The field of solid modeling has developed a variety of techniques for unambiguous representations of three-dimensional objects. Feature recognition is a sub-discipline of solid modeling that focuses on the design and implementation of algorithms for detecting manufacturing information from solid models produced by computer-aided design (CAD) systems. Examples of this manufacturing information include features such as holes, slots, pockets and other shapes that can be created on modern computer numerically controlled machining systems. Automated feature recognition has been an active research area in solid modeling for many years and is considered to be a critical component for integration of CAD and computer-aided manufacturing. This paper gives an overview of the state-of-the-art in feature recognition research. Rather than giving an exhaustive survey, we focus on the three of the major algorithmic approaches for feature recognition: 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 open research and development issues.
Bibliographical noteFunding Information:
Manuscript received January 30, 1998; revised May 12, 1999, March 13, 2000, and August 30, 2000. This paper was recommended for publication by Associate Editor M. Y. Wang and Editor N. Viswanadham upon evaluation of the reviewers’ comments. The work of J. Han was supported in part by the Korea Science and Engineering Foundation’s Basic Research Program under Grant 1999-2-515-001-5. The work of W. Regli was supported in part by the National Science Foundation (NSF) CAREER Award CISE/IIS-9 733 545 and Grant ENG/DMI-9 713 718. This work was supported in part by the National Institute of Standards and Technology (NIST) under Grant 60NANB7D0092.
ASJC Scopus subject areas
- Control and Systems Engineering
- Electrical and Electronic Engineering