|
| Case study | Method | Optimal factors | Optimal responses |
| Frequency (Hz) | Displacement (mm) | Stress (MPa) | MPCI |
|
| Case 1 | Hybrid of Taguchi method and fuzzy logic | D = 2.25 mm
L3 = 8.5 mm
L4 = 18.7 mm | Predicted:
F1 = 24.4574
FEA:
F1 = 26.283
ε = 6.94% | Predicted:
F2 = 0.1691
FEA:
F2 = 0.1772
ε = 4.57% | Predicted:
F3 = 251.463
FEA:
F3 = 259.42
ε = 3.06% | 0.510 |
| Proposed hybrid approach of fuzzy-ANFIS-LAPO algorithm | D = 2.30 mm
L3 = 8.5 mm
L4 = 18.7 mm | Predicted:
F1 = 26.592
FEA:
F1 = 25.828
ε = 2.95% | Predicted:
F2 = 0.1679
FEA:
F2 = 0.1766
ε = 4.92% | Predicted:
F3 = 253.847
FEA:
F3 = 260.570
ε = 2.58% | 0.570 |
|
| Case 2 | Hybrid of Taguchi method and fuzzy logic | θ = 16.5o
L1 = 7.7 mm
L2 = 18.7 mm
D = 2.25 mm | Predicted:
F1 = 28.9482
FEA:
F1 = 649.3
ε = 2.58% | Predicted:
F2 = 0.1527
FEA:
F2 = 0.1782
ε = 9.55% | Predicted:
F3 = 7.9628
FEA:
F3 = 7.8629
ε = 1.28% | 0.375 |
| Proposed hybrid approach of fuzzy-ANFIS-LAPO algorithm | θ = 16.5o
L1 = 8.0 mm
L2 = 14.5 mm
D = 2.5 mm | Predicted:
F1 = 651.08
FEA:
F1 = 682.8535
ε = 4.65% | Predicted:
F2 = 0.1981
FEA:
F2 = 0.1907
ε = 3.88% | Predicted:
F3 = 4.4641
FEA:
F3 = 4.288
ε = 4.10% | 0.517 |
|
| Case 3 | Hybrid of Taguchi method and fuzzy logic | L1 = 7.7 mm
L3 = 10.1625 mm
D = 2.25 mm | Predicted:
F1 = 158.970
FEA:
F1 = 27.175
ε = 484% | Predicted:
F2 = 0.0957
FEA:
F2 = 0.0443
ε = 116% | Predicted:
F3 = 155.8
FEA:
F2 = 86.112
ε = 80% | 0.496 |
| Proposed hybrid approach of fuzzy-ANFIS-LAPO algorithm | L1 = 6.3793 mm
L3 = 9.73 mm
D = 2.25 mm | Predicted:
F1 = 27.0063
FEA:
F1 = 27.178
ε = 6.31% | Predicted:
F2 = 0.2203
FEA:
F2 = 0.2233
ε = 1.34% | Predicted:
F3 = 332.8096
FEA:
F2 = 343.3
ε = 0.03% | 0.611 |
|
