Enhancing Thin-Film Wafer Inspection With A Multi-Sensor Array And Robot Constraint Maintenance

Thin-film inspection on large-area substrates in coating manufacture remains a critical parameter to ensure product quality; however, extending the inspection process precisely over a large area presents major challenges, due to the limitations of the available inspection equipment. An additional manipulation problem arises when automating the inspection process, as the silicon wafer requires movement constraints to ensure accurate measurements and to prevent damage. Furthermore, there are other increasingly important large-area industrial applications, such as Roll-to-Roll (R2R) manufacturing where coating thickness inspection introduces additional challenges. This paper presents an autonomous inspection system using a robotic manipulator with a novel learned constraint manifold to control a wafer to its calibration point, and a novel multi-sensor array with high potential for scalability into large substrate areas. We demonstrate that the manipulator can perform required motions whilst adhering to movement constraints. We further demonstrate that the sensor array can perform thickness measurements statically with an error of $<2\%$ compared to a commercial reflectometer, and through the use of a manipulator can dynamically detect angle variations $>0.5^\circ$ from the calibration point whilst monitoring the RMSE and $R^2$ over 1406 data points. These features are potentially useful for detecting displacement variations in R2R manufacturing processes.

@article{sánchez-arriaga2025_2503.05853,
  title={ Enhancing Thin-Film Wafer Inspection With A Multi-Sensor Array And Robot Constraint Maintenance },
  author={ Néstor Eduardo Sánchez-Arriaga and Ethan Canzini and Nathan John Espley-Plumb and Michael Farnsworth and Simon Pope and Adrian Leyland and Ashutosh Tiwari },
  journal={arXiv preprint arXiv:2503.05853},
  year={ 2025 }
}