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Smart Plant Approach to Increase Plant Profitability
Donald J. Chmielewski
Department of Chemical & Biological Engineering
Illinois Institute of Technology
Miguel J. Bagajewicz
Department of Chemical Engineering
University of Oklahoma
2009 Annual Meeting of the
AIChE
Nashville, TN
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Traditional Plant Operation
Plant Measured Data
Servo-
Loops
MPC
RTO
State
Estimator
Parameter
Estimator
Estimation Units
Set-points
Set-points
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Smart Plant Operation
Plant Measured Data
Servo-
Loops
MPC
RTO
State
Estimator
Parameter
Estimator
Estimation Units
Set-points
Set-points
Smart Plant
Supervisor
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Smart Plant Topics
• Scheduling and Supervision (Enterprise Wide)
• Fault Detection and Diagnosis (Plant Wide)
• Safe Parking and Emergency Management (Plant
Wide)
• Process Efficiency and Sustainable Operation
(Plant Wide)
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Motivating Example (Surge Tank)
q
q(sp)
FT
FC
qin
V
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Surge Tank Operating Scenario
q
q(sp)
FT
FC
qin
V
- Inlet flow (qin) is from a reactor and varies with time.
- Exit (q) to a separation unit which demands little variation.
- Tank should not over-flow or run dry.
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Surge Tank Operating Scenario
q
q(sp)
FT
FC
qin
V
- Inlet flow: qin = 30 3 m3/min.
- Exit flow q = 30 1 m3/min.
- Tank volume V = 10 10 m3.
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Open-Loop Operation
q
q(sp)
FT
FC
qin
V
- Inlet flow: qin = 30 3 m3/min.
- Exit flow q = 30 0 m3/min.
- Tank volume V = 10 10 m3.
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Open-Loop Operation
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
Vq
in
q
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Open-Loop Operation (Disturbance Scenario b)
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Open-Loop Operation
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
Vq
in
q
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
(disturbance a) (disturbance b)
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Closed-loop Surge Tank
q(sp)
FT
FC
q
qin
V(sp)
LT
LC
V
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Closed-loop Level Control Surge Tank
+ -
qGp(s)Gc(s) +
+
qin Gd(s)
VV(sp)
ssGp /1)(
ssGd /1)(
s
KsGI
cc 11)(
2c
c
K
2I c
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Closed-loop Level Control Surge Tank
+ -
qGp(s)Gc(s) +
+
qin Gd(s)
VV(sp)
s
KsGI
cc 11)(
2c
c
K
2I c
Tuning Scenarios:
Case 1: c = 1 min.
Case 2: c = 10 min.
Case 3: c = 50 min.
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Closed-Loop Operation (Case 1: c = 1 min )
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
Vq
in
q0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
Vq
in
q
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
Vq
in
q
Closed-Loop Operation (Case 1: c = 1 min )
(disturbance a) (disturbance b)
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Closed-Loop Operation (Case 1: c = 10 min )
(disturbance a) (disturbance b)
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
Vq
in
q
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Closed-Loop Operation (Case 1: c = 50 min )
(disturbance a) (disturbance b)
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
Vq
in
q
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Extreme Cases
(Over Regulated) (Open-Loop)
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Middle Ground
(Over Regulated) (Open-Loop)
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
(c = 10 min )
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
The Operator’s Plight
Possible scenario
• Shift starts with the following operation (c = 10 min).
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
Vq
in
q
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
The Operator’s Plight
• But, then the disturbance changes to
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
Vq
in
q
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
The Operator’s Plight
• Should the operator re-tune the controller?
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
(c = 10 min )
![Page 24: Smart Plant Approach to Increase Plant Profitabilitymypages.iit.edu/~chmielewski/presentations/2009/AIChE2009_Smart... · Smart Plant Approach to Increase Plant Profitability Donald](https://reader031.vdocuments.net/reader031/viewer/2022022503/5aaf110c7f8b9a3a038ceb4c/html5/thumbnails/24.jpg)
Department of Chemical and Biological Engineering
Illinois Institute of Technology
The Operator’s Plight
• Should the operator re-tune the controller?
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
(c = 10 min )
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
(c = 50 min )
![Page 25: Smart Plant Approach to Increase Plant Profitabilitymypages.iit.edu/~chmielewski/presentations/2009/AIChE2009_Smart... · Smart Plant Approach to Increase Plant Profitability Donald](https://reader031.vdocuments.net/reader031/viewer/2022022503/5aaf110c7f8b9a3a038ceb4c/html5/thumbnails/25.jpg)
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Operator’s Plight Re-Examined
• Broader perspective on the process will yield solution.
q(sp)
FT
FC
q
qin
V(sp)
LT
LC
V
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Operator’s Plight Re-Examined
• Broader perspective on the process will yield solution.
