Optimization of an Additive Manufacturing Process Using Ultrasound

Additive Manufacturing is used for printing parts with high precision and complex geometries, but achieving consistent material properties and avoiding defects is a challenge. This paper presents the use of ultrasound technology as a non-destructive method to optimize the additive manufacturing process. A factorial design is used to print 18 samples using the key process parameters such as Power, Speed, and Hatch Distance. The ultrasound measurements are carried out using a 7.5 MHz focused transducer to capture within-sample variation. The manufacturing parameters and ultrasound variation metric is converted to a response surface model which is then used to identify optimal manufacturing conditions that can help minimize process induced variation and get a consistent microstructure and achieve consistent mechanical properties.

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Publication Details

Published
2024-09-22
DOI
https://doi.org/10.1109/uffc-js60046.2024.10793559
Primary Topic
Additive Manufacturing and 3D Printing Technologies
Type
article
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article

Optimization of an Additive Manufacturing Process Using Ultrasound

Shafaq Zia, Pia Åkerfeldt, Johan E. Carlson
Additive Manufacturing and 3D Printing Technologies
article

Optimization of an Additive Manufacturing Process Using Ultrasound

Shafaq Zia, Pia Åkerfeldt, Johan E. Carlson
article en

Abstract

Additive Manufacturing is used for printing parts with high precision and complex geometries, but achieving consistent material properties and avoiding defects is a challenge. This paper presents the use of ultrasound technology as a non-destructive method to optimize the additive manufacturing process. A factorial design is used to print 18 samples using the key process parameters such as Power, Speed, and Hatch Distance. The ultrasound measurements are carried out using a 7.5 MHz focused transducer to capture within-sample variation. The manufacturing parameters and ultrasound variation metric is converted to a response surface model which is then used to identify optimal manufacturing conditions that can help minimize process induced variation and get a consistent microstructure and achieve consistent mechanical properties.

Luleå University of Technology (SE)
Openalex Percentile: Top 75%
Additive Manufacturing and 3D Printing Technologies
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