References
- Al-Refaie, A., Al-Durgham, L. & Bata, N. 2010, “Optimal Parameter Design by Regression Technique and Grey Relational Analysis”, Proceedings of the World Congress on Engineering III (WCE 2010), London.
- Chakradhar, D. & Venu Gopal, A. 2011, “Multi-Objective Optimization of Electrochemical machining of EN31 steel by Grey Relational Analysis”, International Journal of Modeling and Optimization, Vol. 1, No. 2, pp. 113–117.
- Chiang, K.-T., Chang, F.-P. & Tsai, D.-C. 2007, “Modeling and analysis of the rapidly resolidified layer of SG cast iron in the EDM process through the response surface methodology”, Journal of Materials Processing Technology, Vol. 182, pp. 525–533.
- Deepak, J., Mishra, A. & Sneh, A. 2011, “ANFIS based knee angle prediction: An approach to design speed adaptive contralateral controlled AK prosthesis”, Applied Soft Computing, Vol. 11, pp. 4757–4765.
- Guu, Y. H., Hocheng, H., Chou, C. Y. & Deng, C. S. 2003, “Effect of electrical discharge machining on surface characteristics and machining damage of AISI D2 tool steel”, Materials Science and Engineering, Vol. 358, pp. 37–43.
- Hashmi, K., El Baradie, M. A. & Ryan, M. 1999, “Fuzzy-logic based intelligent selection of machining based upon neural network models”, International Journal of Machine Tools and Manufacture, Vol. 41, pp. 1385–1403.
- Hashmi, K., Graham, I. D. & Mills, B. 2000, “Fuzzy logic based data selection for the drilling process”, Journal of Materials Processing Technology, Vol. 108, pp. 55–61.
- Joshi, S. N. & Pande, S. S. 2011, “Intelligent process modeling and optimization of die-sinking electric discharge machining”, Applied Soft Computing, Vol. 11, pp. 2743–2755.
- Kansal, H. K. & Singh, S. & Kumar, P. 2005, “Parametric optimization of powder mixed electrical discharge machining by response surface methodology”, Journal of Materials Processing Technology, Vol. 169, pp. 427–436.
- Labib, A. W., Keasberry, V. J., Atkinson, J. & Frost, H. W. 2011, “Towards next generation electrochemical machining controllers:A fuzzy logic control approach to ECM”, Expert Systems With Applications, Vol. 38, pp. 7486–7493.
- Mamalis, A. G., Vogtlander, L. O. G. & Markopoulos, A. 2004, “Nanotechnology and nanostructured materials: trends in carbon nanotubes”, Precision Engineering, Vol. 28, pp. 16–30.
- Narender Singh, P., Raghukandan, K. & Pai, B. C. 2004, “Optimization by grey relational analysis of EDM parameters on machining Al-10%SiCP composites”, Journal of Materials Processing Technology, Vol. 155-156, pp. 1658–1661.
- Pecas, P. & Henriques, E. 2008, “Electrical discharge machining using simple and powder-mixed dielectric: the effect of the electrode area in the surface roughness and topography”, Journal of Materials Processing Technology, Vol. 200, pp. 250–258.
- Prabhu, S. & Vinayagam, B. K. 2011, “AFM surface Investigation of Inconel 825 with Multi Wall Carbon Nano Tube in Electrical Discharge Machining Process using Taguchi analysis”, Archives of Civil and Mechanical Engineering (ACME) Journal, Vol. 11, No. 1, pp. 149–170.
- Puertas, I., Luis, C. J. & Alvarez, L. 2004, “Analysis of the influence of EDM parameters on surface quality MRR and EW of WC-Co”, Journal of Materials Processing Technology, Vol. 153-154, pp. 1026–1032.
- Skrabalak, G., Zybura-Skrabalak, M. & Ruszaj, A. 2004, “Building of rules base for fuzzy-logic control of the ECDM process”, Journal of Materials Processing Technology, Vol. 149, pp. 530–535.
- Tzeng, Y. & Chen, F. 2007, “Multi-objective optimisation of high-speed electrical discharge machining process using a Taguchi fuzzy-based approach”, Materials and Design, Vol. 28, pp. 1159–1168.
- Yilmaz, O., Eyercioglu, O. & Gindy, N. N. Z. 2006, “A user-friendly fuzzy based system for the selection of electro discharge machining process parameters”, Journal of Materials Processing Technology, Vol. 172, pp. 363–371.