Taiwan Semiconductor Manufacturing Comp. Ltd.

Chien-Huei Chen

Xiaomeng Chen

Hung-Yi Chung

Shih-Chang Wang

Yung-Cheng Lin

Pei-Chao Su

Kuang-Shing Chen

Wei-Chen Wu

Chan-Ming Chang

Chien-An Lin

Shih-Yung Chen

Li-Jou Lee

Cheng-Kuang Lee

Chao-Ting Hong

Teng-Cheng Hsu

Hsiu-Hui Huang

A hot spot defect detecting method and a hot spot defect detecting system are provided. In the method, hot spots are extracted from a design of a semiconductor product to define a hot spot map comprising hot spot groups, wherein local patterns in a same context of the design yielding a same image content are defined as a same hot spot group. During runtime, defect images obtained by an inspection tool performing hot scans on a wafer manufactured with the design are acquired and the hot spot map is aligned to each defect image to locate the hot spot groups. The hot spot defects in each defect image are detected by dynamically mapping the hot spot groups located in each defect image to a plurality of threshold regions and respectively performing automatic thresholding on pixel values of the hot spots of each hot spot group in the corresponding threshold region.

Hot spot defect detecting method and hot spot defect detecting system

A method of qualifying semiconductor wafer processing includes: illuminating a semiconductor wafer simultaneously with source light having wavelengths in a plurality of wavebands, including at least a first waveband and a second waveband, the second waveband being different from the first waveband; separating light reflected from the semiconductor wafer as a result of said illuminating, the separating dividing the reflected light according to waveband; generating a first image of the semiconductor wafer based on reflected light separated into the first waveband; and, generating a second image of the semiconductor wafer base on reflected light separated into the second waveband.

Simultaneous multi-bandwidth optical inspection of semiconductor devices

A method for semiconductor wafer inspection is provided. The method includes the following operations. The semiconductor wafer is scanned to acquire a scanned map, wherein the semiconductor wafer is patterned according to a design map having a programmed defect. The design map and the scanned map are transformed to a transformed inspection map according to the location of the programmed defect on the design map and the location of the programmed defect on the scanned map. The system of semiconductor wafer inspection is also provided.

Method for semiconductor wafer inspection and system thereof

A defect detecting method, a defect detecting system, and a non-transitory computer-readable medium are provided. The defect detecting method includes applying a rank filter to multiple scan images of consecutive dies of a reference wafer scanned by a wafer inspection tool to obtain multiple reference die images; collecting multiple target die images of a target die of a target wafer scanned by the wafer inspection tool; comparing the target die images with the reference die images to detect multiple defects according to differences of pixel values of corresponding pixels in the target die images and the reference die images; and excluding multiple common defects from the detected defects to detect at least one mask defect printed on the target wafer, where the common defects are obtained by the wafer inspection tool performing a wafer inspection on the target wafer.

Defect detecting method and defect detecting system

A defect inspection method and a defect inspection system are provided. In the method, a plurality of candidate defect images are retrieved from inspection images obtained by at least one optical inspection tool performing hot scans on at least one wafer and a plurality of attributes are extracted from the inspection images. A random forest classifier including a plurality of decision trees for classifying the candidate defect images is created, wherein the decision trees are built with different subset of the attributes and the candidate defect images. A plurality of candidate defect images are retrieved from the optical inspection tool in runtime and applied to the decision trees, and classified into nuisance images and real defect images according to votes of the decision trees in which the nuisance images are filtered out. The real defect images with the votes over a confidence value are sampled for microscopic review.

Defect inspection method and defect inspection system

Growing community of inventors

Kaohsiung, Taiwan

Chien-Huei Chen