1. What is a Good SmartSignal Model?
Presented by
Joe Milton
Engineering Manager
Reliant

2. Outline
Reliant generating fleet and OSIsoft PI infrastructure
Virtual M&D concept
Human factors
What is a good model?
KPIs and other metrics

3. Generating Fleet Location and Fuel Type

4. Common Plant Historian -- OSIsoft PI
29 PI Servers
203 interfaces to various systems
1000+ process displays & reports
350K tags (real-time data points)

5. OSIsoft PI took care of history and current value but not what the value should be….
We selected SmartSignal to leverage our existing OSI PI infrastructure and predict…

6. SmartSignal Predictive Maintenance Tool
SS takes data from our PI infrastructure (like vibration, temperature, pressure, etc.) and inputs it into a software model. This model shows how a a typical piece of equipment is supposed to operate over various loads and ambient temperatures.
If the data goes outside of the predictive model, an alarm is sent to the station for further investigation.
Basically, we are making the computer do the work of scanning all of the sensors and instruments in the plant for changes in known equipment behavior.

7. Defining WatchList Graphing Terms: Actual, Estimate, Residual, Alert, Incident
Actual (blue) from OSI PI
Estimate (green) generated by SSC models
Residual = Actual - Est
Alerts (red X) Statistically significant residual value
Incident (diamond) multiple samples or sensors showing alerts; drives the WatchList

8. Typical Results & Additional Terms
VSG (green diamond) Virtual Signal Generation was enabled
Missing Value (blue X) Signal gave NaN value

9. Smart Signal – Site WatchList
Models
Can see incidents by clicking the arrow button.

10. SmartSignal – Site Model Detail
Site that you are on.
Incident List – This is a list of incidents on the models.
Chart View –The Blue line is the actual PI data and the Green line is the model data.

11. SmartSignal-Reliant Scope
67 coal & natural gas power units across U.S.
Total 13,450 MW power
Rotating & non-rotating balance-of-plant assets monitored
411 assets, 1174 models
Turn 30K+ sensors to exception-based monitoring
Goals include
Early warning of equipment faults & process problems
Maximize availability
Minimize forced outages
Improvement of unit heat rates

12. Reliant’s “Virtual” M&D Center
Staff of three working 5*8 at their own cubes:
Review WatchList
plants when equipment issues are detected
Tune
Build new models
Teach WatchList classes
Document issues and model changes.
Plant champions
Look at the WatchList
Use log
Deal with the easy ones

13. Typical Emails to Plant

14. Typical Plant Response
The Plant Champion will commonly use Pi Processbook or Datalink to confirm the item and issue a work order

15. Example of Full Cycle of a Catch
From:
Sent: Thursday, November 30, :34 PM
This is a pretty significant movement on FD Fan Motor outboard bearing (about 17 deg above expected currently).
The oil levels are all good and the filters have been changed. The filters were dirty and the temps are dropping on the motor after the change out.

16. What is a Good Model?

17. Good Model Brainstorm

18. Truth Table (Logic) SS Catch SS Catch False Catch True Catch
SS no Catch
SS no Catch
No Machine issue
Machine issue

19. What is a Good Model So Far?
Modeling elements
It has catches (detects changes)
It has no misses (or few)
It uses as-found data
Human elements
It has engaged users

20. Metrics
True Catches
Look at the tracking log-equipment/instrumentation catches
Missed Catches
Long term – Use Power GADS to review major events
Was the system modeled? If not, should it be? Build it.
If modeled, review and improve the model.
No Catches & No Machine Problems
Could be a sign of a good program
Could mean just wait
False Catch
Track issues
Use log statistics and target problematic models

21. Catches The table shows true catches and false catches
*2006 catches not a full year

22. False Catch
SmartSignal alerts indicate a change from the model data set (State matrix)-
A repair could cause a change
A new season
An operational mode change
An abnormal configuration
Or bad modeling data

23. Model with False Alerts
Detailed review of this model
data set found that it had two
modes. A and B with the same
Inlet temperature and A down
stream of B

24. Model with False Alerts
Detailed review of this model
data set found that it had two
spikes that were included in the
model.

25. Human Factors How can acceptance be measured? Is the user engaged?
What are good KPIs?
How can it be made “fair” for peaking and base load unit?

26. Levels of SmartSignal Utilization
basic level is where the WatchList Team (WLT) serves as an M&D center. Plant responds to WLT questions about their units and WatchList items.
the engaged user logs into the WatchList at least once a week (on average).
The committed user logs in several times a week (on average). They also add information to the log and clear alerts from the WatchList.
The power user exceeds the committed user level by pressing model issues and providing a dialogue about known plant repairs and changes.

27. Levels of SmartSignal Utilization 2007 – ‘08

28. KPI Issues
Terms like basic, power user work well for a full-year but they did not track seasonal units well
We moved to a new metric that is much closer to the desired outcome– If you are running- login

29. “Average number of service hours between logins”
SS Login Ratio
“Average number of service hours between logins”

30. Log Entries 2007 50% of plants had no log entries
78% of log entries were at one plant “C”
2008
Only 10% have no log entries for 2008
Log entries more evenly spread across fleet
119% increase in total log entries

31. Lessons
The knowledge of how the plant should run comes from how it has run (PI data)
Keeping the messenger alive is part of the task (instruments)
Eliminate variables (do not add them)
Model to detect changes
Exception-based
Statistics-based technologies are not common in plant environments.
Tools are not complete solutions – People still have to act

32. Questions?