The wafer eccentricity deviation caused by misalignment between the center of the wafer and rotary table will lead to edge image distortion and quality degradation of the defect signals during automated inspection. However, wafer end jump and edge topography change will bring great challenges to the accurate measurement of micrometer deviations. A new wafer eccentricity deviation measurement method based on line-scanning chromatic confocal sensors (LSCCSs) is proposed. Firstly, the LSCCS with Z-axis submicron resolution used in the experiment acquires the 3D profile height of the wafer edge as the turntable rotates, and the edge distance is calculated at each rotation angle. Secondly, a robust Fourier-LAR fitting method is used to fit edge distance serial to reduce sensitivity to outliers. Finally, the wafer eccentricity deviation that is equal to the wafer center coordinate can be calculated using the wafer eccentricity deviation model. In the simulated experiment, the results show that the eccentricity deviation measurement accuracy was insensitivity to noise and reached the micron level. Additionally, the measurement uncertainty of eccentricity deviation coordinate $\left(X_w,Y_w\right)$ was (0.53 µm, 1.4 µm) in the actual data of the 12-inch wafers.

Detecting and classifying defects on unpatterned wafers is a key part of wafer front-end inspection. Defect inspection schemes vary depending on the type and location of the defects. In this paper, the structure of the prototype is designed to meet the requirements of wafer surface and edge defect inspection. This prototype has four inspection channels: scattering, reflection, phase, and contour, with two working conditions: surface and edge inspection. The key structure of the prototype was simulated using Ansys. The simulation results show that the maximum deformation of the optical detection subsystem is 19.5 μm and the fundamental frequency of the prototype is 96.9 Hz; thus, these results meet the requirements of optical performance stability and structural design. The experimental results show that the prototype meets the requirements of the inspection sensitivity better than 200 nm equivalent PSL spherical defects.

The spot scanning defect detection system has good detection performance for wafer defects. However, due to the existence of system assembly errors, the wafer defect inspection system could not scan following the planned trace, which resulted in distortion of the reconstructed image and had a greater impact on defect feature extraction and accurate defect location. The system deviation calibration and adjustment can further facilitate the accuracy of the system position and image reconstruction. To address this issue, the causes and shapes of imaging distortion were analyzed and simulated, and a simple and effective calibration method based on a scanning deviation model for the spot scanning defect detection system was proposed. First, a scanning deviation model was established following the characteristics of the spot scanning system, and different degrees of reconstructed image distortion were simulated and analyzed as the system deviation changes. Then, an 8-inch wafer with a grid was used as the calibrator and scanned using the developed spot scanning system. Serveral grid corners in the reconstructed image are selected and used as the calibration feature points. The constraint function is constructed using the equidistant features between adjacent grid points, and then the quasi-Newton method is used to optimize the parameters of the function to obtain the best deviation estimation of the spot scanning system. To prove the validity of the estimated deviation parameters, another patterned wafer was scanned and the distortion image was used for reconstruction. The experiment demonstrated that an accurate and distortion-free wafer image can be reconstructed using the calibrated deviation parameters, and the root mean square error of the measured distance between two points of interest was only 0.61 pixels, which proved the effectiveness of the proposed calibration method.

For spot scanning dark-field scattering technology, the defocus caused by the change in wafer surface height decreases the defect detection rate and size measurement repeatability. The demand for accurately and rapidly measuring the wafer surface height online is becoming increasingly urgent. The defect detection system integrates scattering, reflection, film thickness, and topography defect detection channels. The integration of laser-triangulation-based defocus measurement into the bright-field optical path is proposed. The laser beam is directed onto the surface of the wafer, and the reflected light is transmitted through a lens onto the photosensitive surface of a four-quadrant detector. This detector captures both the strength and position of the reflected signal simultaneously. In this paper, a triangulation-modified model is established to obtain the height of each inspection spot on the wafer surface through the position signal of the reflected image. When the signal-to-noise ratio of the simulated reflection image position is 20 dB, the signal-to-noise ratio of the height measurement resolved by the triangulation-modified model is 41 dB, and the measurement error is less than 0.2 μm, indicating that the model has a noise suppression effect. The spot-scanning imaging system is established, and the height measurement results of the triangulation measurement model are verified using a laser interferometer. Within the travel range of 69 μm, the system has a measurement accuracy better than ±1 μm and a measurement repeatability better than ±0.2 μm, which meet the measurement requirements of the spot-scanning imaging system. The system is utilized for defect detection and defocus measurement of the wafer surface, along with the motion mechanism, to accurately and rapidly obtain the height distribution of the wafer surface.

A phase-modulated ellipsometer enables non-contact, high-precision determination of thin-film optical parameters and thickness through polarized light modulation analysis. However, conventional ellipsometers suffer from limited measurement accuracy due to systemic calibration drift and environmental interference. This research presents a novel metrological approach integrating backpropagation neural networks (BP) with a hybrid Particle Swarm Optimization–Levenberg–Marquardt (PSO-LM) algorithm for thin-film thickness quantification. The proposed framework simultaneously determines system parameters and ellipsometry coefficients (ψ, Δ) via multi-objective optimization, achieving calibration-free thickness characterization with sub-nanometer precision. Experimental validation was performed on SiO₂/Si samples with thicknesses ranging from 20 nm to 500 nm. Results demonstrate that the proposed method achieves a root mean square error (RMSE) of <0.006 across the entire thickness range, outperforming the traditional calibration-based method (RMSE ~ 0.008). In addition, the adaptability and stability of the algorithm to complex optical systems are also verified, providing a new method for industrial film thickness monitoring.