DocumentCode :
3211506
Title :
A Data Mining Framework Oriented CIM for Cooperative Manufacturing
Author :
Dechang Pi ; Fenglin Zhang ; Ningsheng Wang ; Xiaolin Qin
Author_Institution :
Coll. of Inf. Sci. & Technol., Nanjing Univ. of Aeronaut. & Astronaut., China
fYear :
2006
fDate :
7-11 Aug. 2006
Firstpage :
1357
Lastpage :
1362
Abstract :
This paper firstly analyzes the reason why data mining should be implemented in CIM (computer integrated manufacturing) system. Secondly current developments about data mining frameworks are introduced. CIMSMiner is a framework for cooperative manufacturing, which combines the practical requirements of CIM system with the new evolution of data mining. The logical architecture, system objectives and system architectures are described in detail respectively. Its logical architecture includes data obtaining layer, data storing layer and data mining layer. The system architecture is based on C/S. The server is mainly composed of data pumping engine, data warehouse and meta-database, and the client mainly includes algorithms tools set, algorithms primitives and data warehouse manager. CIMSMiner supports many novel algorithms, such as evolving association rule and multi-group genetic algorithm. CIMSMiner may promote CIM system development to the future intelligent CIM system that has the decision support ability.
Keywords :
client-server systems; computer integrated manufacturing; data mining; data warehouses; manufacturing systems; CIMSMiner; computer integrated manufacturing system; cooperative manufacturing; data mining layer; data obtaining layer; data pumping engine; data storing layer; data warehouse; evolving association rule; logical architecture; metadatabase; multigroup genetic algorithm; system architecture; system objective; Algorithm design and analysis; Companies; Computer architecture; Computer integrated manufacturing; Data mining; Data warehouses; Databases; Educational institutions; Forward contracts; Information science; CIM System; Computer Integrated Manufacturing; Data Mining; Knowledge Discovery;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference, 2006. CCC 2006. Chinese
Conference_Location :
Harbin
Print_ISBN :
7-81077-802-1
Type :
conf
DOI :
10.1109/CHICC.2006.280674
Filename :
4060306
Link To Document :
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