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Proprietary Information 1111
A practical application
of a Digital Twin
Integratingsimulationintodaily
operationstominimizelostprofit
SimonCalverley
KBC(AYokogawaCompany)
ERTC 2019
Proprietary Information 2222Proprietary Information 2Proprietary Information 2Proprietary Information 2Proprietary Information 2
The Digital Twin
Practical Application Today
Future Digital Nirvana
Proprietary Information 3333Proprietary InformationProprietary InformationProprietary InformationProprietary Information
Most well-run plants
will have a
simulation model
of the plant
Generally limited to ad-hoc use by
unit engineers for troubleshooting
and investigating improvement
Proprietary Information 4444
Digitalizationallowsus tocompress
timehorizons& reduceuncertainty
LossesDueto
UncertaintyReduced
Decision-Making
Time Horizon
Decision Impact
Time Horizon
SECONDS
Ago
MINUTES
Ago
HOURS
Ago
MONTHS
Ago
SECONDS
Ahead
MINUTES
Ahead
HOURS
Ahead
DAYS
Ahead
MONTHS
Ahead
DAYS
Ago
NOW
Operations
Mgmt.
Automation
Production
Mgmt.
Business
Mgmt.
DecisionValue
Proprietary Information 5555Proprietary InformationProprietary InformationProprietary InformationProprietary Information
A Digital Twin
goes beyond
traditional
simulation
Traditional
Particular
operating case
A snapshot in time
Ad-hoc basis to
answer
a question
Owned and used by
isolated groups
Specific tools for
different silos
Digital
Twin
Full range of asset
operation
Full history and
future
Automated to
business workflows
Centralized single
version of the truth,
used by everyone
Single integrated twin
of process, utilities and
heat exchange sys.
Proprietary Information 6666
Industryis conservativewhenit comestotechnology
• Exception rather than the rule
• New technology early adopters
• Will stay largely the same
• Adoption of proven technology
Survey conducted for KBC by IQPC (International Quality & Productivity Center)
Industry perspectives on adoption
of new technology
Proprietary Information 7777
Daily Meeting
• Unreconciled and
unstructured (spreadsheet)
data
• No predictive view of
performance for current
operations
Troubleshooting
• Data analysis only on
specific trends of the data
• Ad hoc simulations
Planning
• Compiling and reconciling
performance data
• Error identification and
time for LP model updates.
Reporting
• Data gathering and
manipulation
• Metrics, KPI’s calculations
only available in monthly
/ quarterly reports
Unit
Performance
Monitoring
processesare
bogged
down
Proprietary Information 8888
KBCdecidedtointegratePetro-SIM®andPI
Proprietary Information 99999999
Incorporateresultsfrom
Petro-SIMalongsidePIdata
Keyunitperformance
resultsconsumedthrough
PIVision
Expertusersarestillableto
performdeeperanalysis
throughdirectinteraction
withPetro-SIM
Unit Performance Portal built
around PI Vision dashboards
Proprietary Information 10101010
Unit PerformanceAssurance
Daily Meeting
Summary report’s top
3-5 actions based on
value discussed
Troubleshooting
Plant monitored daily
with global network
expertise alerted to
issues
Planning
Real Time LP vs
calibrated Simulation
vs Plant monitoring to
generate always up to
date LP vectors
Reporting
Consistent calculation
and comparison of
metrics, and analytics
for each unit
Proprietary Information 11111111
US$0.05 – 0.10/bbl for ensuring that the LP is an
accurate representation of the refinery
Value of monitoring
via a Digital twin
Up to US$0.05/bbl for unit monitoring, including:
Faster response to/recovery from upsets
Remaining on plan – identifying issues and resolving
them before operation becomes constrained
Identifying improvements to realise increased value
11
Implemented at
Gulf Coast refiner
Identified opportunities of
$8 million in first 6 months.
Rationalized and corrected
yield accounting and unit
material balance.
Advanced analytics helped
increase uptime of key
process equipment
Case study 1
Case study 2
US Refiner with 12+
refineries worked with KBC
IT and Modelling services to
roll out unit health and
model monitoring
applications on nearly all
their process units.
Whole program executed in
just over two years
Uses Petro-SIM & PI
architecture
Refiner modelling team &
SMEs defined KPIs
Worked with KBC team to
speed up deployment
across multiple units
Case study 3
Refiner has seen significant
dollar benefits
Improved operations and
small capex opportunities
Monitoring automation
giving time back to
engineers
Greater engagement with
simulation and optimization
Large US & European
refiner uses continual
model validation through
performance monitoring to
give unit engineers
confidence in model and to
make always up-to-date
models available on
demand
Proprietary Information 15151515
Individualpointsolutiondigitaltwinsexisttoday,a future
digitalnirvanahasonemulti-purposedigitaltwin
THE MANTRA
HAS TO BE:
Proprietary Information 16
Think Big
Start Small
Scale Fast
Drive Adoption
Excellence
is never an accident. It is always the result
of high intention, sincere effort, and
intelligent execution; it represents the wise
choice of many alternatives - choice, not
chance, determines your destiny.
