Probabilistic Modelling of Defects in Additive Manufacturing: A Case Study in Powder Bed Fusion Technology

Hossein Mokhtarian, Azarakhsh Hamedi, Hari Nagarajan, Suraj Panicker, Eric Coatanea, Karl Haapala

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

4 Citations (Scopus)
92 Downloads (Pure)

Abstract

Implementation of additive manufacturing into product manufacturing suffers from the challenge of part defects prediction. Due to interdependencies of design variables and manufacturing parameters in achieving suitable part quality, modelling methods are necessary to provide simulation capabilities for part quality analysis at early stages of product development. A systematic methodology is proposed to extract cause-effect relationships among variables and to transform this causal model into a Bayesian network. The Bayesian network is then used to predict the effect of specific design and manufacturing parameters on part defects and to estimate the needed input parameters backwards, based on acceptable output values.
Original languageEnglish
Title of host publication52nd CIRP Conference on Manufacturing Systems
PublisherElsevier
Pages956-961
DOIs
Publication statusPublished - 31 Dec 2018
Publication typeA4 Article in conference proceedings
EventCIRP Conference on Manufacturing Systems -
Duration: 1 Jan 2000 → …

Publication series

NameProcedia CIRP
Volume81
ISSN (Electronic)2212-8271

Conference

ConferenceCIRP Conference on Manufacturing Systems
Period1/01/00 → …

Publication forum classification

  • Publication forum level 1

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