Wafer surface defect mode detection and analysis method

Abstract

The invention provides a wafer surface defect mode detection and analysis method which can detect surface defects of crystal grains and judge distribution modes and defect mode causes of the defectivecrystal grains. The invention belongs to the field of defect detection in the wafer production and manufacturing process, and aims to solve the problems of high manual labor intensity, low detectionefficiency and the like in the existing defect detection method. The specific process comprises the following steps: acquiring a crystal grain image, and generating a wafer defect mode diagram througha machine vision method; constructing and training a wafer defect mode detection model and a classification model, the detection model being used for determining whether the wafer has a defect mode,and the classification model being used for determining a specific defect mode type; and finally, retrieving the marked sample most similar to the to-be-detected sample in a database according to a similarity measurement algorithm, and inferring the defect mode cause of the to-be-detected sample by analyzing the defect mode cause of the known sample.

Description

[0001] Technical field: [0002] The invention belongs to the field of defect detection in the wafer manufacturing process. Specifically, it relates to a method for detecting defects on the surface of a wafer by using a machine vision method, judging the type of the defect mode, and analyzing the cause of the defect mode. Background technique [0003] Integrated circuits are the basis and source of power for the rapid development of today's information technology industry, and have been highly penetrated and integrated into every field of national economy and social development. One of the signs. In recent years, my country has continuously introduced industrial policies and guidelines to promote and guide the development of the integrated circuit industry. The production and manufacturing of integrated circuits has a very complicated process. Among them, wafers are the main material for manufacturing chips, and their surface defects are the main obstacle affecting product y...

AI Technical Summary

Problems solved by technology

However, these methods all have complex feature engineering, which requires manual extraction of wafer defect pattern features, and the classification accuracy is low.

At the same time, the above methods are limited to the classification of wafer defect modes, and in each defect mode, the fundamental defects of the wafer are different, and the above methods cannot analyze the cause of defect modes

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