A Machine Learning Approach for Uncertainty Management in Optimal Disassembly Planning


A Machine Learning Approach for Uncertainty Management in Optimal Disassembly Planning

Dra. Ying (Gina) Tang

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With the vast amounts of environmental waste being created on a daily basis, many companies are trying to find ways to optimally reuse and recycle obsolete products. Due to tedious and intensive nature of optimal disassembly planning, expert systems which ease the decision making process are becoming much more prevalent. This paper discusses one such system where a machine learning approach based on a Disassembly Petri net (DPN) and a Hybrid Bayesian network (HBN) is used. In particular, this method models the disassembly process and predicts the outcome of each disassembly action by examining the probabilistic relationships between the different aspects of the disassembly process. An overall view of the disassembly process and a simple, specific case are provided to illustrate the operation of this expert system.



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Ying (Gina) Tang (S'99-M'02-SM'07) received the B.S. and M.S. degrees from the Northeastern University, P. R. China, in 1996 and 1998, respectively, and Ph. D degree from New Jersey Institute of Technology in 2001. She is an Associate Professor of Electrical and Computer Engineering at Rowan University, Glassboro, New Jersey. Her current research interests include modeling and adaptive control for Computer-integrated Systems and Robotics, Petri Nets, computational intelligence, healthcare management, and systems-on-chip. Dr. Tang has led or participated in several research and education projects funded by National Science Foundation, US Department of Transportation, US Navy, the Charles A. and Anne Morrow Lindbergh Foundation, the Christian R. and Mary F. Lindback Foundation and industry firms. Her work has resulted in over 60 journal and conference proceedings articles. 

She is currently Associate Editor of International Journal of Intelligent Control and Systems, and Editorial Board Member of International Journal of Remanufacturing. She has chaired several technical sessions and served on program committees for many conferences. She was Finance Chair of 2006 IEEE International Conference on Networking, Sensor and Control; Student Activity Chair of 2005 IEEE International Conference on Networking, Senor and Control; Special Session Chair of 2007 International Conference on Flexible Automation and Intelligent Manufacturing; Special Session Chair of 2006 International Conference on Service Operations and Logistics, and Informatics; Publication Chair of 2005 International Conference on Service Operations and Logistics, and Informatics;  and Award Committee Chair of 2003 International Conference on Information Technology: Research and Education.
She is currently Special Session Chair of 2008 IEEE Conference on Automation Science and Engineering.