Thank You
0022-ERTC-PPT-US-112019

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KBC Proven Application of Digital Twin

  • 1. Proprietary Information 1111 A practical application of a Digital Twin Integratingsimulationintodaily operationstominimizelostprofit SimonCalverley KBC(AYokogawaCompany) ERTC 2019
  • 2. Proprietary Information 2222Proprietary Information 2Proprietary Information 2Proprietary Information 2Proprietary Information 2 The Digital Twin Practical Application Today Future Digital Nirvana
  • 3. Proprietary Information 3333Proprietary InformationProprietary InformationProprietary InformationProprietary Information Most well-run plants will have a simulation model of the plant Generally limited to ad-hoc use by unit engineers for troubleshooting and investigating improvement
  • 4. Proprietary Information 4444 Digitalizationallowsus tocompress timehorizons& reduceuncertainty LossesDueto UncertaintyReduced Decision-Making Time Horizon Decision Impact Time Horizon SECONDS Ago MINUTES Ago HOURS Ago MONTHS Ago SECONDS Ahead MINUTES Ahead HOURS Ahead DAYS Ahead MONTHS Ahead DAYS Ago NOW Operations Mgmt. Automation Production Mgmt. Business Mgmt. DecisionValue
  • 5. Proprietary Information 5555Proprietary InformationProprietary InformationProprietary InformationProprietary Information A Digital Twin goes beyond traditional simulation Traditional Particular operating case A snapshot in time Ad-hoc basis to answer a question Owned and used by isolated groups Specific tools for different silos Digital Twin Full range of asset operation Full history and future Automated to business workflows Centralized single version of the truth, used by everyone Single integrated twin of process, utilities and heat exchange sys.
  • 6. Proprietary Information 6666 Industryis conservativewhenit comestotechnology • Exception rather than the rule • New technology early adopters • Will stay largely the same • Adoption of proven technology Survey conducted for KBC by IQPC (International Quality & Productivity Center) Industry perspectives on adoption of new technology
  • 7. Proprietary Information 7777 Daily Meeting • Unreconciled and unstructured (spreadsheet) data • No predictive view of performance for current operations Troubleshooting • Data analysis only on specific trends of the data • Ad hoc simulations Planning • Compiling and reconciling performance data • Error identification and time for LP model updates. Reporting • Data gathering and manipulation • Metrics, KPI’s calculations only available in monthly / quarterly reports Unit Performance Monitoring processesare bogged down
  • 10. Proprietary Information 10101010 Unit PerformanceAssurance Daily Meeting Summary report’s top 3-5 actions based on value discussed Troubleshooting Plant monitored daily with global network expertise alerted to issues Planning Real Time LP vs calibrated Simulation vs Plant monitoring to generate always up to date LP vectors Reporting Consistent calculation and comparison of metrics, and analytics for each unit
  • 11. Proprietary Information 11111111 US$0.05 – 0.10/bbl for ensuring that the LP is an accurate representation of the refinery Value of monitoring via a Digital twin Up to US$0.05/bbl for unit monitoring, including: Faster response to/recovery from upsets Remaining on plan – identifying issues and resolving them before operation becomes constrained Identifying improvements to realise increased value 11
  • 12. Implemented at Gulf Coast refiner Identified opportunities of $8 million in first 6 months. Rationalized and corrected yield accounting and unit material balance. Advanced analytics helped increase uptime of key process equipment Case study 1
  • 13. Case study 2 US Refiner with 12+ refineries worked with KBC IT and Modelling services to roll out unit health and model monitoring applications on nearly all their process units. Whole program executed in just over two years Uses Petro-SIM & PI architecture Refiner modelling team & SMEs defined KPIs Worked with KBC team to speed up deployment across multiple units
  • 14. Case study 3 Refiner has seen significant dollar benefits Improved operations and small capex opportunities Monitoring automation giving time back to engineers Greater engagement with simulation and optimization Large US & European refiner uses continual model validation through performance monitoring to give unit engineers confidence in model and to make always up-to-date models available on demand
  • 15. Proprietary Information 15151515 Individualpointsolutiondigitaltwinsexisttoday,a future digitalnirvanahasonemulti-purposedigitaltwin
  • 16. THE MANTRA HAS TO BE: Proprietary Information 16 Think Big Start Small Scale Fast Drive Adoption
  • 17. Excellence is never an accident. It is always the result of high intention, sincere effort, and intelligent execution; it represents the wise choice of many alternatives - choice, not chance, determines your destiny. Thank You 0022-ERTC-PPT-US-112019