Incremental recognition of machining features

Jung Hyun Han, Aristides A.G. Requicha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Manufacturing analysis programs that operate in a batch mode are inappropriate for a concurrent engineering environment, in which designers interact with an evolving product model and require rapid feedback on the manufacturing Implications of design actions. This paper discusses a design for an automatic recognizer of machining features that operates incrementally, updating its results efficiently after each design step. The Incremental Feature Finder (IFF) builds upon an earlier, batch recognizer called OOFF, developed at USC in the late 1980s. IFF exploits spatial locality and feature dependency information, stored in a Truth Maintenance System, to improve its performance.

Original languageEnglish
Title of host publicationASME 1994 International Computers in Engineering Conference and Exhibition
PublisherAmerican Society of Mechanical Engineers (ASME)
Pages143-149
Number of pages7
ISBN (Electronic)9780791813805
DOIs
Publication statusPublished - 1994
Externally publishedYes
EventASME 1994 International Computers in Engineering Conference and Exhibition, CIE 1994 and the ASME 1994 8th Annual Database Symposium collocated with the ASME 1994 Design Technical Conferences - Minneapolis, United States
Duration: 1994 Sept 111994 Sept 14

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
VolumePart F168015-2

Conference

ConferenceASME 1994 International Computers in Engineering Conference and Exhibition, CIE 1994 and the ASME 1994 8th Annual Database Symposium collocated with the ASME 1994 Design Technical Conferences
Country/TerritoryUnited States
CityMinneapolis
Period94/9/1194/9/14

ASJC Scopus subject areas

  • Mechanical Engineering
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Modelling and Simulation

Fingerprint

Dive into the research topics of 'Incremental recognition of machining features'. Together they form a unique fingerprint.

Cite this