DocumentCode :
2905458
Title :
Research on Manufacturing Resource Discovery Based on Ontology and QoS in Manufacturing Grid
Author :
He Yu´an ; Tao, Yu ; Lilan, Liu ; Haiyang, Sun
Author_Institution :
Cims & Robot Center, Shanghai Univ.
fYear :
2006
fDate :
Nov. 2006
Firstpage :
209
Lastpage :
215
Abstract :
The core of manufacturing grid (MG) is manufacturing resource (MR) sharing and collaboration, so the efficient discovery of sharable MRs is the precondition and basis that the resource sharing, collaborative design and manufacturing can be realized successfully in MG. Aiming at the problem that semantic information is represented insufficiently when MRs are searched in MG, we propose an ontology-based MR discovery architecture which is based on semantic Web technology. Then from the point of view based on semantics and QoS (quality of service), the main framework of resource matchmaking is constructed, in which three processes are included: task modeling, resource modeling, semantic modeling and resource matchmaking. On the basis of resource representation model and manufacturing features-oriented task representation model, combining with the research results of semantic Web, some pivotal concepts are defined about the matchmaking resources. Finally, by means of a functional semantic extending method based on the ontology and QoS, the MR matchmaking algorithm is constructed
Keywords :
grid computing; manufacturing data processing; ontologies (artificial intelligence); semantic Web; collaborative design; manufacturing grid; manufacturing resource discovery; ontology; quality of service; resource sharing; semantic Web; semantic information; Artificial intelligence; Collaboration; Costs; Manufacturing; Ontologies; Prototypes; Quality of service; Resource management; Semantic Web; Silver;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cyberworlds, 2006. CW '06. International Conference on
Conference_Location :
Lausanne
Print_ISBN :
0-7695-2671-3
Type :
conf
DOI :
10.1109/CW.2006.32
Filename :
4030847
Link To Document :
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