Deep Learning-based deposition modelling and path planning in Wire Arc Additive Manufacturing
type: CreativeWork
author: Glasder, Magnus; id_orcid0000-0002-1071-044X
language: en
keywords: Additive Manufacturing; Wire Arc Additive Manufacturing (WAAM); Deep Learning; Deposition model; Wire arc directed energy deposition (DED-Arc); Artificial Intelligence; Machine Learning; WELDING AND ALLIED TECHNIQUES (JOINING OF MATERIALS), info:eu-repo/classification/ddc/670, info:eu-repo/classification/ddc/620, info:eu-repo/classification/ddc/004, Manufacturing, Engineering & allied operations, Data processing, computer science
license: http://rightsstatements.org/page/InC-NC/1.0/
date published: 2024
date modified: 2026-07-27T19:29:08Z
provider: ETH Zürich
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: ETH Zurich

PropertyValue
property ID: Handle
value: http://hdl.handle.net/20.500.11850/712309

PropertyValue
property ID: DOI
value: 10.3929/ethz-b-000712309