Jeroen will focus on the use of OPC-UA and InfluxDB in industrial settings. Learn how he built an open-source OPC-UA client and server to bring data from and to your process control systems. He will demonstrate the capabilities and show how Flux fits into the picture.

1. Using the Open
Source OPC-UA
Client and Server for
Your IIoT Solutions
JEROEN COUSSEMENT - INFLUXDAYS 2019 - LONDON

2. ABOUT FACTRY
▸ Based in Ghent, Belgium
▸ Industrial software solutions
▸ Tools for data-driven
operational improvement
▸ Factry Historian
▸ Lots of open-source

3. TIME-SERIES
MEETUP
https://www.meetup.com/Time-
Series-Belgium/

4. INDUSTRY

5. INDUSTRY 1.0
STEAM POWER /
MECHANISATION

6. INDUSTRY 2.0
MASS ASSEMBLY

7. INDUSTRY 3.0
COMPUTERS &
AUTOMATION
https://www.flickr.com/photos/greenmambagreenmamba/5307396963/in/photostream/, (CC BY-ND 2.0))

8. SUPERVISORY CONTROL
SYSTEM (SCADA/DCS)
PROGRAMMABLE LOGIC
CONTROLLER (PLC)
PROCESS SENSORS AND ACTUATORS
PROGRAMMABLE LOGIC
CONTROLLER (PLC)

9. INDUSTRY 4.0
CYBER PHYSICAL
SYSTEMS / AI / ML

10. A GAP BETWEEN
OT AND IT.
OT IT?

11. SOMETIMES WE
HAVE TO GO
FULL RETRO
VERY LONG
LIFECYCLES

12. “WE’VE BEEN
DOING IT FOR
YEARS AND IT
WORKS”
SLOW ADOPTION

13. EVERYONE HAS
THEIR OWN
STANDARD
VENDOR LOCK-IN

14. SUPERVISORY CONTROL
SYSTEM (SCADA/DCS)
PROGRAMMABLE LOGIC
CONTROLLER (PLC)
PROCESS SENSORS AND ACTUATORS
EXTERNAL APPLICATIONS ( Artificial Intelligence / Machine Learning / … )
PROGRAMMABLE LOGIC
CONTROLLER (PLC)

15. WHAT KIND OF TIME-SERIES
DATA DO WE HAVE
IN INDUSTRY ?

16. DEVOPS DATA vs INDUSTRIAL DATA
DevOps Industry
Metrics cpu load, disk I/O, database
stats, ...
temperature, pressure, flow,
valveState ...
Resolutions seconds to minutes (sub)seconds
Retention weeks, then downsampling 5 to 10 years, no downsampling
Main goals incident detection, performance
monitoring
quality guarantee, predictive
maintenance

17. THE FIRST TIME-SERIES DATABASES

18. PROCESS HISTORIAN

19. Process historian refers to a
database software application that
logs or historizes time-based
process data.

20. SUPERVISORY CONTROL
SYSTEM (SCADA/DCS)
PROGRAMMABLE LOGIC
CONTROLLER (PLC)
PROCESS SENSORS AND ACTUATORS
InfluxDB
EXTERNAL APPLICATIONS ( Artificial Intelligence / Machine Learning / … )
PROGRAMMABLE LOGIC
CONTROLLER (PLC)

22. OPC-UA
DESCRIPTION
▸ Industrial communication protocol
▸ Successor of OPC - OLE for Process Control
▸ Vendor independent / Platform independent
▸ Released in 2006, but became adopted only recently
▸ Integrated on newest controllers, but retrofit on older
ones possible.

23. OPC-UA
DATA STRUCTURE
▸ Hierarchical data structure
▸ Everything is represented as a data node.
▹ Each node has a unique nodeID
▹ Consists of namespace + identifier
▹ ns=2;s=S7:12_03_12.DB100.4,r

24. SUPERVISORY CONTROL
SYSTEM (SCADA/DCS)
PROGRAMMABLE LOGIC
CONTROLLER (PLC)
PROCESS SENSORS AND ACTUATORS
InfluxDB
EXTERNAL APPLICATIONS ( Artificial Intelligence / Machine Learning / … )
PROGRAMMABLE LOGIC
CONTROLLER (PLC)

