Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Plasma information-based virtual metrology (PI-VM) and mass production process control
by
Park, Yoona
, Kim, Gon-Ho
, Jang, Yunchang
, Park, Seolhye
, Jang, Yongsuk
, Seong, Jaegu
, Song, Jaemin
, Ryu, Sangwon
, Lee, Jinyoung
, Roh, Hyun-Joon
, Yang, Jae-Ho
, Noh, Yeongil
, Cho, Taeyoung
, Roh, Ki-Baek
, Kwon, Ji-Won
in
Accuracy
/ Algorithms
/ Control algorithms
/ Fault detection
/ Innovations
/ Machine learning
/ Manufacturing
/ Mass production
/ Metrology
/ Neural networks
/ Organic light emitting diodes
/ Physical properties
/ Plasma
/ Plasma chemistry
/ Plasma diagnostics
/ Process controls
/ Reaction kinetics
/ Semiconductors
/ Sensors
/ Sheaths
/ Statistical analysis
/ Statistical methods
/ Surface reactions
/ Technological change
/ Variables
2022
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Plasma information-based virtual metrology (PI-VM) and mass production process control
by
Park, Yoona
, Kim, Gon-Ho
, Jang, Yunchang
, Park, Seolhye
, Jang, Yongsuk
, Seong, Jaegu
, Song, Jaemin
, Ryu, Sangwon
, Lee, Jinyoung
, Roh, Hyun-Joon
, Yang, Jae-Ho
, Noh, Yeongil
, Cho, Taeyoung
, Roh, Ki-Baek
, Kwon, Ji-Won
in
Accuracy
/ Algorithms
/ Control algorithms
/ Fault detection
/ Innovations
/ Machine learning
/ Manufacturing
/ Mass production
/ Metrology
/ Neural networks
/ Organic light emitting diodes
/ Physical properties
/ Plasma
/ Plasma chemistry
/ Plasma diagnostics
/ Process controls
/ Reaction kinetics
/ Semiconductors
/ Sensors
/ Sheaths
/ Statistical analysis
/ Statistical methods
/ Surface reactions
/ Technological change
/ Variables
2022
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Plasma information-based virtual metrology (PI-VM) and mass production process control
by
Park, Yoona
, Kim, Gon-Ho
, Jang, Yunchang
, Park, Seolhye
, Jang, Yongsuk
, Seong, Jaegu
, Song, Jaemin
, Ryu, Sangwon
, Lee, Jinyoung
, Roh, Hyun-Joon
, Yang, Jae-Ho
, Noh, Yeongil
, Cho, Taeyoung
, Roh, Ki-Baek
, Kwon, Ji-Won
in
Accuracy
/ Algorithms
/ Control algorithms
/ Fault detection
/ Innovations
/ Machine learning
/ Manufacturing
/ Mass production
/ Metrology
/ Neural networks
/ Organic light emitting diodes
/ Physical properties
/ Plasma
/ Plasma chemistry
/ Plasma diagnostics
/ Process controls
/ Reaction kinetics
/ Semiconductors
/ Sensors
/ Sheaths
/ Statistical analysis
/ Statistical methods
/ Surface reactions
/ Technological change
/ Variables
2022
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Plasma information-based virtual metrology (PI-VM) and mass production process control
Journal Article
Plasma information-based virtual metrology (PI-VM) and mass production process control
2022
Request Book From Autostore
and Choose the Collection Method
Overview
In this paper, we review the development of plasma engineering technology that improves dramatically the production efficiency of OLED (organic light-emitting diode) displays and semiconductor manufacturing by utilizing a process monitoring methodology based on the physical domain knowledge. The domain knowledge consists of plasma-heating and sheath physics, plasma chemistry and plasma-material surface reaction kinetics, and plasma diagnostics. Based on this, a plasma information-based virtual metrology (PI-VM) algorithm was developed drastically enhanced process prediction performance by parameterizing plasma information (PI) which can trace the states of processing plasmas. PI-VM has superior process prediction accuracy compared to the classical statistics-based virtual metrologies. The developed PI-VM algorithms adopted for practical processing issues such as the control and management of the OLED-display mass production demonstrated savings of approximately 25% of the yield loss over the past 5 years. This improvement was achieved with the development of FDC (fault detection and classification) and APC (advanced process control) logic, which can be developed through the analysis of the physical characteristics of the feature parameters used in PI-VM with the evaluation of their contributions and their correlations to the processing results. PI-VM provides leverage that can be applied in the development of process equipment and factory automation technologies.
Publisher
Springer Nature B.V
Subject
This website uses cookies to ensure you get the best experience on our website.