Bridging the Gap: Digital Twin Integration and Evaluation in Robotic Multi-Axis Additive Manufacturing

This study aims to integrate and evaluate digital twin technology with robotic multi-axis additive manufacturing to bridge the gap between virtual planning and physical execution, enhancing the precision and efficiency of manufacturing processes. A laser tracker is employed to calibrate the machine...

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Bibliographic Details
Published inIEEE International Conference on Industrial Informatics (INDIN) pp. 1 - 8
Main Authors Jochman, Tomas, Voltr, Vaclav, Kubacek, Vaclav, Svec, Ondrej, Burget, Pavel, Hlavac, Vaclav
Format Conference Proceeding
LanguageEnglish
Published IEEE 18.08.2024
Subjects
Adaptation models
additive manufacturing
automation
Biological system modeling
digital twin
Digital twins
Laser modes
Laser theory
laser tracker
Planning
Production
robotics
Scalability
Service robots
Three-dimensional printing
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Summary:This study aims to integrate and evaluate digital twin technology with robotic multi-axis additive manufacturing to bridge the gap between virtual planning and physical execution, enhancing the precision and efficiency of manufacturing processes. A laser tracker is employed to calibrate the machine workspace and tools and introduce a comprehensive system involving an industrial robot with a filament extruder head and a rotary-tilt positioner. The digital twin not only encapsulates the geometric and operational intricacies of the multi-axis additive manufacturing process but also automates code generation for robotic operations. The application of this methodology is demonstrated through the production of two complex parts, where their dimensional fidelity is assessed to evaluate the precision limits and potential of digital twin technology in multi-axis additive manufacturing. The findings reveal significant advancements in the alignment of virtual models and physical objects, confirming the potential of digital twins to minimize deviations common in traditional manufacturing setups.
ISSN:2378-363X
DOI:10.1109/INDIN58382.2024.10774248