Mathematical Problems in Engineering / 2018 / Article / Tab 7 / Research Article
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 7 Response surface regression of safety factor versus design parameters.
Source DF Seq SS Contribution Adj SS Adj MS F-Value P-Value Model 35 10.3266 91.71% 10.3266 0.29505 13.59 0.000 Linear 7 6.2102 55.15% 4.2000 0.60000 27.63 0.000 l 1 1 0.0040 0.04% 0.0070 0.00698 0.32 0.574 t 1 1 0.0033 0.03% 0.0198 0.01980 0.91 0.345 l 2 1 5.6464 50.14% 3.8575 3.85746 177.66 0.000 t 2 1 0.0019 0.02% 0.0195 0.01955 0.90 0.348 l 3 1 0.0062 0.05% 0.0002 0.00015 0.01 0.934 t 3 1 0.0237 0.21% 0.0132 0.01323 0.61 0.439 1 0.5248 4.66% 0.3058 0.30581 14.08 0.001 Square 7 3.6100 32.06% 3.6212 0.51731 23.82 0.000 l 1 l 1 1 0.1209 1.07% 0.0723 0.07234 3.33 0.075 t 1 t 1 1 0.1764 1.57% 0.0812 0.08121 3.74 0.060 l 2 l 2 1 3.2129 28.53% 1.1001 1.10007 50.66 0.000 t 2 t 2 1 0.0127 0.11% 0.0783 0.07827 3.60 0.064 l 3 l 3 1 0.0418 0.37% 0.0967 0.09670 4.45 0.041 t 3 t 3 1 0.0105 0.09% 0.0434 0.04343 2.00 0.164 1 0.0348 0.31% 0.0408 0.04083 1.88 0.177 2-Way Interaction 21 0.5064 4.50% 0.5064 0.02411 1.11 0.374 l 1 t1 1 0.0023 0.02% 0.0029 0.00294 0.14 0.715 l 1 l 2 1 0.0010 0.01% 0.0010 0.00104 0.05 0.828 l 1 t 2 1 0.0054 0.05% 0.0053 0.00527 0.24 0.625 l 1 l 3 1 0.0051 0.05% 0.0047 0.00475 0.22 0.642 l 1 t 3 1 0.0010 0.01% 0.0009 0.00092 0.04 0.837 l 1 1 0.0016 0.01% 0.0016 0.00165 0.08 0.784 t 1 l 2 1 0.0320 0.28% 0.0306 0.03061 1.41 0.242 t 1 t 2 1 0.0079 0.07% 0.0073 0.00729 0.34 0.565 t 1 l 3 1 0.0000 0.00% 0.0001 0.00008 0.00 0.953 t 1 t 3 1 0.0015 0.01% 0.0016 0.00163 0.08 0.785 t 1 1 0.0265 0.24% 0.0246 0.02464 1.13 0.293 l 2 t 2 1 0.1314 1.17% 0.1296 0.12961 5.97 0.019 l 2 l 3 1 0.0041 0.04% 0.0043 0.00433 0.20 0.657 l 2 t 3 1 0.0003 0.00% 0.0002 0.00022 0.01 0.920 l 2 1 0.2419 2.15% 0.2428 0.24277 11.18 0.002 t 2 l 3 1 0.0105 0.09% 0.0107 0.01069 0.49 0.487 t 2 t 3 1 0.0058 0.05% 0.0058 0.00580 0.27 0.608 t 2 1 0.0045 0.04% 0.0040 0.00402 0.18 0.669 l 3 t 3 1 0.0001 0.00% 0.0001 0.00006 0.00 0.959 l 3 1 0.0233 0.21% 0.0233 0.02333 1.07 0.306 t 3 1 0.0002 0.00% 0.0002 0.00022 0.01 0.921 Error 43 0.9337 8.29% 0.9337 0.02171 Total 78 11.2603 100.00%
