Modeling of Laser Materials Processing by Artificial Neural Network Modeling and Experimental Validation
Uncertainty is inevitable in problem solving and decision making. One way to reduce it, is by seeking the advice of an expert in related field. On the other hand, when computers are used to reduce uncertainty, the computer itelf can become an expert in a specific field through a variety of methods....
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| Format: | Book |
| Language: | en |
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VDM Publishing, Mauritius
2010
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| Online Access: | http://eprints.utem.edu.my/id/eprint/9231/1/book_3.pdf http://eprints.utem.edu.my/id/eprint/9231/ |
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| _version_ | 1832716393627254784 |
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| author | Sivarao, Subramonian |
| author_facet | Sivarao, Subramonian |
| author_sort | Sivarao, Subramonian |
| building | UTEM Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknikal Malaysia Melaka |
| content_source | UTEM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Uncertainty is inevitable in problem solving and decision making. One way to reduce it, is by seeking the advice of an expert in related field. On the other hand, when computers are used to reduce uncertainty, the computer itelf can become an expert in a specific field through a variety of methods. One such method is machine learning, which involves using a computer algorithm to capture hidden knowledge from data. The researchers conducted the prediction of C02 laser cut quality to obtain singleton output using machine learning techniques. The researchers investigated a problem solving scenario for a metal cutting industry which faces some problems in determining the end quality final part considering several real life machining scenarios with some expert knowledge input from the industry and machine technology features. This large search space poses a challenge for both human experts and machine learning algorithms in achieving the objectives of the industry to reduce the cost of manufacturing by enabling the off hand prediction for laser cut quality to Increase the production quality and rate while significantly reduce the production cost. |
| format | Book |
| id | my.utem.eprints-9231 |
| institution | Universiti Teknikal Malaysia Melaka |
| language | en |
| publishDate | 2010 |
| publisher | VDM Publishing, Mauritius |
| record_format | eprints |
| spelling | my.utem.eprints-92312015-05-28T04:02:33Z http://eprints.utem.edu.my/id/eprint/9231/ Modeling of Laser Materials Processing by Artificial Neural Network Modeling and Experimental Validation Sivarao, Subramonian TJ Mechanical engineering and machinery Uncertainty is inevitable in problem solving and decision making. One way to reduce it, is by seeking the advice of an expert in related field. On the other hand, when computers are used to reduce uncertainty, the computer itelf can become an expert in a specific field through a variety of methods. One such method is machine learning, which involves using a computer algorithm to capture hidden knowledge from data. The researchers conducted the prediction of C02 laser cut quality to obtain singleton output using machine learning techniques. The researchers investigated a problem solving scenario for a metal cutting industry which faces some problems in determining the end quality final part considering several real life machining scenarios with some expert knowledge input from the industry and machine technology features. This large search space poses a challenge for both human experts and machine learning algorithms in achieving the objectives of the industry to reduce the cost of manufacturing by enabling the off hand prediction for laser cut quality to Increase the production quality and rate while significantly reduce the production cost. VDM Publishing, Mauritius 2010 Book PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/9231/1/book_3.pdf Sivarao, Subramonian (2010) Modeling of Laser Materials Processing by Artificial Neural Network Modeling and Experimental Validation. VDM Publishing, Mauritius. ISBN 978-3-639-31529-5 |
| spellingShingle | TJ Mechanical engineering and machinery Sivarao, Subramonian Modeling of Laser Materials Processing by Artificial Neural Network Modeling and Experimental Validation |
| title | Modeling of Laser Materials Processing by Artificial Neural Network Modeling and Experimental Validation |
| title_full | Modeling of Laser Materials Processing by Artificial Neural Network Modeling and Experimental Validation |
| title_fullStr | Modeling of Laser Materials Processing by Artificial Neural Network Modeling and Experimental Validation |
| title_full_unstemmed | Modeling of Laser Materials Processing by Artificial Neural Network Modeling and Experimental Validation |
| title_short | Modeling of Laser Materials Processing by Artificial Neural Network Modeling and Experimental Validation |
| title_sort | modeling of laser materials processing by artificial neural network modeling and experimental validation |
| topic | TJ Mechanical engineering and machinery |
| url | http://eprints.utem.edu.my/id/eprint/9231/1/book_3.pdf http://eprints.utem.edu.my/id/eprint/9231/ |
| url_provider | http://eprints.utem.edu.my/ |