CSI 2016: April 27-28, 2016
CONTINUOUS DIGESTER OPTIMIZATION
USING ADVANCED PROCESS CONTROL
Abhijit Badwe
ABB Pulp & Paper Control Systems Tech. Centre, Singapore
© ABB
May 2, 2016
| Slide 1
Continuous Digester Advanced Control
Outline
•
Challenges in continuous cooking
•
Conventional approaches to control
•
Need for multivariable control
•
Advanced control for continuous digesters: OPT800 Cook/C
•
Case Study: Implementation of OPT800 Cook/C
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| Slide 2
Pulp Mill Operation
Challenges in Continuous Cooking
•
Variations in raw material
•
Production rate changes
•
Large transport delays
•
Complex nonlinear dynamics at low Kappa numbers
•
Infrequent Kappa measurements (every 15-20 min)
•
Assumed blow consistency
•
Chip level variation results in varying degrees of cooking
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| Slide 3
Digester Kappa (end-point) control
Conventional approach
Supervisory control
Challenges:
© ABB
May 2, 2016

Large time delay

Infrequent blow line
Kappa measurement

Non-linear process
interactions

Chip-size, packing
density and raw
material variations

Seasonal variations
| Slide 4
Digester chip level control
Conventional approach
Supervisory control
Challenges
© ABB
May 2, 2016

Blow flow as Primary
Manipulated Variable

Estimated blow
consistency

Varied Digester bottom
conditions

Variations in chip
retention time
| Slide 5
Continuous Digester Control
Need for a multivariable control approach
•
Kappa number affected by H Factor and Alkali/Wood ratio
•
Chip level affected by multivariable effects from:
•
•
Chip meter speed
•
Blow flow
•
Bottom dilution flow
•
Scraper speed
Conventional approaches are usually univariate.
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| Slide 6
Model Predictive Control (MPC)
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| Slide 7

Systematic method for solving
multivariable problems

Main ingredients

Process model

Constraints

Objective function

Model predicts system behaviour
some steps into the future

Solves optimization problem at
every sampling time
Digester mid-point Kappa Control
Model Predictive Control
Kappa MPC control
•
ANN model for mid-point
Kappa (soft sensor)
•
Pulp tracking module:
tracks key process
variables throughout
digester
•
Blow line Kappa used for
output bias correction
•
REA (residual alkali)
control to the target
© ABB
May 2, 2016
| Slide 8
Digester chip level control
Model Predictive Control
MPC for Level control
Model Predicative Control

Actively manipulate
scrapper speed

Blow consistency (soft
sensor)

Ensure stable fiber
discharge (blow flow
variations minimized)

Stabilize chip column
movement to provide
uniform cooking
conditions

CMM – constraint
Management Module
© ABB
May 2, 2016
| Slide 9
OPT800 Cook/C
Continuous Digester Advanced Process Control System
OPT800 Cook/C
Constraint
Management
Module
Soft Sensor
Model
Predictions
PVs
PVs
PVs
Operator
Displays
Dynamic
Constraints
Model
Predictive
Controller
Tracking
Function
Operating Parameters
CV Targets
Optimized Setpoints
PVs
DCS
Continuous Cooking Process
© ABB Group
| Slide 10
May 2, 2016 | Slide 10
PVs Process Variables
Tracked Measurements
Soft Sensor Measurements
OPT800 Cook/C
System Architecture using 800xA APC platform
Engineering Station
Process Portal Client
Operator HMI
• MPC faceplates
• MPC tuning
• Process graphics
AC800 Connectivity
Servers
800xA Model Builder (off-line)
• Off-line Engineering tool kit, for
Model Identification, Controller
Tuning, and Simulation
Aspect
Servers
IMP Run time Engine
• Kappa Inferential measurement
AC800M Run Time Components
• PPOptCook/C CoreLib
• PPOptCook/C TemplateLib
• Control connections to sensors and PID’s
AC800M
800xA APC Interface Lib
Remote I/O
© ABB Group
| Slide 11
May 2, 2016 | Slide 11
Field
Devices
800xA Run Time Components
• APC Afw service
• APC engines / algorithms
• MPC Control Applications
• Kappa
• Level
Case study : Mondi Swiecie, Poland
Digester Advanced Process Controls
APC improves digester operations in Mondi

