DocumentCode :
1235046
Title :
Virtual assembly with biologically inspired intelligence
Author :
Yuan, Xiaobu ; Yang, Simon X.
Author_Institution :
Sch. of Comput. Sci., Windsor Univ., Ont., Canada
Volume :
33
Issue :
2
fYear :
2003
fDate :
5/1/2003 12:00:00 AM
Firstpage :
159
Lastpage :
167
Abstract :
This paper investigates the introduction of biologically inspired intelligence into virtual assembly. It develops a approach to assist product engineers making assembly-related manufacturing decisions without actually realizing the physical products. This approach extracts the knowledge of mechanical assembly by allowing human operators to perform assembly operations directly in the virtual environment. The incorporation of a biologically inspired neural network into an interactive assembly planner further leads to the improvement of flexible product manufacturing, i.e., automatically producing alternative assembly sequences with robot-level instructions for evaluation and optimization. Complexity analysis and simulation study demonstrate the effectiveness and efficiency of this approach.
Keywords :
assembly planning; digital simulation; industrial robots; interactive systems; knowledge acquisition; knowledge based systems; neural nets; optimisation; production engineering computing; alternative assembly sequences; assembly-related manufacturing decisions; biologically inspired intelligence; biologically inspired neural network; complexity analysis; flexible product manufacturing; interactive assembly planner; knowledge extraction; mechanical assembly; optimization; product engineers; robot-level instructions; virtual assembly; Biological system modeling; Humans; Intelligent robots; Manipulators; Manufacturing automation; Neural networks; Robot programming; Robotic assembly; Robotics and automation; Virtual reality;
fLanguage :
English
Journal_Title :
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
Publisher :
ieee
ISSN :
1094-6977
Type :
jour
DOI :
10.1109/TSMCC.2003.813149
Filename :
1211123
Link To Document :
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