Selection of laser bending process parameters for maximal deformation angle through neural network and teaching-learning-based optimization algorithm
| LEADER | caa a22 4500 | ||
|---|---|---|---|
| 001 | 605469504 | ||
| 003 | CHVBK | ||
| 005 | 20210128100322.0 | ||
| 007 | cr unu---uuuuu | ||
| 008 | 210128e20150301xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s00500-014-1282-0 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00500-014-1282-0 | ||
| 245 | 0 | 0 | |a Selection of laser bending process parameters for maximal deformation angle through neural network and teaching-learning-based optimization algorithm |h [Elektronische Daten] |c [Mahyar Omidvar, Reza Fard, Hamed Sohrabpoor, Reza Teimouri] |
| 520 | 3 | |a The present study focused on selecting optimal factors combination that causes maximum bending angle in laser bending of AA6061-T6. For this purpose a L $$_{25}$$ 25 Taguchi orthogonal design (four factors-five levels) is used to design experiments. Here, the process main factors are laser power, spot diameter, pulse duration and scanning speed and the main response was bending angle. To correlate relationship between process factors and bending angle, a radial basis function neural network (RBFNN) was utilized. Then the developed RBFNN model was used as an objective function for maximizing deformation through teaching-learning-based optimization algorithm. Results indicated that the laser power of 3.6kW, spot diameter of 2 mm, pulse duration of 0.9 ms and scanning speed of 2 mm/s lead to maximal bending angle about 28.7 $$^\circ $$ ∘ . Hereafter the optimal results have been verified by confirmatory experiments. | |
| 540 | |a Springer-Verlag Berlin Heidelberg, 2014 | ||
| 690 | 7 | |a Laser bending |2 nationallicence | |
| 690 | 7 | |a L $$_{25}$$ 25 Taguchi design |2 nationallicence | |
| 690 | 7 | |a Radial basis network |2 nationallicence | |
| 690 | 7 | |a Teaching-learning-based optimization algorithm |2 nationallicence | |
| 700 | 1 | |a Omidvar |D Mahyar |u Golpayegan Shohada University of Engineering and Technology, Golpayegan, Iran |4 aut | |
| 700 | 1 | |a Fard |D Reza |u Department of Mechanical Engineering, Islamic Azad University, Kordestan Branch of Science and Research, Sanandaj, Iran |4 aut | |
| 700 | 1 | |a Sohrabpoor |D Hamed |u Department of Mechanical Engineering, Islamic Azad University, Dezfull Branch, Dezful, Iran |4 aut | |
| 700 | 1 | |a Teimouri |D Reza |u Department of Mechanical Engineering, Babol University of Technology, Babol, Iran |4 aut | |
| 773 | 0 | |t Soft Computing |d Springer Berlin Heidelberg |g 19/3(2015-03-01), 609-620 |x 1432-7643 |q 19:3<609 |1 2015 |2 19 |o 500 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00500-014-1282-0 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s00500-014-1282-0 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Omidvar |D Mahyar |u Golpayegan Shohada University of Engineering and Technology, Golpayegan, Iran |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Fard |D Reza |u Department of Mechanical Engineering, Islamic Azad University, Kordestan Branch of Science and Research, Sanandaj, Iran |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Sohrabpoor |D Hamed |u Department of Mechanical Engineering, Islamic Azad University, Dezfull Branch, Dezful, Iran |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Teimouri |D Reza |u Department of Mechanical Engineering, Babol University of Technology, Babol, Iran |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Soft Computing |d Springer Berlin Heidelberg |g 19/3(2015-03-01), 609-620 |x 1432-7643 |q 19:3<609 |1 2015 |2 19 |o 500 | ||