1

MUSTHAVE

SHOULD

HAVE

COULDHAVE

2

Module # C Functions that need to be considered

for Batch Material Transfer Controls

presented by : Rodger Jeffery

company : Mettler Toledo

duration : 30 mins

3

BY FEEDING THE EXACT AMOUNT OF MATERIAL IN THE SHORTEST POSSIBLE TIME EVERY TIME

IN ALMOST ANY MARKET IN MOST APPLICATIONS WITH VIRTUALLY ANY MATERIAL

How does it improve manufacturing efficiency ?

4

Manufacturing Areas

• Batch

• Blend

• Formulate

• Dose

• Fill

Raw Materials

• Granules

• Powders

• Liquids

• Slurries

Primary Markets • Food & Beverage

• Chemical

• Specialty Chemical

• Pharmaceuticals

• Other Measurement

Tools • Scale Platform

• Load Cell systems

• Flow Meters

Where would it be applicable ?

5

Start Feed Stop Feed

Weight

Time

TargetWeight

StartingWeight

Fast Feed Cut Off

Feed Cut OffHistorical

PreactAND

Jog Mode

T1

• USE KNOWLEDGE OF PREVIOUS ERRORS • DEPLOY “BRUTE FORCE” ENGINEERING • TRY TO “THROTTLE” PROCESS VIARIABILITY• SLOW DOWN THE PROCESS

• USE KNOWLEDGE OF PREVIOUS ERRORS • DEPLOY “BRUTE FORCE” ENGINEERING • TRY TO “THROTTLE” PROCESS VIARIABILITY• SLOW DOWN THE PROCESS

T0 T2

T3

Jog

Historical Control of the Material Feed (Transfer) Phase

6

MUSTHAVE

SHOULD

HAVE

1. Managing the Material Transfer Phase

7

must-have functionmust-have functions

BASIC

should-have functionshould-have functions

BEST PRACTICES

Managing the Material Transfer Phase

8

Managing the Material Transfer Phase

# Scale

Devices

# Flow Meter

Devices

Max #

Devices

Max #

Materials

Q.i LITE

4 12 12 1000

Q.i 4 12 200 1000

DEMONSTRATION

2. “ SHOULD HAVE FUNCTIONS“ - for BEST PRACTICE

Historical Adaptive Pre-Act

Reasonableness checking

Slow Step Timer

Command states (status, error handling)

Material feed states (status, error handling, overflow)

Weigh/flow digital filtering

Diagnostics

Control Modes - Manual/Automatic control

Reset Capability

Estimated time to complete

Flow alarm management

1. “ MUST HAVE FUNCTIONS” - for MINIMUM OPERATION Material type (GIW, LIW) Control target management (fixed bias) Setpoint type (absolute, additive) Tolerance check Dump to empty (cut-off approach & setpoint) Pre-feed condition checks (stable scale, vessel

overflow) Post-feed check and report (for accurate & reliable

data) Drain time management Instrument zero shift management Interface driver for data between instrument and

controller Abnormal situation management

9

MUSTHAVE

SHOULD

HAVE

COULDHAVE

2. Optimizing the Material Transfer Phase - PAC

10

Start Feed Stop Feed

Weight

Time

TargetWeight

StartingWeight

DynamicSpill

Scale Reading

Actual Weight Fed

Historical Preact

• ACCEPT NATURAL PROCESS VARIABILITY• LEARN FROM THE PROCESS • ADAPT TO THE NATURAL PROCESS VARIABILITY• USE MODEL BASED - PREDICTIVE ADAPTIVE CONTROL

• ACCEPT NATURAL PROCESS VARIABILITY• LEARN FROM THE PROCESS • ADAPT TO THE NATURAL PROCESS VARIABILITY• USE MODEL BASED - PREDICTIVE ADAPTIVE CONTROL

Feed Cut Off

T0

Optimizing the Material Transfer Phase - PAC

11

must-have functionmust-have functions

BASIC

should-have functionshould-have functions

BEST PRACTICES

could-have functioncould-have functions

OPTIMIZER

Optimizing the Material Transfer Phase

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2. “ SHOULD HAVE FUNCTIONS“ - for BEST PRACTICE

Historical Adaptive Pre-Act

Reasonableness checking

Slow Step Timer

Command states (status, error handling)

Material feed states (status, error handling, overflow)

Weigh/flow digital filtering

Diagnostics

Control Modes - Manual/Automatic control

Reset Capability

Estimated time to complete

Flow alarm management

1. “ MUST HAVE FUNCTIONS” - for MINIMUM OPERATION Material type (GIW, LIW) Control target management (fixed bias) Setpoint type (absolute, additive) Tolerance check Dump to empty (cut-off approach & setpoint) Pre-feed condition checks (stable scale, vessel

overflow) Post-feed check and report (for accurate & reliable

data) Drain time management Instrument zero shift management Interface driver for data between instrument and

controller Abnormal situation management

3. “BENEFICIAL FUNCTIONS”- for BEST PERFORMANCE

Adaptive Predictive Feed Control (PAC)

Overlapping feed management

Instrument cross check maintenance

Group Feeds

Adaptive 2 Speed Feed

Data Management

Material Feed Records

Error Logging

Material Path SPC Reports

Configuration Logging

Optimizing the Material Transfer Phase

…measure, manage, control, reporting

DEMONSTRATION

13

D

V0

V1

Deceleration ForceDeceleration Force

Material insuspension is offsetby (part of) thedeceleration force

Material In SuspensionMaterial In Suspension

D

V0

V1

Material in suspension varies dependent on initial velocity (V0), flow

rate and distance

Scale/Filter LagScale/Filter Lag

Dependent on filter time lag and flow rate

F = Filter time lag

Start Feed

Weight

Time

StartingWeight

R(t) = Scale Reading

ActualWeight Fed

F

WLAG(t)

