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2018
Journal Article
Titel
Self-learning Calculation for Selective Laser Melting
Abstract
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.