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A prototype of feature-based design for assembly

  • T. L. De Fazio
  • A. C. Edsall
  • R. E. Gustavson
  • J. A. Hernandez
  • P. M. Hutchins
  • H. -W. Leung
  • S. C. Luby
  • R. W. Metzinger
  • J. L. Nevins
  • K. K. Tung
  • D. E. Whitney
Design Methods
Part of the Lecture Notes in Computer Science book series (LNCS, volume 492)

Abstract

This paper describes a prototype software system that implements a form of feature-based design for assembly. It is not an automated design system but instead a decision and design aid for designers interested in Concurrent Design. Feature-based design captures design intent (assembly topology, product function, manufacturing, or field use) while creating part and product geometry. Design for assembly as used here extends existing ideas about critiquing part shapes and part count to include assembly process planning, assembly sequence generation, assembly fixturing assessments, and assembly process costs. This work was primarily interested in identifying the information important to DFA tasks, and how that information could be captured using feature-based design. It was not intended to extend the state of the art in feature-based geometry creation, but rather to explore the uses of the information that can be captured. The prototype system has been programmed in LISP on Sun workstations. Its research contributions comprise integration of feature-based design with several existing and new assembly analysis and synthesis algorithms; construction of feature properties to meet the needs of those algorithms; a carefully chosen division of labor between designer and computer; and illustration of feature-based models of products as the information source for assembly analysis and process design. Some of its functions have been implemented approximately or partially but they give the flavor of the benefits to be expected from a fully functional system.

Keywords

Assembly Sequence Automate Design System Assembly Plan Assembly Constraint Assembly Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1991

Authors and Affiliations

  • T. L. De Fazio
    • 1
  • A. C. Edsall
    • 1
  • R. E. Gustavson
    • 1
  • J. A. Hernandez
    • 1
  • P. M. Hutchins
    • 1
  • H. -W. Leung
    • 1
  • S. C. Luby
    • 1
  • R. W. Metzinger
    • 1
  • J. L. Nevins
    • 1
  • K. K. Tung
    • 1
  • D. E. Whitney
    • 1
  1. 1.The Charles Stark Draper Laboratory, Inc.Cambridge

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