PROCESS OPTIMISATION PROCESS OPTIMISATION usingusing

MODEL BASED CONTROLMODEL BASED CONTROLIN THE MELTERIN THE MELTER

“We have millions of dollars

invested in our plant…”

“…are we getting the mostfrom our processes?”

“We’re designing a complex integrated process…”

“…how do we know it’s going to work?”

“We have a complex control scheme…”

“…how do we know it will run our plant to it’s optimum efficiency?”

The Answer – The Answer – Adaptive Model Based ControlAdaptive Model Based Control

ADVANCED CONTROL SOLUTIONS INC

The way PID control worksThe way PID control works• Cannot easily control long dead time

processes • No action taken until process pushed off

target• Doesn’t respond well to non-linear processes• Can’t handle process disturbances quickly

Most PID control loops are detuned or not performing as intended because the loop is out of tune with the dynamics of the process

The result of poor PID The result of poor PID control:control:

• Increased process variability• Inconsistent product quality• Lower production rates• Higher energy costs• Decrease in overall plant efficiency• Leads to Acceptance of controlling what

you can – not what matters• Dependence on experienced operators to

manually run, start up, and recover critical processes

MBC out performs PIDMBC out performs PID

MBC out performs PID because of its two main components:

• An adaptive model

• A predictive controller

The MBC advantageThe MBC advantage• Integrates with existing control systems

• Average implementation time is less than 2 weeks

• Ease of use — customer can deploy and maintain with existing manpower

• Attractive project economics (Payback)

• Operates reliably 100% of the time

Adaptive Model Based Adaptive Model Based ControlControl

• Builds and adapts its own live models during normal plant operations– Models are built in closed loop while the plant

is running

• Patented methodology builds high fidelity models in real time without disrupting operations– This patented method is the key to our fast

implementation

• Models adapt as the dynamics change due to weather, wear, and other factors

predictive controllerpredictive controller• Accurately forecasts process responses

and accounts for multiple objectives• Predicts and prevents disturbances before

process is pushed off target– (PID cannot do this, PID must wait for the error)

• Start ups and grade changes are automated and uneventful

• Solves difficult process control problems• Achieves automatic control of manually

controlled processes

MBC runs where YOU decide, in MBC runs where YOU decide, in one or multiple placesone or multiple places

Ethernet

If you have OPC, you can run Model Based Control

MBC can run on your DCS or on its own server

MBC can simultaneously communicate to multiple PLCs

Ethernet, Modbus Plus, Data Highway Plus

DCSOperator Station

DCSEngineering Station

MBC SERVER

PLC

DCS Controller

Building the Adaptive ModelBuilding the Adaptive Model

The impact of improved control, closer The impact of improved control, closer upper and lower set point limitsupper and lower set point limits

Energy CostEnergy Cost

Productivity and YieldProductivity and Yield

Product QualityProduct Quality

Operating Average ShiftLow Set Point.Limit

OperatingAverage

Low Set Point.Limit

High Set Point.Limit

MBC ApplicationsMBC Applications• Glass melter

temperature• Glass furnace level• Channel

temperature• Forehearth

temperatures• 9 point grid

temperature

• Gob exit temperature

• Large Energy consumers

• Bottlenecks• Annealing oven• Bottle weight

ResultsResults

• Float Glass – Stabilize at new setpoint in 4% of the previous time.

• Fiberglass – huge reduction in variability and improved machine availability.

• Float Glass Level Control – reduction in variance.• Lighting Glass – Reduce Temperature

variation in Furnace and Forehearth.• Container – increase in line efficiency –

increase profit annually.

MBC How to set it up?MBC How to set it up?

• Installed on an NT desktop PC• Communication to Existing Control System

via Ethernet / OPC Server• Initial Models Developed from Historical

Data Review• Models validated with one setpoint change• Entire system installed and operational in

less than one week

MBC Results

Improved process dynamics Reduced level control variations Steady state control improved by 7X Scrap rates reduced Product change time reduced:

Product Changeover MBC vs PID

Glass Level Loop

-0.05

-0.04

-0.03

-0.02

-0.01

0

0.01

0.02

0.03

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0.05

1 51 101 151 201 251 301 351 401 451 501 551 601 651 701 751 801 851 901 951 1001

0

5

10

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25

30

35

40

45

BWC vs PIDLevel Sp Change

BWC Control PID Control

PV (Level)PV (Level)

BWC CV PID CV

5 min <------------------------------ 2 hours -------------------------->

Level Control – Steady StateLevel Control – Steady State

-0.04

-0.035

-0.03

-0.025

-0.02

-0.015

-0.01

-0.005

1 151 301 451 601 751 901 1051 1201 1351 1501 1651 1801 1951 2101 2251 2401 2551 2701 2851 3001 3151 3301 3451 3601 3751 3901 4051 4201 4351 4501 4651

Glass Level Loop - Steady State

PID ControlMBC Control (CV) MBC Control (CV)60 s sample

10s sample 10s sample

PV (Level) PV (Level)

Level Control - PIDLevel Control - PID

PID Control (Oct 21 99)

-0.5

-0.4

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Level Control-MBCLevel Control-MBC

Glass Furnace - Level, MBC Control

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1 11 21 31 41 51 61 71 81 91101111121131141151161171181191201211221231241251261271281291301311321331341351361371381391401411421431441451461471481491

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B

Container ApplicationContainer Application

• MBC installed and connected to existing Forehearth PLC or SLC control system

• Goal was to improve stabilization time in forehearths after pull / product change.

• Allow operators to focus on machine changes and control loops stay in automatic.

