EXPERIMENTAL INVESTIGATION ON EDM MACHINING PARAMETERS OF AL/ALUMINA COMPOSITE AND OPTIMIZATION BY GENETIC ALGORITHM

Authors

  • Vijayalakshmi P Department of Mechanical Engineering, Jayalakshmi Institute of Technology,Thoppur
  • Suresh S Department of Mechanical Engineering, Jayalakshmi Institute of Technology,Thoppur
  • Iniyaraja B Department of Mechanical Engineering, Sona College of Technology, Salem
  • Sivalingam A Department of Mechanical Engineering, Sona College of Technology, Salem

Keywords:

EDM, Alumina, Genetic Algorithm

Abstract

Metal Matrix Composites (MMCs) are extremely difficult to Machine using conventional manufacturing processes due to heavy tool wear caused by the presence of the hard particle reinforcement in the metallic matrix. Electro Discharge Machining (EDM) is capable of machining geometrically complex or hard material components. Since the machining cost is so high, it becomes necessary to find out the best combination of parameters before the material is put in to production. The machining information for the particle-reinforced material using EDM is inadequate. This paper presents details and results of an investigation in to the machinability and selection of optimal parametric combination for Alumina (Al2O3) particle reinforced aluminium matrix composites using Electro Discharge Machining process. Genetic Algorithm is used to optimize the objectives such as Metal Removal Rate (MRR) and Surface Roughness (Ra) with parameters Current(I),Pulse on Time(T ON),Pulse off Time(T OFF),Gap control voltage(V)and Flush Pressure(P). The deviation of actual results from the predicted results are in the negligible range.

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References

Joze Valemtincic, Kusen D, Smrkolj S, Oki Blatnink and Mihael Junkar (2007), “Machining parameters selection for varying surface in EDM”, Int. J. Materials and product Technology, Vol. 29, 1/2/3/4.

Rozenek M, Kozak J, Dabrswski L and Lubkowski K (2001), “EDM Characteristics of MMCs”, Journal of Materials Processing Technology, Vol. 109, 367-370.

Koenraad Bonny, Patric de Baets, Jozef Vleugels, Salehi A, Omer Van derBiest, Bert Lauwers and Wenqing Liu, (2008), “EDM machinability and frictional behaviour of ZrO2-WC composites”,International Journal of Advanced Manufacturing Technology, Vol. 41(11),1085-1093.

Su J C, Kao J Y and Tarng Y S (2004), “Optimization of the electrical discharge machining process using a GA-based neural network”, International Journal of Advanced Manufacturing Technology, Vol.24, 81-90.

Shajan kariahose and Shunmugam M S (2005), “Multi-objective optimization of WEDM process by GA”, Journal of Materials Processing Technology, Vol. 170, 133-141.

Mu-Tian yan, Chi-Cheng Fang (2008), “Application of genetic algorithm-based fuzzy logic control in EDM machine”, Journal of Material Processing Technology, Vol. 205, 128-137.

Asthana R (1998), “Processing effect on the properties of cast of metal matrix composites” University of Wisconsil-Stout, Menomonie WI 54751, 213-255.

Lindroos V K and Talvitie M J (1995), “Recent advances in metal matrix composites” Journal of Material Processing Technology, Vol. 53, 273-284.

Bhaskar reddy C, Diwakar reddy V and Eswara reddy C (2012), “Experimental Investigations On Mrr And Surface Roughness Of EN 19 & SS 420 Steels In Wire Edm Using Taguchi Method” International Journal Of Engineering Science And Technology, Vol. 4 (11), 4603-4614.

Harsimran Singh and Harmesh Kumar (2015), “Review On Wire Electrical Discharge Machining (WEDM) Of Aluminum Matrix Composites” International Journal of Mechanical and Production Engineering, Vol. 3 (10).

Nataraj M and Ramesh P (2016), “Investigation on Machining Characteristics of Al 6061 Hybrid Metal Matrix Composite Using Electrical Discharge Machining”, Middle-East Journal of Scientific Research, Vol. 24 (6), 1932-1940.

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Published

2018-09-01

How to Cite

[1]
Vijayalakshmi P, Suresh S, Iniyaraja B, and Sivalingam A, “EXPERIMENTAL INVESTIGATION ON EDM MACHINING PARAMETERS OF AL/ALUMINA COMPOSITE AND OPTIMIZATION BY GENETIC ALGORITHM”, JME, vol. 13, no. 3, pp. 122–129, Sep. 2018.