Table 1 State-of-the-art - Recent improvements and challenges in wafer metrology with in-process potential for R2R manufacturing.
From: Enhancing thin-film wafer inspection with a multi-sensor array and robot constraint maintenance
Technique | Recent improvements | Challenges | References |
|---|---|---|---|
Spectroscopic Reflectometry (SR) | - Novel high-scalable and low cost invention - In-process implementation - Relative angle misalignment detection | Addressed in this paper: - HW and SW architecture - Multisensor data fusion strategy - Measurement capabilities - Visible spectrum only | This paper |
SR with computer vision | - SR combined with sensor fusion | - Offline physical mapping and thousands of measurements before attempting surface mapping | |
Hyperspectral with computer vision | - Probabilistic sensor fusion implementation | - Offline physical mapping and thousands of measurements before attempting surface mapping - Complexity of technique combination | |
Imaging Ellipsometry (IE) | - Combined IE with machine learning | - Low scalability to use for in-process conditions when combined with robotic arms. - Slow process and low potential for in-process measurements - Requires thousands of measurements and data points before attempting surface mapping. (One hour for full mapping on flat surfaces) | |
Multichannel Interferometry | - Novel method using Lomb-Scargle periodogram and power spectral density for thickness calculation | - Moderate scalability to use for in-process conditions due to fibre optics and power source limitations. - Thin film thickness measurements < 400nm | |
Monochromatic Specular Reflection | - Surface mapping combining stroboscopic images with monochromatic light | - Moderate scalability to use for in-process conditions. - Angle dependency, calibration (optical corrections) and vibration effects |
