a review of process analytics in the year 2012

A REVIEW OF PROCESS ANALYTICS IN THE YEAR 2012

Rob Dubois Jeff Gunnell Dow Chemical ExxonMobil

Chemical

In the years up to 2012 the demand for more difficult measurements

increased Matched by growth in new Process

Analytical technologies...• nanotech TDL lab-on-a-chip

microGC NMR spectrometer-on-chip eNose CRD MS-on-a-chip

… but the old technologies remained...• GC MS FT-(N)IR

CEMS water

… and it became impossible for one person to provide high level support such a wide range of techniques

Remote support requirements were met through initiatives which started at

IFPACs in 2000/1/2

NeSSI: New Sampling / Sensor Initiative

ConnI: Connectivity Initiative

Appl-I: A suite of application software

Characteristics of the Process Analytics industry

Superb science• inventing new analytical technologies

Practicality• efficient engineering of the sensor-world interface• rapid commercialization

Collaboration• selecting winning industry-wide initiatives• competing in the real value-added areas

Innovative deployment of other technologies• seizing opportunities - not reinventing

Computing developments which we used...

PDAs became a standard tool• wireless connectivity• human-machine interface for many devices• used with GPS to pinpoint equipment

Wearable PCs became common

• Heads-up displays and data entry improved– voice entry of data– voice recognition “action” commands

The web ruled...• browser access to everything from everywhere

Security became better and easier• retinal recognition

NeSSI modules are the foundation

Courtesy of CIRCOR

Modular systems built on the desktop

ConnI Architecture - 4 domains

Level 2 LAN = Field LAN

Level 3 LAN

INFORMATION D0MAIN

AnLAN

PROCESS CONTROL DOMAIN

c-LAN

ENTERPRISE DOMAIN

MEASUREMENT DOMAIN

SAM

eSAM

Level 1 SensorBus (CAN)

Level 4 Enterprise LAN

- Highbandwidth data pipelines

- Traffic routers send data to the “need to know” domains

Courtesy of P. van Vuuren and R.J. O’Reilly

Predictive maintenance replaces planned

• Intelligent diagnostics watch analyser systems...all the time...

• ‘I need help’ flags are sent in real time to wireless Personal Digital Assistants (PDAs)

………………

A typical troubleshooting task for a technician starts when her PDA buzzes and indicates a possible problem...

Please help me...

A smart application in an analyser system has detected something strange - relevant information is sent out...

The technician taps down for more info...

Background data and recent history is sent

Key sensor data have been monitored and unusual conditions have been detected...

The technician taps down for more details...

Recent history is shown graphically

The technician starts to think about the cause of the problem…

…and sees the problem…clearly...

A pinched valve is quickly discovered and the problem resolved…pronto!

Appl-I: Smart applications

Functions are part of a shell which is used by all analyser vendors…(much like Excel)

•monitoring of key parameters• flow, pressure, temperature…as well as analytical

•self-validation, both continuous and periodic

•intelligent statistical tools identify abnormal events

•users notified when trouble is suspected

•data presented in a user-friendly way

Excel is a registered trademark of Microsoft Corp.

The technician takes her toolkit, including her wearable PC, out to the

field...

Courtesy of Oxford Technologies

She has access to an on-line manual

The wearable PC means that useful information is readily available:

There are up-to-date descriptions of tasks

Video clips* show how jobs are done.* Video Courtesy of Andy Jopek

ScAN microSpectrometer

Web-based manual

Model : 42 General manualTag : NA733 Specific manual

__________________________________________________________________________

Section 4.3 Valve maintenance

h h h h h h h h h h h h h h h h h h hh h h h h h h h h h h h h h h h h h hh h h h h h h h h h h h h h h h h h hh h h h h h h h h h h

h h h h h h h h h h h h h h h h h h hh h h h h h h h h h h h h h h h h h hh h h h h h h h h h h h h h h h h

h h h h h h h h h h h h h h h h h h hh h h h h h h h h h h h h h h h h h hh h h h h h h h h h h h h h h h h h hh h h h h

h h h h h h h h h h h h h h h h h h hh h h h h h h h h h h h h h h h h h hh h h h h h h h h h h h h h h h h h hh h h h h h h h h h h h h

Valve maintenance video clip

Links to other systems facilitate work

Equipment parts lists are linked to warehousing - both in house and external.

