1. Visualisation of Continuous Petrochemical Plant Operation Zaid Rawi BP Chemicals Ltd, Hull

2. 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. 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. 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. 5 Scrubber Problem But now at ~09:30 the temperatures are dropping

6. 6 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

7. 7 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. 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

9. 9 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. 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

11. 11 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!

12. 12 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

13. 13 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

14. 14 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

15. 15 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