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.
Reference:
Xing, B, Nelwamondo, FV et al 2009. Application of artificial intelligence (AI) methods for designing and analysis of reconfigurable cellular manufacturing system (RCMS). 2nd International Conference on Adaptive Science & Technology (ICAST 2009), Accra, Ghana, 14-16 December 2009, pp 402-409
Xing, B., Nelwamondo, F. V., Battle, K., Gao, W., & Marwala, T. (2009). Application of artificial intelligence (AI) methods for designing and analysis of reconfigurable cellular manufacturing system (RCMS). IEEE. http://hdl.handle.net/10204/4002
Xing, B, Fulufhelo V Nelwamondo, K Battle, W Gao, and T Marwala. "Application of artificial intelligence (AI) methods for designing and analysis of reconfigurable cellular manufacturing system (RCMS)." (2009): http://hdl.handle.net/10204/4002
Xing B, Nelwamondo FV, Battle K, Gao W, Marwala T, Application of artificial intelligence (AI) methods for designing and analysis of reconfigurable cellular manufacturing system (RCMS); IEEE; 2009. http://hdl.handle.net/10204/4002 .
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