| Author | Search for: Yeung, Millan K.1; Search for: Gui, Zhonghua1; Search for: Zhang, Y.F. |
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| Affiliation | - National Research Council of Canada. NRC Industrial Materials Institute
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| Format | Text, Article |
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| Conference | International Conference on Manufacturing Automation, October 26-29 2004, Wuhan, Hubei, China |
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| Subject | CAD/CAM; CNC machining; machining performance; multiple-parameter optimization; machine learning |
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| Abstract | Computed-aided design / computer-aided manufacturing (CAD/CAM) and computerized numerical control (CNC) machining are among the most efficient and commonly used processes by the manufacturing industry. Extensive research and development has been conducted and continuously ongoing in this important area to improve quality of the machined part and to reduce the cycle time. The research generated extensive knowledge on machining and often focused on specific goal and objective. A recent development of an intelligent process planning system for CNC programming identified the need of multiple-parameter optimization for controlling different factors of CNC machining such as feeds, speeds, tools sizes, etc. in order to achieve a good surface finishing, low tool load, fast cycle time and other machining goals. This paper describes a method based on the machine learning approach for the optimization of multiple-parameter CNC machining. |
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| Publication date | 2004-12-27 |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| NPARC number | 21272548 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | ae7fe23a-7f15-4dfc-8f81-187494c65b30 |
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| Record created | 2014-12-02 |
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| Record modified | 2020-04-17 |
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