DocumentCode :
2974894
Title :
A multi-agent model for the order driven agile manufacturing systems and order form selection algorithm
Author :
Zhao, Fuqing ; Zhang, Qiuyu ; Yang, Yahong
Author_Institution :
Sch. of Comput. & Commun., Lanzhou Univ. of Technol., Lanzhou, China
fYear :
2009
fDate :
22-24 June 2009
Firstpage :
1625
Lastpage :
1630
Abstract :
The manufacturing industry is entering a stage of change which is driven by the competitive environment of continuous and unpredictable events. Efficient and effective manufacturing enterprise organization methods are highly desired to be responsive to the physical and software disturbances. A multi-agent model for the order driven agile manufacturing systems and order form selection algorithm are provided in this paper. The information of component agent and detailed schedule plan in the architecture are presented. Shop floor activity and its corresponding control flow are given to support the interaction for the agent community. Particle swarm optimization (PSO) algorithm for the order form selection for the order driven system is used to intelligently select the suitable order for the system. Simulation results show that the architecture model and its optimization algorithm are effective to the problem.
Keywords :
agile manufacturing; multi-agent systems; particle swarm optimisation; production engineering computing; PSO algorithm; component agent; detailed schedule plan; manufacturing enterprise organization method; manufacturing industry; multiagent model; order driven agile manufacturing system; order form selection algorithm; particle swarm optimization algorithm; shop floor activity; Agile manufacturing; Bills of materials; Computer architecture; Control systems; Job shop scheduling; Manufacturing automation; Manufacturing industries; Manufacturing systems; Multiagent systems; Production systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Automation, 2009. ICIA '09. International Conference on
Conference_Location :
Zhuhai, Macau
Print_ISBN :
978-1-4244-3607-1
Electronic_ISBN :
978-1-4244-3608-8
Type :
conf
DOI :
10.1109/ICINFA.2009.5205177
Filename :
5205177
Link To Document :
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