Prediction of Surface Roughness When End Milling Ti6Al4V Alloy Using Adaptive Neurofuzzy Inference System

Table 8

Experimental and ANFIS results of PVD coated cutting tool.

No.	Cutting speed (m/min)	Feed rate (mm/tooth)	Depth of cut (mm)	Surface roughness (µm)	Model A	Model B	Model C
1	77.5	0.1	1	0.55	0.55	0.55	0.55
2	105	0.1	1.5	0.35	0.350001	0.350001	0.350001
3	77.5	0.15	1.5	0.9	0.886667	0.886667	0.886667
4	77.5	0.15	1.5	0.86	0.886667	0.886667	0.886667
5	50	0.15	1	0.72	0.719999	0.719999	0.719999
6	77.5	0.2	1	1.32	1.32	1.32	1.32
7	105	0.15	2	0.8	0.8	0.8	0.8
8	105	0.2	1.5	1.32	1.32	1.32	1.32
9	50	0.15	2	0.7	0.700001	0.700001	0.700001
10	105	0.15	1	0.58	0.579999	0.579999	0.579999
11	77.5	0.15	1.5	0.9	0.886667	0.886667	0.886667
12	50	0.2	1.5	0.8	0.8	0.8	0.8
13	77.5	0.2	2	0.91	0.91	0.91	0.91
14	77.5	0.1	2	1.32	1.319998	1.319998	1.319998