Process Analytics: Improving Measurement Capability in your Plant

AIChE Meeting: Nov. 17, 2009

Steve WrightProcess & Environmental Analytics

Eastman Chemical Company

Overview of Presentation

Introduction Sampling Theory – Why Analyzers? Process Analyzers and Sensors Sampling Systems Ownership and Maintenance Summary and Q&A

Introduction

Process Analytics is the

• Analytical Measurement of Chemical Composition Chemical Properties

of a Chemical Production Stream

• Using one, or more, of four approaches In-Situ / In-Line Extractive At-Line Ambient Detection

100ppm

100ppm

Eastman Process Analytics: Kingsport

Almost 2000 Process Analyzers and Chemical Sensors Personnel: 41 chemists, engineers, techs and analysts. Support: 24x7 where needed. Responsibilities include:

• Analyzer consultation/ specification

• Analyzer system design/purchase

• Sample system construction

• Installation/checkout

• Preventative maintenance

• Reactive maintenance

• Analyzer succession planning

Why Analyzers?

Measurement & Control

MEASUREMENT

CONTROL

Can’t do one without the other..

Majority of Process Measurement Tasks Can be Done Using Simple Sensors or Lab Analyses

Pressure, Temperature, Flow, Mass Lab measurements – slow and steady processes..

For the exceptions – process analytics..

Traditional Reactor Sampling Path

Insert Break

LabQueue

EnterSampleOrder

Ye Olde Bucket/SpigotWait for Truck

Wait for Truck II

GC Results

Sample Point

Create Report

Results!

InsertLunch

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GARBAGE ZONE

Under-Sampling (Aliasing)

Comfort Zone – >4F to “over-sampling”

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Meeting Nyquist.. Just barely

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Sampling Okay – but it’s breaking the bank..

LAB $$$$$$$$$$$$$$$$$$$

Transitioning from Product A to Product B

How long can we continue making “Good A”And when can we call “Good B”?

Good Measurement canLead to Great Processes

100%

0%

?Good A Good B

??

Time

Target Time

Late

EarlyEarly Error Lead

Late ErrorLag

Time

Pro

cess

Var

iabl

e

“While we’re here, let’s savetime & take the next sample”

“Just trying to keep up”

Input Lead/Lag Control Complexities….

Variability Complicates it even More…

Crew 1 is timely..Crew 2 isn’t..

Processtrend

Sample Time-Stamping Errors

Early Late

Good Measurement canLead to Great Processes

A B at 70 deg C 0-100% in 20 minutesA B at 20 deg C 0-100% in 640 minutes

While waiting 2 hours for analysis 20% change!!!

TwoHours

70 deg C20 deg C

% Completion

60% 80%

The Reaction Continues…

Models

Ultimate process understanding “victory” Control process with lean measurements, T, P, flow, etc. “As good as their input data” Model response surface must be well-defined Models tend to perform best in “known territory”

• Prediction weakness can occur during critical times: Upsets Start-Ups/Shut-Downs Product transitions

Direct measurement benefits• Often easier to set up and maintain than complex models

• Full process interaction / understanding is not required to measure

• Output can help build better models!

“The Wall” “The Wall”

Loose measurement& control – broad processperformance

Tight measurement& control

“Wall” = > Impurities, lower value product, permits, safety issues, etc.

Run Closer…

Value Proposition

Process Analyzers & Sensors

Fixed or Dedicated Systems Transmitter Style

oSimple to installo Low costoCan be used as “cheap” analyzers

- If high accuracy not required- Inferential

oExtractive sampling of processes

- Addition of flow cells and sample systemoDirect Insertion

Alan Hensley, 2009

Ambient / Area Point Monitoring

Personnel Protection Leaks or Spills

ElectrochemicaloToxic Gases

• Hydrogen sulfide

• Chlorine dioxide

• Carbon monoxideoOxygen

• % levels

• Oxygen deficiency

• High oxygen in processes

Alan Hensley, 2009

Area / Point Monitoring Combustible Gases

oNormally report values in terms of % of lower explosive limit (LEL)

oNot specific to gas – detect hydrocarbonsoCatalytic sensor

• Combust the sample

• Require oxygeno Infrared sensor

• Can be used in oxygen deficient or inert environments

• Where “poisoning” of catalytic sensor is of concern

Alan Hensley, 2009

Liquid Analytical pH & Conductivity

oSumps / Pure Water / Condensate & Discharges

• Material release

• Quality

• ContaminationoProcess

• Inferential composition measurement

• pH control for reactions / batch processes Dissolved Oxygen

oWastewater Treatment

Oxygen

Fuel Cell % and ppm level measurements

Paramagnetico% level measurementsoOxygen level in nitrogen convey systems

Zirconium OxideoStack monitoringoHandle dirty environmentsoHigh temperature operation

