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A Spatial Multi-layer Control Concept for Strand Geometry Control in Robot-Based Additive Manufacturing Processes
Employing force-flow-oriented designs in structural components holds a significant potential to achieve material savings. This potential is of particular interest to the construction industry due to the substantial component size and the high energy demands in the production of raw materials. However, manufacturing the intricate free-form shapes generated by topology optimizations using conventional construction techniques is costly. Consequently, concrete-based additive manufacturing (AM) processes are researched for construction applications. Utilizing concrete as a 3D printing material faces several challenges such as its susceptibility to environmental influences, including humidity, temperature, and sunlight. While the influence on the individual layer is neglectable, the deviations add up due to the layer-by-layer production and can lead to component collapse. Previous research indicates that large-scale AM’s reproducibility and stability improve using inline process control. This publication introduces a spatial multi-layer approach wherein the measured inline data is stored within the machines’ coordinate system. This approach enables designing a process control algorithm based on current measurements as well as incorporating underlying deviations. This allows the implementation of integral components into the control algorithm to enhance controller performance and stabilize printing processes. The present experiments prove stabilization of the layer width and the spray distance, even in the attendance of multi-layer defects.
A Spatial Multi-layer Control Concept for Strand Geometry Control in Robot-Based Additive Manufacturing Processes
Employing force-flow-oriented designs in structural components holds a significant potential to achieve material savings. This potential is of particular interest to the construction industry due to the substantial component size and the high energy demands in the production of raw materials. However, manufacturing the intricate free-form shapes generated by topology optimizations using conventional construction techniques is costly. Consequently, concrete-based additive manufacturing (AM) processes are researched for construction applications. Utilizing concrete as a 3D printing material faces several challenges such as its susceptibility to environmental influences, including humidity, temperature, and sunlight. While the influence on the individual layer is neglectable, the deviations add up due to the layer-by-layer production and can lead to component collapse. Previous research indicates that large-scale AM’s reproducibility and stability improve using inline process control. This publication introduces a spatial multi-layer approach wherein the measured inline data is stored within the machines’ coordinate system. This approach enables designing a process control algorithm based on current measurements as well as incorporating underlying deviations. This allows the implementation of integral components into the control algorithm to enhance controller performance and stabilize printing processes. The present experiments prove stabilization of the layer width and the spray distance, even in the attendance of multi-layer defects.
A Spatial Multi-layer Control Concept for Strand Geometry Control in Robot-Based Additive Manufacturing Processes
RILEM Bookseries
Lowke, Dirk (Herausgeber:in) / Freund, Niklas (Herausgeber:in) / Böhler, David (Herausgeber:in) / Herding, Friedrich (Herausgeber:in) / Lachmayer, Lukas (Autor:in) / Quantz, Jelle (Autor:in) / Heeren, Hauke (Autor:in) / Recker, Tobias (Autor:in) / Dörrie, Robin (Autor:in) / Kloft, Harald (Autor:in)
RILEM International Conference on Concrete and Digital Fabrication ; 2024 ; Munich, Germany
Fourth RILEM International Conference on Concrete and Digital Fabrication ; Kapitel: 14 ; 119-126
RILEM Bookseries ; 53
01.09.2024
8 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Europäisches Patentamt | 2015
|British Library Online Contents | 2018
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