Multiple-parameter optimization for CNC machining via machine learning

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外文摘要：Computer-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, tool sizes, etc. in order to achieve 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.

外文关键词：

CAD/CAMCNC machiningmachining performancemultiple-parameter optimizationmachine learning

作者：

M K YEUNG、Z GUI、Y ZHANG

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作者单位：

Integrated Manufacturing Technologies Institute, National Research Council, Canada

会议名称：

Manufacturing Automation: Advanced Design and Manufacturing in Global Competition

会议地点：

Wuhan(CN)

会议母体文献：

International Conference on Manufacturing Automation: Advanced Design and Manufacturing in Global Competition(ICMA 2004); 20041026-29; Wuhan(CN)

页码：

P.331-338

出版时间：

2004