Fred M. Carter III (3) , Conor Porter , Dominik Kozjek , Kento Shimoyoshi , Makoto Fujishima (3) , Naruhiro Irino (2) , Jian Cao (1)
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引用次数: 0
Abstract
An adaptive laser power control strategy for Selective Laser Melting (SLM) has been developed using data from a co-axial photodiode monitoring system with 200 KHz temporal resolution. A supervised machine learning based algorithm outputs variable laser power along the scanning path based on mechanistic features. The approach was implemented on a commercial machine and demonstrated an average 12 % reduction in porosity size and 65 % reduction in the standard deviation of porosity size measured by X-Ray Computed Tomography (CT) compared to parts built with constant laser power. This approach is scalable and its precalculated nature is compatible with regulatory concerns.
期刊介绍：
CIRP, The International Academy for Production Engineering, was founded in 1951 to promote, by scientific research, the development of all aspects of manufacturing technology covering the optimization, control and management of processes, machines and systems.
This biannual ISI cited journal contains approximately 140 refereed technical and keynote papers. Subject areas covered include:
Assembly, Cutting, Design, Electro-Physical and Chemical Processes, Forming, Abrasive processes, Surfaces, Machines, Production Systems and Organizations, Precision Engineering and Metrology, Life-Cycle Engineering, Microsystems Technology (MST), Nanotechnology.
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