An Efficient Hybrid Approach of Finite Element Method, Artificial Neural Network-Based Multiobjective Genetic Algorithm for Computational Optimization of a Linear Compliant Mechanism of Nanoindentation Tester

Table 4

Design of experiments and training data using CCD.

No.	l1; (mm)	t1; (mm)	l2; (mm)	t2; (mm)	l3; (mm)	t3; (mm)	(mm)	Displacement; (μm)	Safety factor
1	30	0.5	20	0.4	0.5	6	10	472.59	3.63
2	30	0.5	20	0.4	0.5	6	5	476.33	3.68
3	30	0.5	20	0.4	0.5	6	15	474.79	3.57
4	30	0.5	18	0.4	0.5	6	10	602.70	1.87
5	30	0.5	22	0.4	0.5	6	10	392.22	2.61
6	30	0.5	20	0.36	0.5	6	10	481.24	3.62
7	30	0.5	20	0.44	0.5	6	10	467.73	3.77
8	30	0.5	20	0.4	0.45	6	10	468.62	3.72
9	30	0.5	20	0.4	0.55	6	10	475.77	3.68
10	30	0.5	20	0.4	0.5	5.4	10	473.37	3.60
11	30	0.5	20	0.4	0.5	6.6	10	471.30	3.67
12	27	0.5	20	0.4	0.5	6	10	465.98	3.74
13	33	0.5	20	0.4	0.5	6	10	478.28	3.66
14	30	0.45	20	0.4	0.5	6	10	473.23	3.64
15	30	0.55	20	0.4	0.5	6	10	470.26	3.71
16	28.93	0.51	19.29	0.38	0.48	5.78	8.23	521.26	2.94
17	28.93	0.48	19.29	0.38	0.48	5.78	11.76	524.74	3.04
18	28.93	0.48	20.70	0.38	0.48	5.78	8.23	431.56	3.36
19	28.93	0.51	20.70	0.38	0.48	5.78	11.76	434.51	3.78
20	28.93	0.48	19.29	0.41	0.48	5.78	8.23	515.78	3.01
21	28.93	0.51	19.29	0.41	0.48	5.78	11.76	514.26	3.12
22	28.93	0.51	20.70	0.41	0.48	5.78	8.23	428.35	3.35
23	28.93	0.48	20.70	0.41	0.482	5.78	11.76	432.74	3.78
24	28.93	0.48	19.29	0.38	0.51	5.78	8.23	527.63	2.88
25	28.93	0.51	19.29	0.38	0.51	5.78	11.76	526.40	3.03
26	28.93	0.51	20.70	0.38	0.51	5.78	8.23	438.24	3.53
27	28.93	0.48	20.70	0.38	0.51	5.78	11.76	436.99	3.76
28	28.93	0.51	19.29	0.41	0.51	5.78	8.23	517.02	2.97
29	28.93	0.48	19.29	0.41	0.51	5.78	11.76	520.74	3.04
30	28.93	0.48	20.70	0.41	0.51	5.78	8.23	434.69	3.49
31	28.93	0.51	20.70	0.41	0.51	5.78	11.76	431.84	3.71
32	28.93	0.48	19.29	0.38	0.48	6.21	8.23	522.59	3.00
33	28.93	0.51	19.29	0.38	0.48	6.21	11.76	524.15	3.05
34	28.93	0.51	20.70	0.38	0.48	6.21	8.23	430.91	3.42
35	28.93	0.48	20.70	0.38	0.48	6.21	11.76	434.53	3.96
36	28.93	0.51	19.29	0.41	0.48	6.21	8.23	512.86	3.07
37	28.93	0.48	19.29	0.41	0.48	6.21	11.76	513.27	3.12
38	28.93	0.48	20.70	0.41	0.48	6.21	8.23	433.47	3.44
39	28.93	0.51	20.70	0.41	0.48	6.21	11.76	430.08	3.89
40	28.93	0.51	19.29	0.38	0.51	6.21	8.23	523.21	2.93
41	28.93	0.48	19.29	0.38	0.51	6.21	11.76	526.51	3.04
42	28.93	0.48	20.70	0.38	0.51	6.21	8.23	438.89	3.67
43	28.93	0.51	20.70	0.38	0.51	6.21	11.76	437.81	3.79
44	28.93	0.48	19.29	0.41	0.51	6.21	8.23	517.41	2.99
45	28.93	0.51	19.29	0.41	0.51	6.21	11.76	514.68	3.06
46	28.93	0.51	20.70	0.41	0.51	6.21	8.23	433.78	3.33
47	28.93	0.48	20.70	0.41	0.51	6.21	11.76	433.24	3.74
48	31.06	0.48	19.29	0.38	0.48	5.78	8.23	529.57	2.93
49	31.06	0.51	19.29	0.38	0.48	5.78	11.76	527.76	3.06
50	31.06	0.51	20.70	0.38	0.48	5.78	8.23	441.45	3.60
51	31.06	0.48	20.70	0.38	0.48	5.78	11.76	440.86	3.82
52	31.06	0.51	19.29	0.41	0.48	5.78	8.23	520.39	2.99
53	31.06	0.48	19.29	0.41	0.48	5.78	11.76	522.99	3.09
54	31.06	0.48	20.70	0.41	0.48	5.78	8.23	438.41	3.54
55	31.06	0.51	20.70	0.41	0.48	5.78	11.76	436.12	3.65
56	31.06	0.51	19.29	0.38	0.51	5.78	8.23	530.31	2.94
57	31.06	0.48	19.29	0.38	0.51	5.78	11.76	533.15	3.01
58	31.06	0.48	20.70	0.38	0.51	5.78	8.23	439.53	3.32
59	31.06	0.51	20.70	0.38	0.51	5.78	11.76	444.13	3.78
60	31.06	0.48	19.29	0.41	0.51	5.78	8.23	524.97	2.94
61	31.06	0.517	19.29	0.41	0.51	5.78	11.76	524.10	3.05
62	31.06	0.51	20.70	0.41	0.51	5.78	8.23	435.03	3.32
63	31.06	0.48	20.70	0.41	0.51	5.78	11.76	439.34	3.72
64	31.06	0.51	19.29	0.38	0.48	6.21	8.23	526.08	3.01
65	31.06	0.48	19.29	0.38	0.48	6.21	11.76	529.12	3.05
66	31.06	0.48	20.70	0.38	0.48	6.21	8.23	436.64	3.44
67	31.06	0.51	20.70	0.38	0.48	6.21	11.76	440.67	3.84
68	31.06	0.48	19.29	0.41	0.48	6.21	8.23	520.62	2.99
69	31.06	0.51	19.29	0.41	0.48	6.21	11.76	520.96	3.13
70	31.06	0.51	20.70	0.41	0.48	6.21	8.23	436.90	3.41
71	31.06	0.48	20.70	0.41	0.48	6.21	11.76	438.74	3.86
72	31.06	0.48	19.29	0.38	0.51	6.21	8.23	530.51	2.92
73	31.06	0.51	19.29	0.38	0.51	6.21	11.76	527.16	3.03
74	31.06	0.51	20.70	0.38	0.51	6.21	8.23	442.88	3.63
75	31.06	0.48	20.70	0.38	0.51	6.21	11.76	442.26	3.88
76	31.06	0.51	19.29	0.41	0.51	6.21	8.23	521.42	3.04
77	31.06	0.48	19.29	0.41	0.51	6.21	11.76	522.38	3.07
78	31.06	0.48	20.70	0.41	0.51	6.21	8.23	434.91	3.32
79	31.06	0.51	20.70	0.41	0.51	6.21	11.76	439.50	3.56