Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Jaewoong Shim"'
Autor:
Sungho Lee, Jaewoong Shim
Publikováno v:
IEEE Access, Vol 12, Pp 122684-122694 (2024)
Visual defect classification is a critical process in manufacturing systems, aiming to achieve high-quality production and reduce costs. Although deep learning-based defect classification models have achieved significant success, their performance ca
Externí odkaz:
https://doaj.org/article/b70d50eded504bc58038cdbff5f9073c
Publikováno v:
Journal of Process Control. 105:250-258
Manufacturing processes typically involves a number of inspections, including basic inspections for all products and advanced inspections for selected sampled products. The partial application of advanced inspections decreases processing time and cos
Publikováno v:
IEEE Transactions on Semiconductor Manufacturing. 33:258-266
Wafer maps provide important information for engineers for detecting root causes of failure in a semiconductor manufacturing process. Thus, there has been active research into the automation of wafer map pattern classification. With recent advances i
Publikováno v:
International Journal of Production Research; Jul2018, Vol. 56 Issue 14, p4849-4859, 11p
Autor:
Seokho Kang, Jaewoong Shim
Publikováno v:
Computers in Industry. 135:103572
Virtual metrology (VM) is a promising solution for wafer-to-wafer quality monitoring in the semiconductor manufacturing process. VM alternates physical metrology with a prediction model trained using previous metrology data. Active learning can be us
Publikováno v:
BigComp
There have been significant research efforts for developing decision tree (DT)-based ensemble methods. Such methods generally construct an ensemble by aggregating a large number of unpruned DTs, thereby yielding good classification accuracy. A recent
Publikováno v:
Computers & Industrial Engineering. 161:107632
The fault detection and classification (FDC) model is a prediction model that utilizes the sensor data of equipment to predict whether each wafer is faulty or not in the future, which is important to achieve a high yield and reduce the cost. To const
Publikováno v:
International Journal of Production Research. 56:4849-4859
In production data, missing values commonly appear for several reasons including changes in measurement and inspection items, sampling inspections, and unexpected process events. When applied to pr...
Publikováno v:
Computers & Industrial Engineering. 106:137-146
We propose a data mining process for failure analysis of industrial products.Failures are examined by a mashup of the production and customer service data.Interpretable visualization based on relative failure density is implemented.A case study is co