Mohamed Aburaia
Papers
12
Total Citations
101
H-Index
5
About
Mohamed Aburaia is a researcher and academic at the University of Applied Sciences Technikum Wien, whose work sits at the dynamic intersection of robotics, additive manufacturing, and digital manufacturing education. He is best known for advancing robot-based Fused Filament Fabrication (FFF), addressing one of the field's most persistent limitations: the constraint of single-direction material deposition in conventional 3D printing. His highly cited 2021 paper on multi-axis robotic FFF platforms (31 citations) demonstrated how increased degrees of freedom can significantly enhance the structural integrity of printed objects, while his companion work on MeshSlicer (19 citations) tackled the critical software gap by enabling industrial robots to process STL files and generate robot-specific printing code. His earlier contribution designing a lightweight, low-cost 4-axis robot using additive manufacturing techniques (21 citations) showcased his commitment to accessible, practical robotics solutions. Beyond hardware and software innovation, Aburaia champions research-integrated teaching through Technikum Wien's Digital Factory initiative, bridging smart manufacturing concepts with higher education. His broader portfolio also spans energy-efficient robot design, machining accuracy, mobile robot navigation, and industrial cybersecurity, reflecting a versatile and impactful research vision.
Research Focus
Key Achievements
Top Papers
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- 6Design of a Robot Application with Regard to Energy Efficiency4 citations · 2021
- 7Accuracy Improvement and Process Flow Adaption for Robot Machining3 citations · 2020
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- 9Evaluierung von Navigationsmethoden für mobile Roboter2 citations · 2020
- 10A Configurable Skill Oriented Architecture Based on OPC UA2 citations · 2022