Original scientific paper

https://doi.org/10.31803/tg-20200526143210

In-Situ Process Monitoring in Additive Manufacturing Using Statistics and Pre-Process Data

Eva Maria Scheideler orcid.org/0000-0002-5552-2493 ; Department of Production Engineering, TH-OWL University of Applied Sciences and Arts, Campusallee 12, D 32657 Lemgo, Germany
Andrea Huxol ; Quality Assurance, Hora Holter Regelarmaturen GmbH & Co. KG, Helleforthstraße 58-60, D 33758 Schloß Holte-Stukenbrock, Germany

Abstract

Long computation times are a major obstacle for the application of in-situ monitoring in additive manufacturing. This paper presents rapid in-situ monitoring, which returns a control value within typical build times. Observing powder bed fusion processes reveals that unsuitable parameter settings influence the appearance of the molten surface and the surrounding powder bed. The presented research approach evaluates the changing appearance of the exposed layers, in combination with the information from the pre-process about the position and geometry of the components in each layer. Grayscale images are captured with the build envelope camera and examined regarding the grayscale distribution in the critical areas surrounding the component boundaries. The grayscale distribution is then used to predict product quality by using standard statistical methods. The combination of the pre-process data and the fast analysis of the grayscale distribution allows promptly calculating a performance indicator for required process intervention and control.

Keywords

energy density; image processing; layer check; part quality; Selective Laser Melting

Hrčak ID:

239006

URI

https://hrcak.srce.hr/239006

Publication date:

11.6.2020.

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