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From computer-aided to intelligent machining: Recent advances in computer numerical control machining research

From computer-aided to intelligent machining: Recent advances in computer numerical control machining research

Gao, James, Lee, Chen-Han and Li, Yingguagan (2015) From computer-aided to intelligent machining: Recent advances in computer numerical control machining research. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 229 (7). pp. 1087-1103. ISSN 0954-4054 (Print), 2041-2975 (Online) (doi:10.1177/0954405414560622)

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Abstract

The aim of this paper is to provide an introduction and overview of recent advances in the key technologies and the supporting computerized systems, and to indicate the trend of research and development in the area of computational numerical control machining. Three main themes of recent research in CNC machining are simulation, optimization and automation, which form the key aspects of intelligent manufacturing in the digital and knowledge based manufacturing era. As the information and knowledge carrier, feature is the efficacious way to achieve intelligent manufacturing. From the regular shaped feature to freeform surface feature, the feature technology has been used in manufacturing of complex parts, such as aircraft structural parts. The authors’ latest research in intelligent machining is presented through a new concept of multi-perspective dynamic feature (MpDF), for future discussion and communication with readers of this special issue. The MpDF concept has been implemented and tested in real examples from the aerospace industry, and has the potential to make promising impact on the future research in the new paradigm of intelligent machining. The authors of this paper are the guest editors of this special issue on computational numerical control machining. The guest editors have extensive and complementary experiences in both academia and industry, gained in China, USA and UK.

Item Type: Article
Uncontrolled Keywords: Digital manufacturing, Optimisation, Process modeling and planning, CNC machining, Feature
Faculty / Department / Research Group: Faculty of Engineering & Science
Last Modified: 14 Oct 2016 09:30
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/12832

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