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PLEASE NOTE: The Publications System provided by the Manufacturing Systems Integration Division (MSID) has moved to: http://www.mel.nist.gov/msidlibrary/publications.html. The pages below are maintained for archival purposes only.
Publication summary
Author(s): Jung-Hyun Han, Mike Pratt and William Regli
Publication date: June 2000
Citation: Jung-Hyun Han, Mike Pratt and William Regli: "Manufacturing Feature Recognition from Solid Models: A Status Report," IEEE Trans. on Robotics and Automation (2000), June, 2000.
Key words: solid models, manufacturing feature recognition
Availability:
- A paper copy of this document is available by contacting Kristy Thompson [web,email]
Abstract:
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Solid modeling refers to techniques for unambiguous representations of
three-dimensional objects. Feature recognition is a sub-discipline focusing
on the design and implementation of algorithms for detecting manufacturing
information such as holes, slots, etc. in a solid model. Automated feature
recognition has been an active research area in solid modeling for many
years, and is considered to be a critical component for CAD/CAM integration.
This paper gives a technical overview of the state of the art in feature
recognition research. Rather than giving an exhaustive survey, we focus on
the three currently dominant feature recognition technologies: graph-based
algorithms, volumetric decomposition techniques and hint-based geometric
reasoning. For each approach, we present a detailed description of the
algorithms being employed along with some assessments of the technology. We
conclude by outlining important research and development issues.
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