Abstract—Composite materials have been used in considerable industrial applications due to their light weight and high strength. However, the machining costs of these materials may reach high and the grinding of these materials is much more susceptible to surface damage as compared to metals. Electrolytic In- Process Dressing (ELID) grinding can be used to machine hard and brittle materials to achieve high surface quality and high material removal rate. In the present work, “the Design of Experiments” (DOE) technique is developed for five factors at three levels to conduct experiments. Experiments have been conducted for measuring surface roughness based on the DOE technique in an ELID grinding machine using a diamond wheel. The experimentally measured values are also used to train the feed forward back propagation Neuro-fuzzy for prediction of surface roughness. The ANFIS (Adaptive Neuro-Fuzzy Interference System) predictive neuro fuzzy model was found to be capable of better predictions of surface roughness.
Index Terms—ELID grinding process, Optimization, ANFIS.
P. Babu Aurtherson is with Research Scholar in the Dept. of Manufacturing Engineering, Annamalai University, Chidambaram, India (e-mail: pbaurtherson@ gmail.com.).
S. Sundaram is now with the Department of Manufacturing Engineering, Annamalai University, Chidambaram
Cite: P. Babu Aurtherson, S. Sundaram, A. M. Shanawaz and M. Siva Prakash, "Grinding Process on AlSic composite material and Optimization of surface roughness by ANFIS," International Journal of Engineering and Technology vol. 3, no. 4, pp. 425-430, 2011.
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