Container Glass ResultsContainer Glass Results• Forehearth Temperature stabilization time

reduced by 50% after job changes – leading to more machine availability at optimum conditions

• Ability to control using Mass Flow Temp (9-point grid as control parameter

• Ability to control using Gob Exit Temperature as control parameter

• Increased yield, 0.5 to 1% due to improved process stability.

Pull Change – conventionalPull Change – conventional

PID Control Performance

1120.00

1130.00

1140.00

1150.00

1160.00

1170.00

1180.00

1190.00

1200.00

1210.00

1220.00

0.0

00

0.3

00

0.6

00

0.9

00

1.2

00

1.5

00

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00

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00

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00

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00

5.1

00

Time (Hours)

Tem

pera

ture

(D

eg

C)

Rear

Front

Cond

Pull Change - MBCPull Change - MBC

AC Control Performance

1100.00

1110.001120.00

1130.00

1140.001150.00

1160.001170.00

1180.00

1190.001200.00

1210.00

0.0

00

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00

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Time (Hours)

Tem

pera

ture

(D

eg

C)

Rear

Front

Cond

Steady State ControlSteady State Control

PID-AC Control Comparison

1120.00

1130.00

1140.00

1150.00

1160.00

1170.00

1180.00

1190.00

1200.00

1210.00

1220.00

0.0

00

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00

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00

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00

Time (Hours)

Tem

pera

ture

(D

eg

C)

ACPID PID

Rear

Front

Cond

Fiberglass ManufacturingFiberglass Manufacturing

• Goal is to stabilize process & reduce variability in downstream processes.

• Level control in melt tank is primary cause of defects.

• MBC connected to existing DCS via OPC server.

Fiberglass ResultsFiberglass Results

• Profoundly stabilized system• Better bushing control• Reduced spinner blockage• Better quality• Higher production rates

Fiberglass Melter Fiberglass Melter TempTemp

Float Glass ProjectFloat Glass Project

• Major manufacturer of Flat/Float Glass

• Level control variability decreases product quality

• Installed to existing DCS• Commissioned in only 2 days• Immediate profound effect in

operation

Increased Glass Level Increased Glass Level StabilityStability

Melter Crown temperature Melter Crown temperature stabilitystability

Reduction In Exit Temp Reduction In Exit Temp VariationVariation

Float Glass - PIDFloat Glass - PIDPID Level Control

-15

-10

-5

0

5

10

15

2:17

:32

2:27

:18

2:37

:02

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2:56

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3:55

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:17

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:02

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:02

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5:32

:32

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5:52

:03

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6:11

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6:40

:48

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7:00

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:03

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Level (Thou)

Level Setpoint (Thou)

Feed Rate ()

Float Glass - MBCFloat Glass - MBCModel Based Control

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Level (Thou)

Level Setpoint (Thou)

Feed Rate ()

Float Glass ResultsFloat Glass Results

“The control continues to be excellent. We had a port failure Tuesday night that took the MBC offline. For the 8-10 hours that we were back in DCS control, our level control was +/- 0.015", while MBC was able to maintain +/- 0.002". I printed the 24-hour trend chart for that period showing MBC controlling for 7 hours, Bailey DCS for 10 hours, and back to MBC for the remaining 7 hours and the charts show a graphic picture of why we need MBC for controlling glass level in our furnace!” – Ernie Curley, QA Manager, Cardinal Glass – Portage, WI

TestimonialTestimonial

“In PID control, our level control was +/- 0.015", while MBC was able to maintain +/- 0.002”; the charts show a graphic picture of why we need MBC!”

Ernie Curley, QA Manager, Cardinal Glass

>7 times better level control with MBC

PID Level Control

BrainWave Level Control

Lighting Glass OptimizationLighting Glass Optimization

• Major manufacturer of Lighting Glass• Temperature Control Critical for proper

forming• Installed to existing TI PLC environment• Commissioned in only 1 week• Immediate profound effect in operation

Lighting Glass ResultsLighting Glass Results

•Dramatic Reduction in variability•Complete Automatic Control•Improved recovery from disturbances•Reduced operator workload•Reduced scrap•Increased profits

TestimonialTestimonial“MBC stabilized our toughest loops – ones we have spent countless hours working on .”

Steve HolmesSenior Process Controls Engineer

Bowater Newsprint

3535.5

3636.5

3737.5

3838.5

3939.5

40

11:5

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0Time

Ste

am

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ss

ure

(P

SI)

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70

Va

lve

Po

sit

ion

(%

)

BWC Control PID Control

Steam Valve

TestimonialTestimonial

“ This was something that could be done immediately with very little cost. And it did not require any outages; it was done on the run.”

Andrey PawelczakContract Engineer, Syncrude Canada

MeadWestvaco TestimonialMeadWestvaco Testimonial

“Reducing Lime Kiln temperature variability with MBC was easy and it reduced our fuel consumption over $400,000/year!” Our operators love it and rely on it for efficient operation.

Terry Canup, Process & IT Manager, MeadWestvaco

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08-Mar-0100:00:00

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Temp (degF) Fuel Flow (GPM) Prod Rate (TPD) ID Fan (RPM) Total NCG (acfm)

88% improvement by control with MBC

Before: +/- 90 degrees or more MBC +/- 5 to 10 degrees Saturday 27th October

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9:36:00 12:00:00 14:24:00 16:48:00 19:12:00 21:36:00 0:00:00

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BWC Ctrl Status Front End Temp (T/C) (degF) SP Front End Temp (degF) CV Fuel Flow x10 (Btu/hr) (btu)

FF1 Lime Prod Rate (TPD) FF2 ID Fan (RPM) FF3 NCG Flow Rate (ACFM)

NCG Flow

ID Fan

Production Rate

Prod rate=900

Prod Rate=1100

Prod Rate=1000