DocumentCode
3172438
Title
Edwards-Venn Diagrams for knowledge representation and reasoning in industrial systems
Author
Dvoryanchikova, A. ; Lobov, A. ; Capanji, A. ; Lastra, J. L Martinez
Author_Institution
Dept. of Production Eng., Tampere Univ. of Technol., Tampere, Finland
fYear
2010
fDate
13-16 Sept. 2010
Firstpage
1
Lastpage
7
Abstract
Edwards-Venn Diagrams (EVD) were introduced to facilitate knowledge representation and reasoning in connectionistic approach for modeling industrial systems. Semantic descriptions are seen helpful in solving the challenges of mass customization due to capability to capture knowledge interpretable both for humans and machines. However modern knowledge technologies could not provide required flexibility in expressing the semantics of dynamical nature of events and processes which are essential for industrial systems. This motivates further research for flexible yet formal tools for knowledge representation and reasoning. In order to provide flexible semantic descriptions to dynamic qualities of industrial systems, a connectionistic knowledge model - connectionistic concept grid (CCG) - was introduced, which was inspired by natural knowledge structure derived from connectionism approach to natural cognition. EVD were found useful to represent relations among different sets of concepts in CCG and to provide structural reasoning in the models.
Keywords
cognition; diagrams; inference mechanisms; knowledge representation; mass production; product customisation; Edwards-Venn diagram; connectionistic concept grid; connectionistic knowledge model; formal tool; industrial system; knowledge representation; mass customization; modern knowledge technology; natural cognition; natural knowledge structure; semantic description; structural reasoning;
fLanguage
English
Publisher
ieee
Conference_Titel
Emerging Technologies and Factory Automation (ETFA), 2010 IEEE Conference on
Conference_Location
Bilbao
ISSN
1946-0740
Print_ISBN
978-1-4244-6848-5
Type
conf
DOI
10.1109/ETFA.2010.5641281
Filename
5641281
Link To Document