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Self-learning calculation for selective laser melting
Citation Link: https://doi.org/10.15480/882.1741
Publikationstyp
Journal Article
Date Issued
2018-03-21
Sprache
English
Author(s)
Institut
TORE-DOI
Journal
Volume
67
Start Page
185
End Page
190
Citation
Procedia CIRP (67): 185-190 (2018)
Contribution to Conference
Publisher DOI
Scopus ID
Publisher
Elsevier
Selective laser melting (SLM) is increasingly used in the industrial production of metallic parts. This creates the need for an efficient and
accurate quotation costing. The manufacturing costs of a part mainly result from the machine running time for coating and exposure. At the
time of the offer calculation the final orientation of the part in the build chamber and the composition of the build job are typically not known.
Addressing this need, this paper presents and evaluates different statistical based methods for an automated and self-learning calculation for SLM given a part’s CAD data.
accurate quotation costing. The manufacturing costs of a part mainly result from the machine running time for coating and exposure. At the
time of the offer calculation the final orientation of the part in the build chamber and the composition of the build job are typically not known.
Addressing this need, this paper presents and evaluates different statistical based methods for an automated and self-learning calculation for SLM given a part’s CAD data.
Subjects
Calculation
Quotation costing
Self-learning
Selective laser melting (SLM)
Additive manufacturing (AM)
DDC Class
600: Technik
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