transform your business with real-time analytics · possible returns with real-time analytics 26...

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Transform your business

with real-time analytics

ACOMPby

© 2018 Fluence Analytics - Proprietary

PRESENTATION TO:

GULF COAST CONFERENCE 2018

Application of ACOMP (Automatic Continuous Online Monitoring of Polymerization Reactions)

for Process and Quality Improvements Based on Real-Time Measurements in Polymerizations

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Sigmund Floyd and Michael Drenski

Business Development Advisor & CTO at:


COMPANY PROFILE

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• Started 2013 as spinoff from Tulane University

• 12 issued patents, 35 pending

• Operating in 600 m2 facility near Tulane

• Core team of 20 people (R&D, engineering, manufacturing,

field service, operations, BD)

• Technical Advisory Board (TAB) of world experts in

polymers and biotechnology

• Mission: developing Industrial Internet of Things (IIoT)

hardware, software and data products for chemical and

biopharma industries


TRANSFORM YOUR BUSINESS WITH REAL-TIME ANALYTICS

Reduce costs and

gain market share

Improve quality and

develop new products

Reduce waste and

environmental footprint

Streamline processes

and drive efficiencies

Cost

Quality

HSE

Efficiency

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Operator Control Lab Data

Plant Control System Plant Control Room

Off-line

Measurement =

“PAST” Data

QC Lab

MANUAL SAMPLINGReactor

INEFFICIENCY IN POLYMER MANUFACTURING

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COSTS OF INTERMITTENT (OR NO) DATA

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✓ Inconsistent batches

✓ Customer returns of

“shipped on-spec”

material

✓ Slow/ineffective scale-up

of new products

✓ Redundant lab work

✓ Hard to trace problems

to root cause

✓ Batch rework/losses

✓ Higher inventory

✓ Periodic write-offs of

dead stock

✓ Always “flying blind”

✓ Cannot see process

upsets till too late

✓ Reliance on PhDs for

modelling/intervention

Off-spec

Quality Deviations

Reduced Efficiency

Poor Control


Plant Control System

Plant

Control

Room

Optimized Operator Control

Processed

Data

Reactor Raw DataAnalysis

Software

OPTIMIZED PROCESS USING ACOMP

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Sampling

System

Analytical

Detectors

Smart

Sensors

Automation

Software


ONLINE POLYMER MONITORING: ACOMP

AC

OM

P

• Continuous reactor sample extraction of 0.05 to 2 ml/min

• Continuous measurement with typical delay of 30-300 seconds

• ACOMP does not require chromatographic columns

ANALYSIS

MONITORED

CHARACTERISTICS

• Molecular Weight

• Intrinsic Viscosity

• Composition

• Monomer Conversion

• Residual Monomer ppm

• Detection of process

anomalies

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CASE STUDY - POLYACRYLAMIDE

FREE-RADICAL POLYMERIZATION IN BATCH

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OPERATION BENEFITS WITH ACOMP - BATCH

Set-up

time

Set-up

timeReaction time without ACOMP

Reaction time with ACOMP

Viscosity

degradation under

excess reaction

time

Time →

Vis

co

sity →

On-spec and consistent in minimum batch time!10

Time

Saving


CASE STUDY – POLYACRYLAMIDE

Time (hours)

Reduced V

iscosity

(cm

3/g)

Monom

er

Concentr

atio

n (

ppm

)

ACOMP data:

- Viscosity

- Residual Monomer

Residual

Monomer Spec0 1 2 3 4 6 75

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Tighter Quality

Cost savings

Reaction stop based on ACOMP data = = Reaction stop based on Lab Data

Lab data:

Viscosity

Residual Monomer


CASE STUDY – CONDENSATION POLYMERS

BATCH REACTIONS OF A WIDESPREAD ENGINEERING PLASTIC

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MONITORING OF A STEP-GROWTH POLYMERIZATION

• RI signal is very sensitive to oligomer formation and plateaus at a certain

degree of polymerization (about 10 in this case)

• Reduced viscosity (measured directly from viscometer) is not sensitive to

oligomer formation but starts to increase once high MW polymer is formed13


KINETICS OF MULTIPLE REACTIONS

• These 3 reactions were at nominally the same reaction conditions

• The RI trace is highly sensitive to kinetic variations caused by unknown

variables – very useful for process troubleshooting!

Reaction 1

Reaction 2

Reaction 3

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USING ACOMP TO TRACK ONSET OF GELATION

• Light scattering is very sensitive to formation of high molecular weight

species, and consequently can be used to predict the onset of gelation

• Compare the experiment on left where Mw approaches a plateau with

experiments on right, where an abrupt increase in Mw indicates gelation15


CASE STUDY: ADHESIVES

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Reactants EA (solvent) 2-EHA Acrylic Acid AIBN

Poly2EHA 250g (278 ml) 74g (83 ml) 0 0.3g

Poly2EHA-AA 250g (278 ml) 68g (77 ml) 5.85g (5.6ml) 0.3g

ACOMP detectors – what they do:

