Kla Tencor Corporation

3i Systems Corporation

Wayne Chen

Andrew Zeng

Mustafa Akbulut

Zheng Yan

Bo Li

Guoheng Zhao

Jianbo Gao

Tony Young

Ning Li

Automatic optical inspection (AOI) systems are described comprising optical modules that include an illumination component and a lens array configured to direct illumination of the illumination component at a portion of a substrate. The lens array includes a Fresnel lens. The optical module includes a camera that receives reflected light resulting from an interaction of the illumination and the substrate. The camera includes a time delay integration (TDI) sensor. A telecentric imaging lens directs reflected light from the substrate to the camera. The illumination component comprises a controller coupled to multiple LED light sources, each emitting light at a different wavelength. The controller independently controls each LED light source. The illumination component includes a bright field and/or a dark field light source. The illumination component can include a front side and/or a back side light source. An optical fiber is coupled to the camera and an image processor.

Automatic inspection system for flat panel substrate

The radiation beam of discrete light source such as LEDs is shaped by a cylindrical lens and a spherical lens to form two perpendicular narrow lines to illuminate a surface. The first line is projected onto a sample surface to improve illumination efficiency, and the second line is projected onto a pupil plane of an imaging lens to improve illumination uniformity. The layout of the LED chip is optimized to match the aspect ratio of the imaging detector. Multiple LEDs at different wavelengths are combined to improve sensitivity. The full surface of the sample is inspected through the relative motion between the sample and the optics.

Method and system for inspecting surfaces with improved light efficiency

Two or more defect maps may be provided for the same sample surface at different detection sensitivities and/or processing thresholds. The defect maps may then be compared for better characterization of the anomalies as scratches, area anomalies or point anomalies. This can be done without concealing the more significant and larger size defects amongst numerous small and immaterial defects. One or more defect maps can be used to report the anomalies with classified information; the results from this map(s) can be used to monitor the process conditions to obtain better yield.

System and methods for classifying anomalies of sample surfaces

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Palo Alto, CA, United States of America

Wayne Chen