W(t) = QMAX t

Dependent on the material transmission characteristics of the valve

TECHNOLOGY BREAKTHROUGH

THE 4 COMPONENTS OF DYNAMIC SPILLTHE 4 COMPONENTS OF DYNAMIC SPILL

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SPILL

Flow QMAX

WLAG = QMAX • F

WSUSP = QMAX • g

WVLT = QMAX • KV

Total SPILL:Total SPILL (TS) = K 1 • QMAX + K2 • QMAX

2

NOTE: Total SPILL canbe negative

SUSPMAXDEC(1) WgQF -=·-=

)ADñ(52.2 /QF V3

MAXDEC(2)··-=

)Añ(62.2 /QTQFFF V2

MAXMAXDEC(2)DEC(1)DEC··-·-=+=

3. TECHNOLOGY BREAKTHROUGH

THE 4 COMPONENTS OF DYNAMIC SPILLTHE 4 COMPONENTS OF DYNAMIC SPILL

Simpler Engineering

+ Consistent Production

= Efficient Manufacturing

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PAC algorithms for almost any feed characteristic

Acceptable ProblematicTarge

t

Target

1 Speed Feed - K1 or K2 (in-feed model based predictive adaptive control algorithm)

2 Speed Feed - K1 or K2 (in-feed model based predictive adaptive control algorithm)

1 Speed Feed - Spill Only (pre-feed preact control algorithm)2 Speed Feed - Spill Only (pre-feed preact control algorithm)

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UNIONCARBIDE - UCAR

17

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1 3 5 7 9

11

13

15

17

19

21

23

25

27

29

31

Qi - MP1 (Vib 1) BLH MP1

-1

-0.5

0

0.5

1

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31

Qi - MP5 BLH

Recipe - 4 ingredients

Ingredient 2 Feeder 1 MP1 206 kg

Ingredient 5 Feeder 5 MP5 155 kg

Ingredient 6 Feeder 6 MP6 284 kg

Ingredient 9 Feeder 8 MP8 180 kg

Batch Cycle time improvements

PRE Q.i 320 seconds

POST Q.i 170 seconds

Feed Control improvements

PRE Q.i < 0.9 kg at 3 sigma

POST Q.i < 0.25 kg at 3 sigma

Capital Savings

Engineering Effort 30% less

Overall Cost 20% less

UNIONCARBIDE - UCAR

18

Level 4: MEDIUM to LARGE – Advanced to Complex Automatic (Q.i)

This Metamucil plant applied the Qi technology early 2004.

With the previous system operations had to adjust 25 batches a week due to deviations in material additions.

The control system was reengineered using Honeywell’s PlantScape controller and 8 Qi matrollers.

Material Feed deviations were reduced to the point that only 1 batch a week requires adjustment.

This is a 25 to 1 improvement that has had a very positive impact on operations.

This Metamucil plant applied the Qi technology early 2004.

With the previous system operations had to adjust 25 batches a week due to deviations in material additions.

The control system was reengineered using Honeywell’s PlantScape controller and 8 Qi matrollers.

Material Feed deviations were reduced to the point that only 1 batch a week requires adjustment.

This is a 25 to 1 improvement that has had a very positive impact on operations.

19

20000 LBs Crutcher

TDC 3000 Standard Dev

(LBS)

Qi Standard Dev

(LBS)Delta (LBS) % Delta

DumpHi K1 221.62 36.54 185.08 83.51%Dump Hi K2 221.62 33.71 187.90 84.79%A-RECYCLE 55.63 36.34 19.29 34.68%

AC BASE 64.95 59.86 5.09 7.84%CARBONATE 10.30 11.88 -1.59 -15.39%

PASTE K1 23.87 19.34 4.53 18.98%PASTE K2 23.87 13.27 10.60 44.41%

Sulfate 10.37 12.48 -2.12 -20.40%

5000 LBs PW1

BRIGHT 24 3.10 1.81 1.28 41.36%HOT WATER 6.37 3.85 2.53 39.62%

LVP 9.00 2.67 6.33 70.35%POLYACRYLA 18.48 3.05 15.43 83.49%WET RECYCL 23.54 3.89 19.66 83.49%

600 LBs PW2

LIQUID PEG 0.87 0.56 0.31 35.81%

Augusta ABC June 30 2004 Deviations from Target

An example of the improvements brought by the Qi can be found in the 2004 re-control of the Augusta ABC. The Augusta ABC was using the advanced predictive material deliver techniques in the form of an older Honeywell TDC3000 control application and doing quite well with control (Lbs. deviation from target as a % of full scale with over 500 samples used to derive one standard deviation) ranging from 0.05% to 1.11%. In May of 2004 the TDC3000 was replaced by a Rockwell application using the Qi. As can be seen in the table “Augusta ABC June 30 2004 Deviations from Target” the Qi offers significant improvement for many of the materials over the traditional methods with a range of 0.04% to 0.30%. It also shows that the previous TDC3000 system was doing very well on several materials without significant changes from the Qi. The values in italics and blue indicate at least a 0.05% change, note all were positive improvements. The black values show relatively little change, all 0.03% or less with any negative changes 0.01% or less which would indicate minor process variations.