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Surface Inspection|Corerain x The Domestic Microelectronics Group

Introduction

As one of the largest manufacturers of lithography machine in China, the microelectronics group is mainly dedicated to the development, design, manufacture, sales and technical services of semiconductor equipment, pan-semiconductor equipment and high-end intelligent equipment.


Challenges
Insufficient Amount of Defect Data
Insufficient Amount of Defect Data
Some defect samples are small in number and not easy to collect in the short term, and there is a lack of effective public data sets in the industry.
High Problem Complexity
High Problem Complexity
The diversity of wafer defect types is high and the imaging of the same defect is affected by various factors such as process, batch, and lighting conditions of AOI.
High Requirements of Real-time Computation
High Requirements of Real-time Computation
AOI has a high imaging resolution, and the complexity of image computation is positively correlated with the image resolution.
Solutions

In response to the complicated problems of wafer surface defect detection, Corerain provides a hybrid solution based on deep learning algorithms and supplemented by traditional computer vision algorithms to integrate the detection, classification, regression  and recognition algorithms of the target. Combined with the self-developed AI accelerators with low latency, high performance and high cost-efficiency, an integrated AI machine vision wafer inspection solution is developed by Corerain.

Results
Identify defects such as wafer overdisplay, tarnish, probe, residue and scuff with an algorithm accuracy over 99%.
Identify defects such as wafer overdisplay, tarnish, probe, residue and scuff with an algorithm accuracy over 99%.
有效加强现场安全监管管理,提高生产效率,降本提效。
Achieve accurate and efficient full-line inspection and classification, effectively shorten the product development cycle and reduce production cost by 50% for companies.
Relevant Cases

Accelerate AI Deployment with Next-Gen Computing Platform

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