Abstract
Disassembly processes of used manufactured products are subject to uncertainties. The optimal disassembly level that minimizes the costs of these processes and maximizes the end of life components values is hard to establish. In this work, we propose a method to find influences and causalities between the main disassembly performance indicators in order to decide the optimal disassembly policy. The proposed model highlights the temporal dependencies between variables of the system and is validated using the Bayesia Lab software. In the final part of the chapter, the results of method implementation on a reference case study are presented in order to demonstrate the performance of our approach.
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Duta, L., Douche, S.A. (2012). Dynamic Bayesian Network for Decision Aided Disassembly Planning. In: Borangiu, T., Thomas, A., Trentesaux, D. (eds) Service Orientation in Holonic and Multi-Agent Manufacturing Control. Studies in Computational Intelligence, vol 402. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27449-7_11
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DOI: https://doi.org/10.1007/978-3-642-27449-7_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27448-0
Online ISBN: 978-3-642-27449-7
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