She identifies spares which she needs and orders them as she works using the manual and warehousing tool

ScAN microSpectrometer

Web-based manual

Model : 42 General manualTag : NA733 Specific manual

__________________________________________________________________________

Section 4.8 Spares

h h h h h h h h h h h h h h h hh h h h h h h h h h hh h h h h h h h h h h h h h hh h h h h h h h hh h h h h h h h h h h h h

Record keeping is built in

Intelligent checklists and voice entry make record keeping easy:

The manual helps her fill in a work record - using voice data entry

ScAN microSpectrometer

Web-based manual

Model : 42 General manualTag : NA733 Specific manual

__________________________________________________________________________

Section 4.3 Valve maintenance checklist

Say "Voice entry" and "your name "

h h h h h h h h h h h h h h h hh h h h h h h OK

h h h h h h h h h h h h h h h hh h h OK

h h h h h h h h h h h h h h h hh h h h h

h h h h h h h h h h h

h h h h h h h h h h h h h h h hh h h h h h h h h h h h h

Say "Comments"

Wizards help with many tasks

On completion she runs the smart health check wizard

She requests two day data watch so she can personally check that everything is OK. A maintenance encounter is booked into her calendar

ScAN microSpectrometer

Web-based manual

Model : 42 General manualTag : NA733 Specific manual

__________________________________________________________________________

Section 5.1 Auto check wizard

Say "Run autocheck" and select options

h h h h h h h h h h h h h h h hh h h h h h h Yes

h h h h h h h h h h hYes

h h h h h h h h h h h h h h h hh h h h h h h h h h h h h No

Section 5.1 Data watch wizard

Say "Run data watch" and select options

h h h h h h h h h h h h h h hYes

h h h h h h h h h h h hYes

h h h h h h h h h h h h h hNo

h h h h h h h h h h hYes

In 2012 a typical engineering support problem involves...data reconciliation

A micro-spectrometer system has been installed in a new plant in China...

• The process control engineers have a model to predict process behavior - and they use the analyser to correct their model

• In testing, the analyser and model tracked well during small excursions, however there was a discrepancy during a large excursion– the analyser response was just too slow and too small

• The site team in China asked the engineer to take a look

• All folks involved were able to browse their analyser and process data base from their PC

They could see the problem but could not explain it...

Model Analyser

The engineer realized he needed expert help...

• He checked a few parameters using the analyser browser but nothing jumped out at him immediately...

• In a video conference with the China team the engineer decided to ask for additional support

Connectivity tools enabled remote teamworking

• The China team set up a data-base containing the entire data record plus design and test information

• He called up a virtual team which included• the process and analyser people in China• another site which has a similar installation• the analyser vendor’s design group

• They had a virtual conference using:• video communications• data & screen sharing

It certainly looked like an analyser problem...

• The virtual team felt pretty sure that there was something strange about the analyser, not the process...

• The vendor team asked for time to work on the data bases

• They discovered that the problem was due to hysteresis in their micro-technology, coupled with an unexpected effect in their software smoothing algorithm

The problem was fixed remotely by the vendor

• A software patch was downloaded to the analyser in China• revisions were automatically updated• a sprite to monitor performance was

included

• The vendor also sent out an alert to other clients, along with the sprite

• The vendor initiated their product improvement process

Key points: Technician level

Technicians in plants retain the prime responsibility of maintaining analyser systems

Human knowledge, skills, thought processes are needed more than ever

Logic and intelligence in machines help technicians to use their human skills better• real-time health checks of systems

– focus on predictive maintenance• data presentation helps troubleshooting• …and bureaucracy is unburdened

Key points: Engineer level

Highly complex analyser technologies abound

Sites are spread all around the globe

Technical support and troubleshooting is a team game• collaboration tools facilitate virtual teams• support round the clock, round the globe• changes in

– responsibility– behaviour– relationships

This is life in 2012 - how did we get here?

NeSSI came through:• modular sample systems• integrated with analysers sensors• in smart, field mounted units

ConnI • delivered an architecture which linked

everything together

Appl-I• provided a common application shell

…and collaboration delivered benefits for all

…and a special thanks to...

Peter van Vuuren

- for supplying the building blocks

Walter Henslee

- for widening the vision

Smart

artificially intelligent

analysers