1. Qin Group Research Highlights: Process Monitoring and Control
S. Joe Qin
Department of Chemical Engineering
The University of Texas at Austin
Austin, Texas 78712
CPE5.408

2. Mizushima Plant from Mitsubishi Chemical
Area：2.100 k㎡
Start of production： 1964
ETY Plant Capacity： 450 kt/year
Number of Plant ： 61
Number of Controller：5500 loops
Information Media Plant
Tyugoku Electric
MCRC
Petrochemical Plant
Tank yard
Future area
ETY Plant
Japan Energy
Asahi Chemical
© S. Joe Qin

3. Advanced Process ControlLC TC F V D L B xD xB AI
Advanced
Control System u1 u2 y2 y1 d1
Distillation Column Control
Advanced Process Control
Constraints:
Objective Function:
present
improve
control performance
optimization
Courtesy of Mitsubishi Chemical (M. Ogawa)
© S. Joe Qin

4. Control Hierarchy Model Predictive Control (MPC) Or Multi-loop Control
Global Steady-State
Optimization
(every day)
Plant-Wide Optimization
Fab-wide control
FWET
Local Steady-State
Optimization
(every hour)
Unit Level Optimization
Module Level Optimization
SWET
Dynamic
Constraint
Control
(every minute)
Model Predictive
Control (MPC) Or
Multi-loop Control
Tool level
Run to Run Control
Integrated Metrology
Supervisory
Dynamic
Control
(every minute)
Basic Dynamic
Control
(every second)
In-situ sensors
Distributed Control System
Within-tool process control FC PC TC LC FC PC TC LC
© S. Joe Qin

5. Device Modeling - Flash Memory Transistor
                                                      
Device Modeling - Flash Memory Transistor
Contains floating gate not present in traditional MOS transistor
Non-Volatile Memory Capability
Programming : Apply + Voltage
Floating gate fills with electrons
Threshold voltage increases
No current between source and drain: “Off” State
Erasing : Apply - Voltage
Electrons flow from floating gate to drain
Threshold voltage decreases
Current flows: “On” State
© S. Joe Qin

6. Modeling and Control Focus
Conventional control problems
Process/quality monitoring
Process modeling
Feedback control
output
input
quality
Quality modeling
Quality control $
Semiconductor process modeling
Batch control
geometry
recipe
Semiconductor control problems
Device modeling
Fab-wide control $
electrical property
© S. Joe Qin

7. Our Research Focus Model Predictive Control and Performance Assessment
Process Monitoring and Fault Diagnosis
Model and System Identification
Semiconductor, Chemical and Pulp and Paper Processes
We interact actively with the members of the Texas-Wisconsin Modeling and Control Consortium which allows us to focus on methodology development that will impact the practice
© S. Joe Qin