Kyriakos Sabatakakis

Papers

Total Citations

H-Index

About

Kyriakos Sabatakakis is a researcher at the forefront of intelligent manufacturing, specializing in the quality monitoring and optimization of robotized Resistance Spot Welding (RSW)—a process critical to the automotive industry. His work bridges mechanical engineering and data science, leveraging machine learning to solve industrial challenges. Sabatakakis’s most impactful contribution is his pioneering use of infrared (IR) thermography combined with machine learning algorithms for non-destructive quality assessment of RSW. His 2021 paper on this topic, which has garnered 41 citations, demonstrates how thermal imaging data can predict weld quality in real time, significantly reducing the need for costly destructive testing. This work has established a new paradigm for in-process monitoring in automated assembly lines. More recently, Sabatakakis has explored the influence of mechanical vibrations on weld quality, a critical factor often overlooked in robotic applications. His 2023 study on this subject adds a vital layer of understanding to the field, showing how dynamic forces affect joint integrity. By integrating sensor data with AI-driven analysis, Sabatakakis is driving the evolution of smart, self-correcting manufacturing systems, making him a key figure in the advancement of Industry 4.0 quality control.