Markus Fratz

Fraunhofer Institute for Physical Measurement Techniques

Papers

Total Citations

H-Index

About

Markus Fratz is a researcher advancing the frontiers of precision metrology through digital holography and deep learning. His work focuses on integrating multi-wavelength digital holographic sensor systems into dynamic, production-line environments, particularly on multi-axis platforms like collaborative robots and machine tools. Fratz’s major contributions address a critical challenge: detecting and compensating for unknown, complex vibrations that degrade measurement quality during high-precision quality control in machining production. In his 2023 paper, he pioneered the use of deep learning to identify vibrations in the early steps of hologram reconstruction, a breakthrough that enhances measurement reliability in real-world industrial settings. His 2021 work marked a significant milestone by presenting the first extensive, stitched, manually selected multiwavelength digital holographic measurement data recorded using a collaborative robot for handling. Though his most-cited papers currently have 3 and 2 citations respectively, these foundational studies are poised to grow in influence as the field adopts AI-driven, robot-integrated optical metrology. Fratz’s innovative fusion of holography, robotics, and machine learning is paving the way for smarter, more resilient quality control in advanced manufacturing.