@article{(Open Science Index):https://publications.waset.org/pdf/4307,
	  title     = {A Fuzzy Logic Based Model to Predict Surface Roughness of A Machined Surface in Glass Milling Operation Using CBN Grinding Tool},
	  author    = {Ahmed A. D. Sarhan and  M. Sayuti and  M. Hamdi},
	  country	= {},
	  institution	= {},
	  abstract     = {Nowadays, the demand for high product quality
focuses extensive attention to the quality of machined surface. The
(CNC) milling machine facilities provides a wide variety of
parameters set-up, making the machining process on the glass
excellent in manufacturing complicated special products compared to
other machining processes. However, the application of grinding
process on the CNC milling machine could be an ideal solution to
improve the product quality, but adopting the right machining
parameters is required. In glass milling operation, several machining
parameters are considered to be significant in affecting surface
roughness. These parameters include the lubrication pressure, spindle
speed, feed rate and depth of cut. In this research work, a fuzzy logic
model is offered to predict the surface roughness of a machined
surface in glass milling operation using CBN grinding tool. Four
membership functions are allocated to be connected with each input
of the model. The predicted results achieved via fuzzy logic model
are compared to the experimental result. The result demonstrated
settlement between the fuzzy model and experimental results with the
93.103% accuracy.},
	    journal   = {International Journal of Industrial and Manufacturing Engineering},
	  volume    = {6},
	  number    = {10},
	  year      = {2012},
	  pages     = {2122 - 2128},
	  ee        = {https://publications.waset.org/pdf/4307},
	  url   	= {https://publications.waset.org/vol/70},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 70, 2012},
	}