Off-Line Error Recovery Logic Synthesis in Automated Assembly Lines by using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Cem M. Baydar and Kazuhiro Saitou",
  title =        "Off-Line Error Recovery Logic Synthesis in Automated
                 Assembly Lines by using Genetic Programming",
  booktitle =    "Proceedings Of The 2000 Japan/USA Symposium On
                 Flexible Automation",
  year =         "2000",
  editor =       "Steven Y. Liang and Tatsuo Arai",
  address =      "Ann Arbor, MI, USA",
  month =        "23-26 " # jul,
  organisation = "ASME",
  email =        "",
  keywords =     "genetic algorithms, genetic programming, Error
                 Recovery Synthesis, Off-line Programming, Automated
                 Assembly Lines",
  ISBN =         "0-7918-1998-1",
  broken =       "",
  URL =          "",
  size =         "8 pages",
  abstract =     "Unexpected failures are one of the most important
                 problems, which cause costly shutdowns in an assembly
                 line. Generally the recovery process is done by the
                 experts or automated error recovery logic controllers
                 embedded in the system. The previous work in the
                 literature is focused on the on-line recovery of the
                 assembly lines which makes the process, time and money
                 consuming. Therefore a novel approach is necessary
                 which requires less time and hardware effort for the
                 generation of error recovery logic. The proposed
                 approach is based on three-dimensional geometric
                 modelling of the assembly line coupled with the
                 evolutionary computation techniques to generate error
                 recovery logic in an off-line manner. The scope of this
                 work is focused on finding an error recovery algorithm
                 from a predefined error case. An automated assembly
                 line is virtually modeled and the validity of the
                 recovery algorithm is evaluated in a generate and test
                 fashion by using a commercial software package. The
                 obtained results showed that the developed framework is
                 capable of generating recovery algorithms from an
                 arbitrary part positioning error case. It is aimed that
                 this approach will be coupled with the error generation
                 in the future, providing efficient ways for the study
                 of error recovery in automated assembly lines.",
  notes =        "
                 ASME Order #: I464CD",

Genetic Programming entries for Cem M Baydar Kazuhiro Saitou