UV-Vis

➢ 4 wavelengths at 260, 270, 290, 310nm

➢ Measure total monomer and polymer

concentrations

DRI

➢ Corroborates polymer concentration

Viscometer

➢ Provides intrinsic/reduced viscosity

Multi-Angle Light Scattering

➢ Weight-average and instantaneous MW

Reactor

Temperature: 60˚C

Recirculation: 20ml/min

ACOMP Front End

Solvent: EA Dilution: 150X

ACOMP Detectors

Flow rate: 2ml/min

POLY-2EHA AND POLY-2EHA/AA CHEMISTRY

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REAL-TIME MONITORING OF REACTION KINETICS

Figure 1 Raw UV, LS and Viscosity data

2EHA homopolymerization

Figure 2: Raw UV, LS and Viscosity data from 2EHA and AA

Copolymerization reaction

• 8 wt% acrylic added into 2-ethylhexylacrylate causes a significant impact on the reaction kinetics

and molecular weight

• ACOMP was used to monitor these effects providing useful information for reactions, which would

present an opportunity to compare from recipe to recipe

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MONITORING REACTION KINETICS OF A POLYURETHANE

Started IPDI 0.1 ml/min

Increased IPDI

0.2 ml/min

Stopped Flow

r=0.997

Polymerization of isophorone diisocyanate (IPDI) with ethylene glycol (EG)


CASE STUDY – CONTINUOUS PROCESS

OPTIMIZATION

EPDM RUBBER EXAMPLE

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CASE STUDY: CONTINUOUS PROCESS OPTIMIZATION

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0

10

20

30

40

50

60

70

80

90

100

0 50 100 150 200

TimeP

ropert

y (

eg

. M

oone

y)

In-spec (time saving)

Potential for shorter grade transitions

Know when product

goes out of prior spec

Concept illustration with

discrete samples (EPDM)

(Lab)

(ACOMP)

1-hour

delay

- ACOMP Measurement- Real Process • Lab Measurement


LAB ACOMP

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• Intended for monitoring at bench/pilot scale

• Can be set up to run multiple chemistries and

applications

• Reporting and graphical interfaces tailored for

scientists

• Can be supplied with reactor and/or control system

• Fits inside a typical laboratory hood

• Optionally, can be integrated with GPC or other

instruments


CASE STUDY: ACRYLAMIDE MOLECULAR WEIGHT

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• Data from 3 ACOMP runs shows Mw

measured by light scattering vs. conversion for acrylamide in batch reactions with different amounts of persulfate initiator

• Can optimize conversion and initiator quantity based on required molecular weight

• Can instantly visualize reaction conditions for different Mw grades

• To get comparable information using offline measurement, would have to run at least 3X the number of experiments!

T= 60C

[Persulfate]/[Aam] (M/M)

0.006

0.025

0.100

Dots are GPC data

from aliquots withdrawn

during the reaction


A DESIGNED POLYMER EXAMPLE: INDEPENDENT

CONTROL OF MW AND COMPOSITION IN COPOLYMERS

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Fss Target Trajectory Fss

Mw Target TrajectoryMw

• Data for copolymerization of

acrylamide and sodium styrene

sulfonate (SS) where ACOMP was

used to produce a trimodal composition

distribution at near-constant MW

• This was achieved by manipulating the

feed flow rates of the two monomers to

the reactor in a one-shot experiment

• Virtually impossible to do without

ACOMP! Would have a run a very

large number of experiments!


ACOMP VERSATILITY – FOR YOUR PRODUCTS TODAY & TOMORROW

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Batch

Semi-batch

Continuous

Solution

Bulk monomer

Emulsion

Inverse

emulsion

}

Process Industrial*includes feedback control

Acrylamides*

Acrylates

Acrylic acid

Cellulosics

Glycols

Methacrylates

Methacrylamides

Phenylenes

Phenyl ethers

Polyelectrolytes*

PVP

Styrenics

Urethanes

Coming Soon:

EPDM

SSBR

PC

Polyester

Polyolefins

PVAc

Silicones


POSSIBLE RETURNS WITH REAL-TIME ANALYTICS

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Batch/semi-batch process

Ex: 20kt plant, $50m sales

• Cycle time reduction –

up to $1M+

• Better product consistency

• Energy savings

• Less manual sampling

Continuous process

Ex: 60kt plant, $150m sales

• Off-spec reduction –up to $1M+

• Improved process control = tighter specs

• Reduce lab analytics

• Less manual sampling

New

products

Improve

quality &

consistency

Free up capacity,

reduce or eliminate lab

analytics, improve yield,

mitigate process upsets


Polymer Manufacturing

Inputs(monomers, solvents,

catalysts, etc.)

Processors and End

Uses

Real-time Product

Data

Process Data

Process Control

Advanced Correlation &

Modeling

Knowledge and AI

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VISION FOR DYNAMIC MANUFACTURING OPTIMZATION

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Plant Control System

Closed Loop Control

Polymer

Property

Data

Reactor Raw DataAnalysis

Software

VISION FOR AUTOMATED CLOSED LOOP CONTROL ENABLED BY ACOMP

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Sampling

System

Analytical

Detectors

Smart

Sensors

Automation

Software

Modeling & Control

Algorithms

Process Data & Variables


SEE WHAT IS HAPPENING…

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NOT WHAT HAPPENED!


THANK YOU!

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transform your business with real-time analytics · possible returns with real-time analytics 26...

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