ANN-SA. Expert Syst Appl 2011; 38 (7):8316-26.
Mohamad, A., Zain, A. M., Bazin, N. E. N., & Udin, A. (2015). A process prediction model based on Cuckoo algorithm for abrasive waterjet machining. Journal of Intelligent Manufacturing, 26(6), 1247-1252.
Zainal, N., Zain, A. M., Radzi, N. H. M., & Othman, M. R. (2016). Glowworm swarm optimization (GSO) for optimization of machining parameters. Journal of Intelligent Manufacturing, 27(4), 797-804.
Kamaruzaman, A. F., Zain, A. M., Yusuf, S. M., & Udin, A. (2013). Levy flight algorithm for optimization problems-a literature review. In Applied Mechanics and Materials (Vol. 421, pp. 496-501). Trans Tech Publications.
Raja, S. B., Pramod, C. S., Krishna, K. V., Ragunathan, A., & Vinesh, S. (2015). Optimization of electrical discharge machining parameters on hardened die steel using Firefly Algorithm. Engineering with Computers, 31(1), 1-9.
Teimouri, R., & Baseri, H. (2014). Optimization of magnetic field assisted EDM using the continuous ACO algorithm. Applied Soft Computing, 14, 381-389.
Rao, M. S., & Venkaiah, N. (2015). Parametric optimization in machining of Nimonic-263 alloy using RSM and particle swarm optimization. Procedia Materials Science, 10, 70-79.
Geem, Z. W., Kim, J. H., & Loganathan, G. V. (2001). A New Heuristic Optimization Algorithm: Harmony Search. Simulation, 76(2), 60-68.
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