Located in Northern Poland

Pulpmill with 2 Fiber lines, 4 Paper
Machines

Project scope

Replace measurex DCS system

OPT800 Cook/C for both lines

© ABB
May 2, 2016
‒
Kappa MPC control
‒
Level MPC control
OPT800 Wash for both lines
| Slide 12
‒
Conductivity controls at each
stage
‒
Dilution Factor control
Case study : Mondi Swiecie, Poland
APC Methodology
Implement
Diagnose
Step 1:
Diagnose
Sustain
Step 3:
Sustain
Step 2:
Implement
Service
• Control Loop Audit
• Analysis, Findings
• Action plan
Process
Fingerprint
© ABB
May 2, 2016
| Slide 13
Service
Pulp
Tracking
• Chip Bin
• Impregnation
Vessel
• Digester Vessel
• Blow consistency
• Kappa model
• Install IMP
• Data collection
Soft Sensor
Models
MPC
• Kappa MPC
• Dig level MPC
• Step Test
• Develop models
• Deploy MPC
• Performance Test
• Case Study
• Success Story
Results
Report
Performance
Monitoring
• Quarterly Audit
• Benchmarking
results
• ServicePort
Case study : Mondi Swiecie, Poland
Digester APC Overview
Operator overview
APC display
Faceplates
Switch APC and
Supervisory mode
© ABB
May 2, 2016
| Slide 14
Case study : Mondi Swiecie, Poland
Mid-point Kappa control
Results before & after APC implementation
Performance test run results
Kappa variability reduced by 56.4%
Blow Kappa
Test Run
Average Upper Lt Lower Lt Sigma
% results
Before APC
88.86
89.00
85.00
3.68
36.8%
After APC
87.93
89.00
85.00
1.61
71.4%
Improvements
0.93
2.08
94%
Before APC
After APC
© ABB
May 2, 2016
| Slide 15
% of data within Limits
% of Data within Limits
36.8%
71.4%
56.4%
Case study : Mondi Swiecie, Poland
Residual Alkali control
Results before & after APC implementation
C12 Residual Alkali
Variability reduced by 48%
O v e r la y C o lu m n C o m p a r is o n
T w o S ig m a C o m p a r iso n
C o lu m n s = 2 , P o in ts = 4 5 6 1
C 1 2 R e A lk a li_ B e fo r e A P C
Po in ts = 4 5 6 1
C 1 2 R e A lk a li_ A fte r A P C
C 1 2 R e A lk a li_ B e fo r e A P C
14
C 1 2 R e A lk a li_ A fte r A P C
1 .2 5
13
1 .0 0
11
2 S ig m a
R e s A lk a li
12
10
9
8
48 %
0 .7 5
0 .5 0
7
0 .2 5
6
5
0 .0 0
0
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May 2, 2016
500
1000
| Slide 16
1500
2000
2500
D a ta P o in ts
3000
3500
4000
4500
C 1 2 R e A lk a li_ B e fo r e A P C
C 1 2 R e A lk a li_ A fte r A P C
1
1 .3 2 7 7 0 4 2
2
0 .6 4 7 9 4 3 3
Case study : Mondi Swiecie, Poland
Digester chip-level control
Results before & after APC implementation
Dig chip level - 5 days trend
40% reduction in 2-Sigma
Trend captured from customer historian while
commissioning OPT800 Cook/C for digester
T w o S i g m a C o m p a ri s o n
Po i n t s = 4 5 6 1
D ig lv l_ B e fo r e A P C
D ig L v l_ A fte r A P C
APC OFF
APC ON
D ig C h ip L e v e l
25
40%
20
15
10
5
0
D ig lv l_ B e fo r e A P C
D ig L v l_ A fte r A P C
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May 2, 2016
| Slide 17
1
2 6 .6 7 2 5 8 8 3
2
1 6 .1 3 2 9 8 2 3
Case study : Mondi Swiecie, Poland
Results: Digester chip-level control
Results
•
Stable blow flow
•
Lower variations in
production rate MV
(measured)
•
Improved cooking
conditions
•
Stabilized downstream
washing process
© ABB
May 2, 2016
| Slide 18
Stabilized digester operations - blow flow
Customer Testimonials
•
Mr. Tomas Katewicz (Member of Management Board & Production Director)
“…through their (ABB) APC, new and effective solutions have been implemented which are
stabilizing strongly the processes of the cooking and pulp washing lines.”
•
Mr. Wojciech Jazdziewski (Pulp Mill Assistant Manager)
“ We do believe that the implemented MPC system will allow us to increase production output in a
stable way, whereas the high quality parameters of pulp will remain unchanged.”
“ I would like to express our appreciation to ABB for implementation and successful start-up of APC
for two production lines at Mondi Świecie S.A.”
•
Senior Operator (more than 20 years at Mondi)
“ I have never seen in my life the chip level stabilize so beautifully.”
© ABB
May 2, 2016
| Slide 19
Happy Customer
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Group |
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Month DD, Year
| Slide 20
Contact information
If you have further questions, please contact me at:
Presenter
: Abhijit Badwe
Company
: ABB Pte Ltd
Contact phone : (+65) 9665-9947
Contact e-mail : abhijit.badwe@sg.abb.com
© ABB
May 2, 2016
| Slide 21
© ABB
| Slide 22