An Optimized Design of New XYθ Mobile Positioning Microrobotic Platform for Polishing Robot Application Using Artificial Neural Network and Teaching-Learning Based Optimization

Table 6

Analysis of variance for the stroke.

Source	DF	Seq SS	Contribution (%)	Adj SS	Adj MS	F-value	value
Model	20	120513	89.49	120513	6025.7	2.56	0.124
Linear	5	78626	58.39	74177	14835.4	6.29	0.022
A	1	629	0.47	402	401.5	0.17	0.694
B	1	816	0.61	538	538.3	0.23	0.650
C	1	50697	37.65	42836	42836.3	18.17	0.005
D	1	16789	12.47	22090	22089.6	9.37	0.022
E	1	9695	7.20	8915	8914.8	3.78	0.100
Square	5	11426	8.49	11673	2334.7	0.99	0.494
A^∗A	1	3	0.00	543	542.9	0.23	0.648
B^∗B	1	847	0.63	0	0.1	0.00	0.995
C^∗C	1	971	0.72	2371	2371.5	1.01	0.355
D^∗D	1	1855	1.38	125	125.0	0.05	0.826
E^∗E	1	7750	5.76	7236	7236.3	3.07	0.130
2-Way interaction	10	30461	22.62	30461	3046.1	1.29	0.392
A^∗B	1	3646	2.71	3897	3897.1	1.65	0.246
A^∗C	1	1382	1.03	1339	1338.9	0.57	0.480
A^∗D	1	6	0.00	149	148.8	0.06	0.810
A^∗E	1	612	0.45	654	654.0	0.28	0.617
B^∗C	1	5120	3.80	6498	6498.5	2.76	0.148
B^∗D	1	8707	6.47	7900	7900.3	3.35	0.117
B^∗E	1	2376	1.76	2570	2570.0	1.09	0.337
C^∗D	1	7492	5.56	7488	7488.1	3.18	0.125
C^∗E	1	1115	0.83	1103	1102.8	0.47	0.520
D^∗E	1	6	0.00	6	5.9	0.00	0.962
Error	6	14147	10.51	14147	2357.9
Total	26	134661	100.00