Data-Driven Process Optimization of Fused Filament Fabrication based on In Situ Measurements
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Author / Producer
Date
2023-11-22
Publication Type
Conference Paper
ETH Bibliography
yes
Citations
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Data
Abstract
The tuning of fused filament fabrication parameters is notoriously challenging. We propose an autonomous data-driven method to select parameters based on in situ measurements. We use a laser sensor to evaluate the surface roughness of a printed part. We then correlate the roughness to the mechanical properties of the part, and show how print quality affects mechanical performance. Finally we use Bayesian optimization to search for optimal print parameters. We demonstrate our method by printing liquid crystal polymer samples, and successfully find parameters that produce high-performance prints and maximize the manufacturing process efficiency.
Permanent link
Publication status
published
External links
Book title
22nd IFAC World Congress
Journal / series
Volume
56 (2)
Pages / Article No.
4713 - 4718
Publisher
Elsevier
Event
22nd IFAC World Congress 2023
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Process control applications; Process optimization; Applications in advanced materials manufacturing; Bayesian methods; Machine Learning; Sensing
Organisational unit
03751 - Lygeros, John / Lygeros, John
02650 - Institut für Automatik / Automatic Control Laboratory