Additive Manufacturing (AM) enables novel classes of product complexity together with high levels of customization for functional components that shall meet strict quality requirements. Because of this, novel product qualification and statistical process control challenges must be faced in industry. Traditional methods could become not applicable in this new scenario, as they are based on monitoring simple geometrical or dimensional features and they entail a training phase consisting of several copies of the same part. Because of this, the possibility of using data and signals acquired via in-situ sensors during the process to support qualification procedures has been attracting a great industrial interest. This study presents an in-situ metrology method that combines in-situ geometry reconstruction of the part via layerwise image segmentation and a quality modelling approach that allows estimating synthetic geometric patterns in terms of 1D profile data. The method is specifically thought for one class of complex shapes enabled by AM that is lattice structures. It aims at providing a methodological framework to anticipate geometrical assessment and anomaly detection while the part is being built and even in the presence of one-of-a-kind structures. A real case study in L-PBF is presented to demonstrate the feasibility and benefits of the proposed approach.

In-situ metrology and process monitoring in laser powder bed fusion of lattice structures

Marco Grasso;Federica Garghetti;Luca Pagani;Bianca Maria Colosimo
2020-01-01

Abstract

Additive Manufacturing (AM) enables novel classes of product complexity together with high levels of customization for functional components that shall meet strict quality requirements. Because of this, novel product qualification and statistical process control challenges must be faced in industry. Traditional methods could become not applicable in this new scenario, as they are based on monitoring simple geometrical or dimensional features and they entail a training phase consisting of several copies of the same part. Because of this, the possibility of using data and signals acquired via in-situ sensors during the process to support qualification procedures has been attracting a great industrial interest. This study presents an in-situ metrology method that combines in-situ geometry reconstruction of the part via layerwise image segmentation and a quality modelling approach that allows estimating synthetic geometric patterns in terms of 1D profile data. The method is specifically thought for one class of complex shapes enabled by AM that is lattice structures. It aims at providing a methodological framework to anticipate geometrical assessment and anomaly detection while the part is being built and even in the presence of one-of-a-kind structures. A real case study in L-PBF is presented to demonstrate the feasibility and benefits of the proposed approach.
2020
Proceedings of the ASTM International Conference on Additive Manufacturing (ASTM ICAM 2020)
In-situ metrology, lattice structures, additive manufacturing, laser powder bed fusion, image segmentation
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1167697
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