• Reconsider the separation unit downstream:
q(sp)
FT
FC
q
qin
V(sp)
LT
LC
V Separation
Unit
Nominal Throughput:
30 m3/min
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Operator’s Plight Re-Examined
• Broader perspective on the process will yield solution.
• Reconsider the separation unit downstream:
q(sp)
FT
FC
q
qin
V(sp)
LT
LC
V Separation
Unit
Nominal Throughput:
30 m3/min
Maximum Throughput:
31 m3/min
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Operator’s Plight Re-Examined
• Broader perspective on the process will yield solution.
• Reconsider the separation unit downstream:
q(sp)
FT
FC
q
qin
V(sp)
LT
LC
V Separation
Unit
Nominal Throughput:
30 m3/min
Maximum Throughput:
31 m3/min
Exit flow q = 30 1 m3/min.
![Page 29: Smart Plant Approach to Increase Plant Profitabilitymypages.iit.edu/~chmielewski/presentations/2009/AIChE2009_Smart... · Smart Plant Approach to Increase Plant Profitability Donald](https://reader031.vdocuments.net/reader031/viewer/2022022503/5aaf110c7f8b9a3a038ceb4c/html5/thumbnails/29.jpg)
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Operator’s Solution
0 10 20 30 40-5
0
5
10
15
20
25
30
35
time (minutes)
Ta
nk H
old
-up
(m
3)
or
Volu
metr
ic F
low
(m
3/m
in)
(c = 10 min ) • Reselect to the nominal
throughput.
• From 30 m3 / min
to 29 m3 / min
• Obtain guidance from
)( nom
design
nom
actual qqKP
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Operator’s Plight
V
EDOR
* *
OSSOP
3129
20
0
Original
Operating Point
q
![Page 31: Smart Plant Approach to Increase Plant Profitabilitymypages.iit.edu/~chmielewski/presentations/2009/AIChE2009_Smart... · Smart Plant Approach to Increase Plant Profitability Donald](https://reader031.vdocuments.net/reader031/viewer/2022022503/5aaf110c7f8b9a3a038ceb4c/html5/thumbnails/31.jpg)
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Operator’s Solution
V
EDOR
*
OSSOP
3129
20
0New BOP
q
*
![Page 32: Smart Plant Approach to Increase Plant Profitabilitymypages.iit.edu/~chmielewski/presentations/2009/AIChE2009_Smart... · Smart Plant Approach to Increase Plant Profitability Donald](https://reader031.vdocuments.net/reader031/viewer/2022022503/5aaf110c7f8b9a3a038ceb4c/html5/thumbnails/32.jpg)
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Operator’s Solution
V
EDOR
* *
OSSOP
3129
20
0
Original
Operating Point
q
V
EDOR
*
OSSOP
3129
20
0New BOP
q
*
![Page 33: Smart Plant Approach to Increase Plant Profitabilitymypages.iit.edu/~chmielewski/presentations/2009/AIChE2009_Smart... · Smart Plant Approach to Increase Plant Profitability Donald](https://reader031.vdocuments.net/reader031/viewer/2022022503/5aaf110c7f8b9a3a038ceb4c/html5/thumbnails/33.jpg)
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Operator’s Solution
V
EDOR
* *
OSSOP
3129
20
0
Original
Operating Point
q
V
EDOR
* *
OSSOP
3129
20
0
New BOP
q
![Page 34: Smart Plant Approach to Increase Plant Profitabilitymypages.iit.edu/~chmielewski/presentations/2009/AIChE2009_Smart... · Smart Plant Approach to Increase Plant Profitability Donald](https://reader031.vdocuments.net/reader031/viewer/2022022503/5aaf110c7f8b9a3a038ceb4c/html5/thumbnails/34.jpg)
Department of Chemical and Biological Engineering
Illinois Institute of Technology
Model Predictive Control
LT
q(sp)
V(nom)
MPC
q(no
m)
V FT
FC
q
FTqin
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Operator’s Perspective
• Disturbance characteristics will impact the controller’s ability to meet operational criteria.
• In some cases, adjustment of the controller (re-tuning) will recover performance.
• In other cases, only recourse is modification of nominal operating conditions.
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Impact on Smart Plant Operation
• Evolution of disturbance characteristics necessitates the ability to retune controllers.
• To enable such retuning, two technologies are needed:
1. A method to characterize disturbances.
2. A profit focused tuning method that is responsive to disturbance modeling.
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Department of Chemical and Biological Engineering
Illinois Institute of Technology
Profit View of Smart Plant Operation
Plant Measured Data
Servo-
Loops
MPC
RTO
State
Estimator
Parameter
Estimator
Estimation Units
Set-points
Set-points
Disturbance
Characterization
Reselection of nominal
operating conditions
Retuning
of
controller