A Rough Set Based Knowledge Discovery Model and its Application in Virtual Assembly

Abstract:

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To solve the problem of lack of assemble knowledge in ship virtual assembly system, a novel rough-set theory based knowledge discovery model is studied to find the process knowledge hidden in virtual assembly. First the typical knowledge structure used in ship virtual assembly is analyzed and improved into a generalized definition using the object-oriented technology. The technology solution to develop knowledge discovery model for ship virtual assembly is proposed based on rough set theory. All the key technologies such as Petri-RS information transformation model, RS attribute reduction and knowledge management technologies are analyzed respectively for real engineering application. The developed knowledge discovery system of the ship virtual assembly can realize the data processing and mining, to discover useful assembly knowledge automatically. Further with an engineering example from virtual assembly in shipbuilding enterprises, this paper provides a technical solution to disvover useful assembly knowlege, reduce assembly time for ship building in real product line, to enhance production efficiency obviously.

Info:

Periodical:

Advanced Materials Research (Volumes 314-316)

Edited by:

Jian Gao

Pages:

2132-2139

DOI:

10.4028/www.scientific.net/AMR.314-316.2132

Citation:

C. L. Li and R. Y. Zhao, "A Rough Set Based Knowledge Discovery Model and its Application in Virtual Assembly", Advanced Materials Research, Vols. 314-316, pp. 2132-2139, 2011

Online since:

August 2011

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Price:

$35.00

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