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dc.contributor.author
Eisenbarth, Daniel
dc.contributor.author
Menichelli, Alessandro
dc.contributor.author
Soffel, Fabian
dc.contributor.author
Wegener, Konrad
dc.contributor.editor
Meboldt, Mirko
dc.contributor.editor
Klahn, Christoph
dc.date.accessioned
2021-01-18T10:20:30Z
dc.date.available
2020-12-22T07:37:15Z
dc.date.available
2021-01-18T10:20:30Z
dc.date.issued
2020
dc.identifier.isbn
978-3-030-54333-4
en_US
dc.identifier.isbn
978-3-030-54334-1
en_US
dc.identifier.other
10.1007/978-3-030-54334-1_12
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/457994
dc.description.abstract
Direct metal deposition is an additive technology that has the potential to fabricate large parts in multiple buildup directions. Especially curved, thin-walled geometries such as exhaust manifolds are a promising use case: In theory, direct metal deposition allows nearly arbitrary shapes. Internal surfaces that are not accessible with the final part could be inspected and machined in a stepwise buildup process. However, the successful production of such parts requires suitable algorithms for five-axis tool path planning as well as for the optimization of the parameters for the specific process. Herein, an adaptive slicing algorithm is presented that aligns the direction of each layer for minimized overhangs and creates the tool path under consideration of the process capabilities and limits. By a variation of the scan speed, the deposited powder per length and therefore the layer height can be modified continuously. A model-based feedforward control of the laser power accounts for the varying thermal conduction in thin walls. These approaches are integrated in a fully automated CAM software that generates a suitable tool path with locally adapted parameters. The fabrication of an exemplary exhaust manifold shows that the software reduces the manual preparation effort and enables a flexible additive manufacturing process.
en_US
dc.language.iso
en
en_US
dc.publisher
Springer
en_US
dc.subject
Direct metal deposition
en_US
dc.subject
Adaptive slicing
en_US
dc.subject
Tool path planning
en_US
dc.subject
Process optimization
en_US
dc.subject
CAM programming
en_US
dc.title
Adaptive Slicing and Process Optimization for Direct Metal Deposition to Fabricate Exhaust Manifolds
en_US
dc.type
Conference Paper
dc.date.published
2020-09-01
ethz.book.title
Industrializing Additive Manufacturing
en_US
ethz.pages.start
160
en_US
ethz.pages.end
173
en_US
ethz.event
2nd International Conference on Additive Manufacturing in Products and Applications (AMPA 2020)
en_US
ethz.event.location
Zurich, Switzerland
en_US
ethz.event.date
September 1-3, 2020
en_US
ethz.notes
Due to the Coronavirus (COVID-19) the conference was held as a hybrid conference with participants on site and remote.
en_US
ethz.publication.place
Cham
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02623 - Inst. f. Werkzeugmaschinen und Fertigung / Inst. Machine Tools and Manufacturing::03641 - Wegener, Konrad (emeritus) / Wegener, Konrad (emeritus)
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02130 - Dep. Maschinenbau und Verfahrenstechnik / Dep. of Mechanical and Process Eng.::02623 - Inst. f. Werkzeugmaschinen und Fertigung / Inst. Machine Tools and Manufacturing::03641 - Wegener, Konrad (emeritus) / Wegener, Konrad (emeritus)
en_US
ethz.relation.isPartOf
20.500.11850/450196
ethz.date.deposited
2020-12-22T07:37:23Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2021-01-18T10:21:09Z
ethz.rosetta.lastUpdated
2024-02-02T12:53:30Z
ethz.rosetta.versionExported
true
ethz.COinS
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