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Automated Classification Scheme

Title of Invention

Automated Classification Scheme



Automatic Virtual Metrology (AVM) has a wide range of applications in the semiconductor industry. It can convert sampling inspection with metrology delay into real-time and online total inspection. For the current wafer sawing process, the whole lot of wafers is inspected at the end of entire process; therefore, a defect occurs during processing will only be detected until the process finish, which is too late and may cause massive defects. After implementing AVM to the Wafer Sawing process, when an abnormality is found, it can be improved immediately to avoid generating defects in the subsequent wafers. Therefore, there is a need to predict wafer-chipping occurrence before applying AVM to the wafer sawing process. However, chipping won’t happen to all wafers. The AVM system can predict the chipping value for each wafer when a chipping exists while AVM cannot distinguish if the wafer has chipping or not; in other words, users can’t differentiate whether the wafer is chipped through the AVM system.

To solve the above mentioned problem, the wafer sawing quality monitoring is divided into two stages. An Automated Classification Scheme (ACS) based on ensemble learning is developed in Stage 1 to pre-determine whether there is chipping in the wafer. If chipping is detected, then proceed to Stage 2 for the AVM system to predict the chipping value.


In this patent, in addition to providing classification results, the Automated Classification Scheme (ACS) is different from the existing classification algorithms. It also provides a data quality check module, classification confidence index, and classification similarity index to reconfirm the classification results. In this way, the accuracy performance of the classification results is better ensured.

Possible Applications/ Industry Categories

TFT-LCD, Semiconductor, LED industry, Solar industry and Machine tool industry.

Contact Information

Technology Transfer and Business Incubation Center, NCKU

Contact personClaire Huang



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