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Visualisation of Continuous Petrochemical Plant Operation
Zaid RawiBP Chemicals Ltd, Hull
2
Introduction
• Problem: Detecting developing abnormal situations earlier to give more response time
• Solution: Overview plots
• Allow operators to see big picture and spot potential problems earlier
• Tested:
– Parallel coordinates
– Principal component analysis (PCA/MSPC)
• All use pictures to paint a 1000 words!
• Will show some example off-line cases
3
Parallel Coordinates
•Looking at 10 tags
•Each vertical axis is a tag/variable
•Each point is a variable value
•The points are joined up to form a profile
•The profile represents the state of the plant at this minute of time
•An excellent overview plot
4
Scrubber Problem
•An example scrubber problem
•Now showing 10 minutes of operation (10 profiles)
•Will scroll this 10 minute window through a day’s operation
•Plant starts off operating stably
5
Scrubber Problem
•But now at ~09:30 the temperatures are dropping
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Scrubber Problem
•And an oscillation develops
•Can see this quickly using parallel coordinates
•Can see the route cause
•Can display many more than 10 tags
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Compressor Problem
•An example compressor problem
•Have 16 key variables displayed
•Again showing 10 minutes and will scroll window
•Plant starts off operating stably
•Yellow is “normal” starting point
•Could show alarm limits as well
8
Compressor Problem
•Night time and temperatures are dropping and something strange is happening to a flow measurement
•It’s fluctuating rapidly
•Impulse line blockage!
•Can see this quickly using parallel coordinates
•Less obvious with traditional views
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Compressor Problem
•And it leads to the plant tripping a few hours later
•Would have had over 3 hours warning with this type of view
10
Compare Reactors
•Comparing 2 reactors which are dropping rates
•One has a problem the other doesn’t
•Can see the differences and problems quickly!
•Would have had 1 hour warning of a trip
Reactor 1
Reactor 2
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Plant Quality Query
•View also useful for plant operation query
•How to improve plant quality?
•We’ve marked when this quality parameter is low
•It lights up all the profiles that satisfy this
•Can see how the plant must be run to achieve this (red circles)
•Could do the query on more than one variable too!
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PCA (MSPC)
•An even more powerful view of the big picture
•Compress correlated plant variables into a few new ones (principal components)
•Build a model of normal operation
•Detect statistical deviations from normal operation
•Can then determine the variables responsible for the problem
•More sophisticated model building required but earlier warning possible
•Demonstrated on and off line
Instability
Clusters of normal operation
PC2
PC1
PC3
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Where Does It Fit In?
The Plant
Advanced Control -Stabilise and Optimise
On-line Operator Overview Displays - Detect Unforeseen Problems
Equipment Health Management - Look For Specific Problems
Radar plots
MSPC
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Conclusions
• Different methods to see big picture
• Demonstrated using Spotfire
• Being put on-line at BP Chemicals Hull
• Spot developing problems early
• Maximise response time
• Help diagnose root cause
• Avoid or minimise the impact of abnormal situations
• Reduce danger and off spec material
• When on-line, estimated benefits to one example plant are +£100kpa
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Acknowledgements
Acetyls team, VAM team, DF team, Richard Burkett, Paul Oram, Zaid Rawi, Don White, et al
BP Chemicals Ltd, Saltend, Hull, HU12 8DS, UK
Elaine Martin, Ewan Mercer, Julian Morris
CPACT, School of Chemical and Advanced Materials, University of Newcastle Upon Tyne, Merz Court, NE1 7RU, UK
Chris Hawkins
MDC Technology Ltd, Startforth Road, Riverside Park, Middlesbrough, TS2 1PT, UK
Mark Weedon
Spotfire, Första Långgatan 26, SE-413 28 Göteborg, Sweden