Alan Hensley, 2009

Physical Property Density (not just for mass flow)

o Inferential Composition MeasurementoDepends on process stream

TurbidityoContamination

ViscosityoProcess Control

Alan Hensley, 2009

Fixed or Dedicated Systems

Traditional StyleoAnalyzer is remote from areaoExtractive sampling with sample systemoHigher costoHigher complexityoRequire more care and feedingoStream ComplexityoAccuracyoSpecific

Photometric MethodsPhotometers UV/NIR/Non-dispersive IR Use specific wavelengths = 1 or 2 components Solids: non-contact

o% moisture Gases

oCO, CO2, NOx, SO2 Liquids

o% water, % organic acids

Alan Hensley, 2009

1100 1300 1500 1700 1900 2100 2300

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Process Analyzer Availability

If it can be done in the lab, it can installed on-line.• Up-Front cost issues / ROI

• Sample handling issues

Our group will build it if we cannot buy it.• Integration tasks, sample handling systems

• Panel Shop in B-359A

FRONT VIEW

Sampling Systems

Maintenance

Goals

Representative Sampling / Minimal Handling• Want sample to mirror process content

• Minimal interaction with sample

• Minimal sampling delays

Sample Compatibility with Analyzer Specifications• Temperature

• Pressure

• Flow

• Viscosity

• Particulates / Bubbles

• Materials Compatibility

In-situ Measurement

No sampling system• Pipeline/tank/line insertion

• No delay – real time results

Probe design Probe can be removed for cleaning – usually.

• Exceptions would be high pressure / temperature applications

Representative! Passive? Yes.

Extractive Sampling Systems

0-10gpm 0-0.5

gpm

RapidBypassLoop

Filter

DP

Flow Integrity Monitor

Analyzer

SampleLoop

Extractive Sampling Systems

Sample stream removed from main process line Advantages

• Allows isolation from process (cleaning/calibration)

• Filtration, dilution, P/T manipulation

• Improved safety – block/bleed

Difficulties• Must have dP across sample loop - or

• Sample pumping

• Delays

• Returning altered material to process or waste

• Filtration maintenance – when needed

Process Analyzer Maintenance

Ownership Cycle..

Development

Purchase

Installation

Start-UpMaintenance

Improvement

Replacement

70-90%Cost of Ownership

Maintenance is major cost of analyzer installation – process GC example

Reliability Maintenance Approach

Reliability – in degrees..• Ideal

Lasts forever, accurate and precise – cheap to own too.

• Reality (March to Entropy) Machine components wear out Unusual, unexpected events happen

• Goal Want capable function whenever machine is needed

• High Availability Uptime.

Want ownership at lowest possible cost. Reliability-Centered Maintenance Approach

Maintenance Categories

Reactive (RTF)• Appropriate for ultra-high reliability, low criticality systems

• Cheapest / Most Expensive approach – feeling lucky?

Preventative (PrM)• Process analytics use PrM

• Shewhart control charts (+/- 3 sigma, run of eight)

• Scheduled benchmarking visits

Predictive (PdM)• Maximum system availability at minimum cost.

• Relies on obtaining detailed history at component levels.

• We now have tools in-place to transition to PdM where needed.

pH 4pH 4

pH X.XXpH 3.95pH 4.15

Analyzer Benchmarking

Apply standard of known concentration to analyzer

Read analyzer response Compare response to standard response

Within control limits:• Note response, add to control chart

• Walk away, just walk away…..

Outside of control limits, or eight either side of average:

• Note response, add to control chart

• Calibrate analyzer / determine cause / log

Avoids human tendency to over-control, chasing system noise. Much better for process stability.

pH 4.0

pH 3.9

pH 4.1 +3s

-3s

Target

pH 4.00

pH 4 StandardBuffer Solution

Process Analyzer Maintenance

Effective PrM has greatly improved reliability of our analyzers• High availability up-times

• Analyzer data can be trusted for monitoring & control

Productivity (analyzers/analyst) has greatly improved over the last 20 years• Better analyzer technology

• Better diagnostics

• Scheduled PrM

• Improved tools such as OSI PI

Questions & Answers

Thanks!

• Steve Wright

• Senior Development Associate

• Process and Environmental Analytics

• Bldg 359A

• Eastman Chemical Company

• Phone: 423-229-4060

• Email: sfwright@eastman.com