Recognition of defect spatial patterns in semiconductor fabrication-Reference-Cited by-同舟云学术

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Recognition of defect spatial patterns in semiconductor fabrication

Published:2004-10 Issue:19 Volume:42 Page:4153-4172
ISSN:0020-7543
Container-title:International Journal of Production Research
language:en
Short-container-title:International Journal of Production Research

Author:

Hsieh H.-W.¹²,Chen * F.-L.¹²

Affiliation:

1. a Department of Industrial Engineering and Engineering Management , National Tsing Hua University , Hsinchu, Taiwan, ROC

2. b Department of Industrial Engineering and Engineering Management , National Tsing Hua University , Hsinchu, Taiwan, ROC E-mail:

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207540410001716507

Reference14 articles.

1. A neural-network approach to recognize defect spatial pattern in semiconductor fabrication

2. FEATURE BASED DEFECT MAP PATTERN RECOGNITION AND CLASSIFICATION ALGORITHM

3. The use and evaluation of yield models in integrated circuit manufacturing

4. A cluster-modified Poisson model for estimating defect density and yield

5. Model-free estimation of defect clustering in integrated circuit fabrication

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1. Development of a spatial dimension-based taxonomy for classifying the defect patterns in a wafer bin map;Advanced Engineering Informatics;2024-04

2. Development of taxonomy for classifying defect patterns on wafer bin map using Bin2Vec and clustering methods;Computers in Industry;2023-11

3. An Active Deep Learning Method for the Detection of Defects in Power Semiconductors;2021 32nd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC);2021-05-10

4. A Review and Analysis of Automatic Optical Inspection and Quality Monitoring Methods in Electronics Industry;IEEE Access;2020

5. A Novel DBSCAN-Based Defect Pattern Detection and Classification Framework for Wafer Bin Map;IEEE Transactions on Semiconductor Manufacturing;2019-08

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