Welcome to the IKCEST

IEEE Transactions on Semiconductor Manufacturing | Vol.31, Issue.1 | | Pages 156-165

IEEE Transactions on Semiconductor Manufacturing

Clustering the Dominant Defective Patterns in Semiconductor Wafer Maps

Kamal Taha  
Abstract

Identifying defect patterns on wafers is crucial for understanding the root causes and for attributing such patterns to specific steps in the fabrication process. We propose in this paper a system called Dominant Defective Patterns Finder (DDPfinder) that clusters the patterns of defective chips on wafers based on their spatial dependence across wafer maps. Such clustering enables the identification of the dominant defect patterns. DDPfinder clusters chip defects based on how dominant are their spatial patterns across all wafer maps. A chip defect is considered dominant, if: 1) it has a systematic defect pattern arising from a specific assignable cause and 2) it displays spatial dependence across a larger number of wafer maps when compared with other defects. The spatial dependence of a chip defect is determined based on the contiguity ratio of the defect pattern across wafer maps. DDPfinder uses the dominant chip defects to serve as seeds for clustering the patterns of defective chips. This clustering procedure allows process engineers to prioritize their investigation of chip defects based on the dominance status of their clusters. It allows them to pay more attention to the ongoing manufacturing processes that caused the dominant defects. We evaluated the quality and performance of DDPfinder by comparing it experimentally with eight existing clustering models. Results showed marked improvement.

Original Text (This is the original text for your reference.)

Clustering the Dominant Defective Patterns in Semiconductor Wafer Maps

Identifying defect patterns on wafers is crucial for understanding the root causes and for attributing such patterns to specific steps in the fabrication process. We propose in this paper a system called Dominant Defective Patterns Finder (DDPfinder) that clusters the patterns of defective chips on wafers based on their spatial dependence across wafer maps. Such clustering enables the identification of the dominant defect patterns. DDPfinder clusters chip defects based on how dominant are their spatial patterns across all wafer maps. A chip defect is considered dominant, if: 1) it has a systematic defect pattern arising from a specific assignable cause and 2) it displays spatial dependence across a larger number of wafer maps when compared with other defects. The spatial dependence of a chip defect is determined based on the contiguity ratio of the defect pattern across wafer maps. DDPfinder uses the dominant chip defects to serve as seeds for clustering the patterns of defective chips. This clustering procedure allows process engineers to prioritize their investigation of chip defects based on the dominance status of their clusters. It allows them to pay more attention to the ongoing manufacturing processes that caused the dominant defects. We evaluated the quality and performance of DDPfinder by comparing it experimentally with eight existing clustering models. Results showed marked improvement.

+More

Cite this article
APA

APA

MLA

Chicago

Kamal Taha,.Clustering the Dominant Defective Patterns in Semiconductor Wafer Maps. 31 (1),156-165.

Disclaimer: The translated content is provided by third-party translation service providers, and IKCEST shall not assume any responsibility for the accuracy and legality of the content.
Translate engine
Article's language
English
中文
Pусск
Français
Español
العربية
Português
Kikongo
Dutch
kiswahili
هَوُسَ
IsiZulu
Action
Recommended articles

Report

Select your report category*



Reason*



By pressing send, your feedback will be used to improve IKCEST. Your privacy will be protected.

Submit
Cancel