Manufacturing feature recognition from solid models: A status report

Jung Hyun Han, Mike Pratt, William C. Regli

Research output: Contribution to journalArticle

209 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)782-796
Number of pages15
JournalIEEE Transactions on Robotics and Automation
Volume16
Issue number6
DOIs
Publication statusPublished - 2000 Dec 1

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ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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