NDLI: Parameter estimation for optimal disassembly planning

Content Provider	IEEE Xplore Digital Library
Author	Grochowski, D.E. Ying Tang
Copyright Year	2007
Description	Author affiliation: Rowan Univ., Glassboro (Grochowski, D.E.; Ying Tang)
Abstract	Due to the rapid increase of technological waste in recent years, it has become necessary to find ways of handling the waste in an economically sound and environmentally benign manner. In order to do so, many groups are attempting to disassemble obsolete products in order to reuse or recycle the various components and/or materials such products are comprised. To ease in the disassembly procedure of these products, this paper describes an expert system, consisting of a disassembly Petri network (DPN) and a hybrid Bayesian network (HBN), for optimal disassembly planning. The DPN, the HBN, the interaction between the DPN and the HBN, and the use of inference with the HBN are briefly discussed. Specifically, the paper focuses on ascertaining the parameters of the nodes in the HBN with the use of data collected during the disassembly process and a method for the structure learning of nodes which influence the logistic nodes in the HBN.
Starting Page	2490
Ending Page	2495
File Size	243872
Page Count	6
File Format	PDF
ISBN	9781424409907
DOI	10.1109/ICSMC.2007.4413878
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-07
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Parameter estimation Learning Bayesian methods Space technology Uncertainty Technology planning Waste handling Environmental economics Recycling Expert systems
Content Type	Text
Resource Type	Article

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