25. OPC-UA LOGGER
OPEN SOURCE
▸ Reads data from OPCUA sources
▸ Local buffering for no data loss
▸ github.com/coussej/
node-opcua-logger

26. OPC-UA LOGGER
DEMO
▸ Configure some nodes
to be collected from
simulation server

27. OPC-UA LOGGER
OPEN SOURCE
▸ V2 coming soon
▹ Cleaner code (async/await!)
▹ Better buffering
▹ Deploy as a single binary

28. USE-CASE: BIOREACTOR

29. USE-CASE: ENERGY MONITORING

30. USE-CASE: WIND TURBINE OPERATIONS

31. SUPERVISORY CONTROL
SYSTEM (SCADA/DCS)
PROGRAMMABLE LOGIC
CONTROLLER (PLC)
PROCESS SENSORS AND ACTUATORS
InfluxDB
EXTERNAL APPLICATIONS ( Artificial Intelligence / Machine Learning / … )
PROGRAMMABLE LOGIC
CONTROLLER (PLC)

32. OPC-UA SERVER
OPEN SOURCE
▸ Return algorithm results back
to the process control
▸ Exposing last() value of
specified series over OPCUA
▸ github.com/factrylabs/
influx-opcua-server

33. OPC-UA SERVER
OPEN SOURCE
▸ DEMO

34. HOW DOES FLUX FIT INTO
THE PICTURE?

35. FLUX
CUSTOMER QUESTION 1
▸ Input Pressure
▸ Output Pressure
▸ Can we calculate Pressure drop?
▸ Math across measurements!

37. DEMO FLUX - Pressure drop (1/2)
UF1PT01 = from(bucket: "historian")
|> range(start: 2019-05-01, stop: 2019-05-25)
|> filter(fn: (r) => r._measurement == "CV-UF1PT01")
|> aggregateWindow(every: 3m, fn: mean, createEmpty: false)
UF1PT02 = from(bucket: "historian")
|> range(start: 2019-05-01, stop: 2019-05-25)
|> filter(fn: (r) => r._measurement == "CV-UF1PT02")
|> aggregateWindow(every: 3m, fn: mean, createEmpty: false)

38. DEMO FLUX - Pressure drop (2/2)
join(
tables: {pt01:UF1PT01, pt02:UF1PT02},
on: ["_time"]
)
|> map(fn: (r) => ({
_time: r._time,
_pressureDrop: r._value_pt01 - r._value_pt02
}))
|> filter(fn: (r) => r._pressureDrop > 0)
|> aggregateWindow(columns: ["_pressureDrop"], every: 1h, fn: mean, createEmpty: false)

39. FLUX
CUSTOMER QUESTION 2
▸ NTU (Nephelometric Turbidity Unit)
▸ Machine Status
▸ Can we see the NTU only when the machine is in
production?

41. DEMO FLUX - Filter on status (1/2)
NTU = from(bucket: "historian")
|> range(start: 2019-05-01, stop: 2019-05-02)
|> filter(fn: (r) => r._measurement == "CV-UF1NTU01" and r.status == "Good")
|> aggregateWindow(every: 30s, fn: mean)
|> keep(columns: ["_value", "_time"])
Status = from(bucket: "historian")
|> range(start: 2019-05-01, stop: 2019-05-02)
|> filter(fn: (r) => r._measurement == "Status" and r.status == "Good")
|> map(fn: (r) => ({
_time: r._time,
_status: float(v: contains(value: int(v: r._value), set: [11,21])
}), mergeKey: false)

42. DEMO FLUX - Filter on status (2/2)
union(tables: [NTU, Status])
|> sort(columns: ["_time"], desc: false)
|> fill(column: "_status", usePrevious: true)
|> fill(column: "_status", value: 0.0)
|> fill(column: "_value", usePrevious: true) // same for the values themselves
|> fill(column: "_value", value: 0.0)
|> map(fn: (r) => ({_time: r._time, _filteredValue: r._value * r._status}), mergeKey: false)
|> yield()

43. THANK YOU!ANY QUESTIONS?

44. JEROEN COUSSEMENT
jeroen.coussement@factry.io
FACTRY
OPEN OPERATIONAL INTELLIGENCE