DocumentCode :
3416770
Title :
Application of artificial intelligence (AI) methods for designing and analysis of reconfigurable cellular manufacturing system (RCMS)
Author :
Xing, Bo ; Nelwamondo, Fulufhelo V. ; Battle, Kimberly ; Gao, Wenjing ; Marwala, Tshilidzi
Author_Institution :
Fac. of Eng. & the Built Environ., Univ. of Johannesburg, Johannesburg, South Africa
fYear :
2009
fDate :
14-16 Jan. 2009
Firstpage :
402
Lastpage :
409
Abstract :
This work focuses on the design and control of a novel hybrid manufacturing system: reconfigurable cellular manufacturing system (RCMS) by using artificial intelligence (AI) approach. It is hybrid as it combines the advantages of cellular manufacturing system (CMS) and reconfigurable manufacturing system (RMS). In addition to inheriting desirable properties from CMS and RMS, RCMS provides additional benefits including flexibility and the ability to respond to changing products, product mix and market conditions during its useful life, avoiding premature obsolescence of the manufacturing system. The emphasis of this research is the formation of reconfigurable manufacturing cell (RMC) which is the dynamic and logical clustering of some manufacturing resources, driven by specific customer orders, aiming at optimally fulfilling customers´ orders along with other RMCs in the RCMS.
Keywords :
artificial intelligence; cellular manufacturing; pattern clustering; production engineering computing; artificial intelligence method; cellular manufacturing system; dynamic clustering; logical clustering; reconfigurable manufacturing system; Artificial intelligence; Cellular manufacturing; Collision mitigation; Design methodology; Machinery production industries; Manufacturing industries; Manufacturing systems; Mass production; Productivity; Virtual manufacturing; AI; ANN; RCMS; RMC;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Adaptive Science & Technology, 2009. ICAST 2009. 2nd International Conference on
Conference_Location :
Accra
ISSN :
0855-8906
Print_ISBN :
978-1-4244-3522-7
Electronic_ISBN :
0855-8906
Type :
conf
DOI :
10.1109/ICASTECH.2009.5409694
Filename :
5409694
Link To Document :
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