Artificial intelligence device and corresponding methods for selecting machinability data.
The present invention describes a device incorporating artificial intelligence and corresponding methods for recommending an optimal machinability data selection. The device comprises of a first component, which feeds the system with necessary input. A second component which is the main processing u...
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my.upm.eprints.208802015-04-28T12:14:52Z http://psasir.upm.edu.my/id/eprint/20880/ Artificial intelligence device and corresponding methods for selecting machinability data. Wong, Shaw Voon Hamouda, Abdel Magid S. The present invention describes a device incorporating artificial intelligence and corresponding methods for recommending an optimal machinability data selection. The device comprises of a first component, which feeds the system with necessary input. A second component which is the main processing unit, acts as an inference engine to predict the outputs. The last component interprets the outputs, conveys the processed outputs to target location and converts them into necessary task. The inputs are identified as the machining operation, work piece material, machining tool type, and depth of cut. The outputs are the machining parameters, comprising of the optimal cutting speed and feed rate. The inference engine can be established with fuzzy logic, neural network of fuzzy-neural network. 2010-03-15 Patent NonPeerReviewed Wong Shaw Voon (2010) Artificial intelligence device and corresponding methods for selecting machinability data. PI20024308. |
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The present invention describes a device incorporating artificial intelligence and corresponding methods for recommending an optimal machinability data selection. The device comprises of a first component, which feeds the system with necessary input. A second component which is the main processing unit, acts as an inference engine to predict the outputs. The last component interprets the outputs, conveys the processed outputs to target location and converts them into necessary task. The inputs are identified as the machining operation, work piece material, machining tool type, and depth of cut. The outputs are the machining parameters, comprising of the optimal cutting speed and feed rate. The inference engine can be established with fuzzy logic, neural network of fuzzy-neural network.
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format |
Patent |
author |
Wong, Shaw Voon Hamouda, Abdel Magid S. |
spellingShingle |
Wong, Shaw Voon Hamouda, Abdel Magid S. Artificial intelligence device and corresponding methods for selecting machinability data. |
author_facet |
Wong, Shaw Voon Hamouda, Abdel Magid S. |
author_sort |
Wong, Shaw Voon |
title |
Artificial intelligence device and corresponding methods for selecting machinability data.
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title_short |
Artificial intelligence device and corresponding methods for selecting machinability data.
|
title_full |
Artificial intelligence device and corresponding methods for selecting machinability data.
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title_fullStr |
Artificial intelligence device and corresponding methods for selecting machinability data.
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title_full_unstemmed |
Artificial intelligence device and corresponding methods for selecting machinability data.
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title_sort |
artificial intelligence device and corresponding methods for selecting machinability data. |
publishDate |
2010 |
url |
http://psasir.upm.edu.my/id/eprint/20880/ |
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1643827415092297728 |
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13.18916 |