Off-Line Error Recovery Logic Synthesis in Automated Assembly Lines by using Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{oai:CiteSeerPSU:538284,
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author = "Cem M. Baydar and Kazuhiro Saitou",
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title = "Off-Line Error Recovery Logic Synthesis in Automated
Assembly Lines by using Genetic Programming",
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booktitle = "Proceedings Of The 2000 Japan/USA Symposium On
Flexible Automation",
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year = "2000",
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editor = "Steven Y. Liang and Tatsuo Arai",
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address = "Ann Arbor, MI, USA",
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month = "23-26 " # jul,
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organisation = "ASME",
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email = "kazu@umich.edu",
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keywords = "genetic algorithms, genetic programming, Error
Recovery Synthesis, Off-line Programming, Automated
Assembly Lines",
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ISBN = "0-7918-1998-1",
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broken = "http://www-personal.engin.umich.edu/~cbaydar/japan-usa-00.pdf",
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URL = "http://citeseer.ist.psu.edu/538284.html",
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size = "8 pages",
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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.",
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notes = "http://www.asme.org/divisions/med/enewsletter/2000oct/JapanUSAsymp.html
http://members.asme.org/catalog/ItemView.cfm?ItemNumber=I464CD
ASME Order #: I464CD",
- }
Genetic Programming entries for
Cem M Baydar
Kazuhiro Saitou
Citations