AEC/APC Symposium Asia 2023 Program*program schedule is subject to change.

ChairSpeaker

Affiliation

Opening Remarks from AEC/APC Asia

Hidetaka Nishimura

Renesas Electronics

Program Outline

Hidenori Kakinuma

Kioxia Corporation＜ONLINE＞Practical molecular, material and process design and process control
with artificial intelligence and machine learning

Hiromasa Kaneko

Meiji University

Paper#Title

Hitotsubashi Memorial Hall
9:15

Registration Starts / Door Open

9:45
Opening & Tutorial 1 Speech

9:45
9:50
9:55

9:50
9:55

Hirai Toshiya
KOKUSAI ELECTRIC

10:40

Tutorial-1

Session 1
10:40

11:00

11:00

11:20

11:20

11:40

11:40

12:00

12:00

13:00

Hisato Tanaka
Tokyo Electron

Takashi Kurosawa
Azbil

GX-018Smart Subfab Transformation using Context-Based Control

Holland Smith

INFICON

PTL-013

Unified Platform for detecting faults governed by Process Controls

Vishali Ragam

Applied Materials

DA-016

Mixed-type Defect Pattern Classifications

Takumi Maeda

University of Tsukuba

YM-009

Defective Wafer Map Classification for Unknown Patterns Using Image Generation
Model

Seima Sakaguchi

Mie University

Lunch Break & Supplier Exhibition
Keynote Speech

13:00

13:45

Hidenori Kakinuma
KioxiaKeynoteThe Future of Computing - Bits/Neurons/Qubits -Shintaro Yamamichi

IBM Research -Tokyo, IBMJapan

Hyung Joo Lee

Siemens EDA

Chuhua SongINFICON

Chihiro Matsui

The University of Tokyo

Session2
13:45

14:05

PTL-007

Machine Learning Based Virtual Metrology for Effective Process Control in High
Product Mix Manufacturing

14:05

14:25

PTL-019

RF sensing method to detect low open area end point

14:25

14:45

PTL-008

Comparison of Numerical Method with Prefixed Profile and Machine Learning-based
Method for Wet Etching Amount Prediction

14:45

15:05

DA-012

Population estimation of characteristic variation and its application to circuitsimulation for power transistors

15:05

15:25

15:25

15:45

Takahiro Tsuchiya
United Semiconductor
JapanTomoya Tanaka
Tower Partners
Semiconductor

DA-017

Haruka Fukumoto

ROHM Co.,LtdYumiko Miyaji

Sony Semiconductor
Manufacturing

Prediction of Defect Rate Using Machine Learning in Assembly Process

Supplier Exhibition / Coffee Break
Tutorial 2 Speech

15:45

16:30

16:30
16:50
17:10

17:30

17:30

17:50

17:50

18:00

Kenji Miyake
Office Miyake

Tutorial-2

Chiplet Integration Technology

Prof. Yoichiro Kurita

Tokyo Institute of Technology

Hiroyuki Kawazato

Shinwa Controls Co.,Ltd.

Session3
16:50

DA-011Intelligent motor valve with failure prediction feature

17:10

MEP-010Development of Versatile Fault Detection Using Image Sensors

DA-014

Anomaly detection of semiconductor manufacturing equipment by cluster analysis

PTL-015

Root Cause Analysis of Plasma Processes Perturbation using Optical Emission
Spectroscopy Signals with Modified Autoencoder

Hirofumi Tsuchiyama
INFICON

Shunichi Shibuki
Sony Semiconductor
Manufacturing

Takuya Sugiura

Renesas Electronics

Yuki Shiga

KOKUSAI ELECTRICCORPORATION

Jaehyeon Kim

Sungkyunkwan Univ.

Closing

Conference Room
18:00

18:30

18:30

19:20

19:20

19:30

Author's Interview

Koichi Sakamoto
Tokyo Electron

Reception & Supplier Exhibition
Best Paper & Student Award