Papers
23
Total Citations
1,190
H-Index
14
About
P. Aivaliotis is a prominent researcher whose work sits at the intersection of digital manufacturing, robotics, and intelligent maintenance systems. Best known for pioneering contributions to the Digital Twin (DT) concept applied to predictive maintenance, Aivaliotis has developed physics-based simulation methodologies that enable the calculation of Remaining Useful Life (RUL) for industrial machinery and robots — work that has resonated strongly with the research community, earning over 400 citations for a single landmark 2019 paper alone. A second foundational study from the same year, with 233 citations, further solidified the two-pillar framework of digital model creation and DT enabling that has since influenced the field broadly. Beyond predictive maintenance, Aivaliotis has made meaningful contributions to human-robot collaboration, including sensorless power and force limiting on industrial robots and ROS-based coordination architectures for cooperative assembly tasks. More recent work explores dynamic digital twins and flexible robotic manipulator modeling, reflecting a sustained drive to keep pace with evolving manufacturing demands. With machine learning applied to visual part recognition and mobile robot integration also among their contributions, Aivaliotis represents a versatile voice in modern smart manufacturing research, accumulating over 1,000 citations across a focused and cohesive body of work.
Research Focus
Key Achievements
Top Papers
- 1The use of Digital Twin for predictive maintenance in manufacturing411 citations · 2019
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- 4Power and force limiting on industrial robots for human-robot collaboration88 citations · 2019
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- 7Design and simulation of assembly systems with mobile robots36 citations · 2014
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- 9Towards accurate robot modelling of flexible robotic manipulators30 citations · 2021
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