Parametric optimization of Nd:YAG laser microgrooving on aluminum oxide using integrated RSM-ANN-GA approach
Abstract Nowadays in highly competitive precision industries, the micromachining of advanced engineering materials is extremely demand as it has extensive application in the fields of automobile, electronic, biomedical and aerospace engineering. The present work addresses the modeling and optimizati...
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| Format: | Article |
| Language: | English |
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Islamic Azad University
2018-10-01
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| Series: | Journal of Industrial Engineering International |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1007/s40092-018-0295-1 |
| _version_ | 1818720012362317824 |
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| author | Salila Ranjan Dixit Sudhansu Ranjan Das Debabrata Dhupal |
| author_facet | Salila Ranjan Dixit Sudhansu Ranjan Das Debabrata Dhupal |
| author_sort | Salila Ranjan Dixit |
| collection | DOAJ |
| description | Abstract Nowadays in highly competitive precision industries, the micromachining of advanced engineering materials is extremely demand as it has extensive application in the fields of automobile, electronic, biomedical and aerospace engineering. The present work addresses the modeling and optimization study on dimensional deviations of square-shaped microgroove in laser micromachining of aluminum oxide (Al2O3) ceramic material with pulsed Nd:YAG laser by considering the air pressure, lamp current, pulse frequency, pulse width and cutting speed as process parameters. Thirty-two sets of laser microgrooving trials based on central composite design (CCD) design of experiments (DOEs) are performed, and response surface method (RSM), artificial neural network (ANN) and genetic algorithm (GA) are subsequently applied for mathematical modeling and multi-response optimization. The performance of the predictive ANN model based on 5-8-8-3 architecture gave the minimum error (MSE = 0.000099) and presented highly promising to confidence with percentage error less than 3% in comparison with experimental result data set. The ANN model combined with GA leads to minimum deviation of upper width, lower width and depth value of − 0.0278 mm, 0.0102 mm and − 0.0308 mm, respectively, corresponding to optimum laser microgrooving process parameters such as 1.2 kgf/cm2 of air pressure, 19.5 Amp of lamp current, 4 kHz of pulse frequency, 6% of pulse width and 24 mm/s of cutting speed. Finally, the results have been verified by performing a confirmatory test. |
| first_indexed | 2024-12-17T20:16:04Z |
| format | Article |
| id | doaj.art-efeca9d7905d4bfc9733bca449800acd |
| institution | Directory Open Access Journal |
| issn | 1735-5702 2251-712X |
| language | English |
| last_indexed | 2024-12-17T20:16:04Z |
| publishDate | 2018-10-01 |
| publisher | Islamic Azad University |
| record_format | Article |
| series | Journal of Industrial Engineering International |
| spelling | doaj.art-efeca9d7905d4bfc9733bca449800acd2022-12-21T21:34:07ZengIslamic Azad UniversityJournal of Industrial Engineering International1735-57022251-712X2018-10-0115233334910.1007/s40092-018-0295-1Parametric optimization of Nd:YAG laser microgrooving on aluminum oxide using integrated RSM-ANN-GA approachSalila Ranjan Dixit0Sudhansu Ranjan Das1Debabrata Dhupal2Department of Production Engineering, Veer Surendra Sai University of TechnologyDepartment of Production Engineering, Veer Surendra Sai University of TechnologyDepartment of Production Engineering, Veer Surendra Sai University of TechnologyAbstract Nowadays in highly competitive precision industries, the micromachining of advanced engineering materials is extremely demand as it has extensive application in the fields of automobile, electronic, biomedical and aerospace engineering. The present work addresses the modeling and optimization study on dimensional deviations of square-shaped microgroove in laser micromachining of aluminum oxide (Al2O3) ceramic material with pulsed Nd:YAG laser by considering the air pressure, lamp current, pulse frequency, pulse width and cutting speed as process parameters. Thirty-two sets of laser microgrooving trials based on central composite design (CCD) design of experiments (DOEs) are performed, and response surface method (RSM), artificial neural network (ANN) and genetic algorithm (GA) are subsequently applied for mathematical modeling and multi-response optimization. The performance of the predictive ANN model based on 5-8-8-3 architecture gave the minimum error (MSE = 0.000099) and presented highly promising to confidence with percentage error less than 3% in comparison with experimental result data set. The ANN model combined with GA leads to minimum deviation of upper width, lower width and depth value of − 0.0278 mm, 0.0102 mm and − 0.0308 mm, respectively, corresponding to optimum laser microgrooving process parameters such as 1.2 kgf/cm2 of air pressure, 19.5 Amp of lamp current, 4 kHz of pulse frequency, 6% of pulse width and 24 mm/s of cutting speed. Finally, the results have been verified by performing a confirmatory test.http://link.springer.com/article/10.1007/s40092-018-0295-1Laser microgroovingAluminum oxideRSMANNGA |
| spellingShingle | Salila Ranjan Dixit Sudhansu Ranjan Das Debabrata Dhupal Parametric optimization of Nd:YAG laser microgrooving on aluminum oxide using integrated RSM-ANN-GA approach Journal of Industrial Engineering International Laser microgrooving Aluminum oxide RSM ANN GA |
| title | Parametric optimization of Nd:YAG laser microgrooving on aluminum oxide using integrated RSM-ANN-GA approach |
| title_full | Parametric optimization of Nd:YAG laser microgrooving on aluminum oxide using integrated RSM-ANN-GA approach |
| title_fullStr | Parametric optimization of Nd:YAG laser microgrooving on aluminum oxide using integrated RSM-ANN-GA approach |
| title_full_unstemmed | Parametric optimization of Nd:YAG laser microgrooving on aluminum oxide using integrated RSM-ANN-GA approach |
| title_short | Parametric optimization of Nd:YAG laser microgrooving on aluminum oxide using integrated RSM-ANN-GA approach |
| title_sort | parametric optimization of nd yag laser microgrooving on aluminum oxide using integrated rsm ann ga approach |
| topic | Laser microgrooving Aluminum oxide RSM ANN GA |
| url | http://link.springer.com/article/10.1007/s40092-018-0295-1 |
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