• DocumentCode
    299954
  • Title

    Assembly planning using case adaptation methods

  • Author

    Pu, Pearl ; Purvis, Lisa

  • Author_Institution
    Lab. d´´Intelligence Artificielle & Robotique, Swiss Federal Inst. of Technol., Lausanne, Switzerland
  • Volume
    1
  • fYear
    1995
  • fDate
    21-27 May 1995
  • Firstpage
    982
  • Abstract
    In our previous paper, we have shown that case-based reasoning (CBR) techniques can be used as a viable formulation for solving assembly sequence generation problems. The issues covered in that paper were case base organization, case selection and matching, and case indexing. The part on case adaptation was not addressed in a formal way to allow satisfactory generalization of the method to a large class of assembly planning problems. We present in this paper a methodology which formalizes the adaptation process of CBR using constraint satisfaction techniques. Combining CBR with constraint satisfaction provides a generalized formalism for assembly planning problem solving
  • Keywords
    adaptive systems; assembling; case-based reasoning; planning (artificial intelligence); problem solving; production control; assembly planning; case adaptation methods; case-based reasoning; constraint satisfaction; generalized formalism; problem solving; Assembly systems; Computer aided software engineering; Computer science; Indexing; OFDM modulation; Paper technology; Problem-solving; Robotic assembly; Search problems; Storms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation, 1995. Proceedings., 1995 IEEE International Conference on
  • Conference_Location
    Nagoya
  • ISSN
    1050-4729
  • Print_ISBN
    0-7803-1965-6
  • Type

    conf

  • DOI
    10.1109/ROBOT.1995.525410
  • Filename
    525410