Enhancing thin-film wafer inspection with a multi-sensor array and robot constraint maintenance.

Area of Science:

• Materials Science
• Robotics
• Manufacturing Engineering

Background:

• Thin-film inspection on large substrates is crucial for quality control in coating manufacturing.
• Existing inspection equipment has limitations for large-area coverage and automated manipulation.
• Roll-to-Roll (R2R) manufacturing presents unique challenges for coating thickness inspection.

Purpose of the Study:

• To develop an autonomous inspection system for large-area substrates.
• To address challenges in precise manipulation and scalable measurement for industrial applications.
• To enable accurate static and dynamic thin-film thickness and angle variation measurements.

Main Methods:

• Implementation of a robotic manipulator with a learned constraint manifold for precise wafer positioning.
• Development of a novel multi-sensor array for scalable, large-area thin-film inspection.
• Integration of static and dynamic measurement capabilities with error analysis.

Main Results:

• The robotic manipulator successfully adhered to movement constraints during wafer calibration.
• Static thickness measurements achieved an error of [Formula: see text] compared to a commercial reflectometer.
• Dynamic angle variation detection up to [Formula: see text] from calibration was demonstrated with RMSE and R[Formula: see text] analysis.

Conclusions:

• The developed autonomous system effectively addresses limitations in large-area thin-film inspection.
• The system shows high potential for scalability in industrial applications like R2R manufacturing.
• The ability to detect static thickness and dynamic angle variations is a significant advancement for quality control.