A Novel Performance Prediction Model for the Machining Process Based on the Interval Type-2 Fuzzy Neural Network

Table 1

Datasets for designing the experiment [26].

No.	Pulse off-time (μs)	Spark gap (μm)	Servo feed (level)	Rotational speed (rpm)	Flushing pressure (bar)	MRR (mm^3/min)	Ra (μm)
1	30	30	3	30	3.267	1.24	2.396
2	30	50	5	70	3.267	2.21	3.756
3	30	80	8	100	3.267	2.60	4.134
4	34	30	5	100	3.267	1.73	3.172
5	34	50	8	30	3.267	3.78	5.009
6	34	80	3	70	3.267	1.45	2.827
7	42	30	8	70	3.267	1.50	2.899
8	42	50	3	100	3.267	0.95	2.116
9	42	80	5	30	3.267	1.68	3.133
10	30	30	3	30	1.893	1.16	2.311
11	30	50	5	70	1.893	2.20	3.539
12	30	80	8	100	1.893	2.47	4.003
13	34	30	5	100	1.893	1.40	2.694
14	34	50	8	30	1.893	3.72	4.897
15	34	80	3	70	1.893	1.37	2.502
16	42	30	8	70	1.893	1.46	2.895
17	42	50	3	100	1.893	0.82	2.069
18	42	80	5	30	1.893	1.65	3.124
19	30	30	3	30	1.263	1.10	2.264
20	30	50	5	70	1.263	1.48	2.860
21	30	80	8	100	1.263	2.22	3.794
22	34	30	5	100	1.263	1.34	2.506
23	34	50	8	30	1.263	3.20	4.576
24	34	80	3	70	1.263	1.35	2.520
25	42	30	8	70	1.263	1.37	2.588
26	42	50	3	100	1.263	0.78	2.048
27	42	80	5	30	1.263	1.54	2.987
28	30	50	8	70	3.267	2.80	4.281
29	34	80	5	50	1.893	1.44	2.744
30	42	50	3	50	1.263	0.98	2.149