1. Accessing Real-time-data in PLCs
R in Automation
Accessing Real-time-data in PLCs

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Automation, PLCs, HMI
Automation, roboticization or industrial automation or numerical control is the use of control systems such as computers to control industrial machinery and processes, reducing the need for human intervention.
Closed Loop Control
PLCs (Programmable Logic Controllers)
Connected with sensors and actors (so-called I/O-devices)
Cyclic execution of applications
Read inputs
Compute outputs
Write outputs
Real-time capabilities (e.g., executed every 1ms)
HMI
Real Controls (switches/LEDs)
Virtual Controls (GUI in Software) (
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3. OPC (OLE for Process Control)
OPC (DA) is a standard for data exchange
Between HMI software and PLCs
Data exchange between PLCs
Based on Microsoft COM (formerly known as OLE)
Additional spefications extending original OPC DA
OPC DA is the de-facto standard for data exchange in automation
Implemented by most (nearly all) PLC and HMI vendors
OPC UA
Currently in-work specification(s)
No more based on COM
Portable (no limitation to Windows)
Binary communication protocol and SOAP/http
OPC foundation
Maintains specifications
Provides source code/reference implementations to members
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4. ropc: Let R Access OPC Servers
Why R?
Open and powerful system
Easily embeddable in other software systems
Lots of pre-build functionality (1518 packages on CRAN and many others elsewhere)
Why ropc?
ropc builds a bridge between automation devices and R
Lots of data available for further processing
Vendor-independent data access mechanism
R+OPC+ropc
Can fetch real-time data from automation devices/plants
Possibility to write data to automation devices
R‘s Powerful engine and packages can work directly on real-time data
Even possible to implement (closed loop) control algorithms using R
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Using ropc
Initialization phase
Connect to an OPC server (opcConnect())
Add one (or more) groups of OPC items („automation variables“) using opcAddGroup() and opcAddItems()
Processing phase
Read groups of OPC items (opcRead())
Write groups of OPC items (opcWrite())
Termination phase
OPC items, groups and servers are processed by R‘s garbage collector
Additional features
Recording of OPC items over some time period (opcTSRead())
Changing OPC item groups (opcAddItems(), opcRemoveItems())
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An ropc Sample Session
library(ropc)
srv<-opcConnect() # use default server
grp<-opcAddGroup(srv) # create default group
# add 3 items to the group
opcAddItems(grp,c(„InsideTemp“, „OutsideTemp“, „HeatingTemp“))
# read item values every minute for 5 hours
temps<-opcTSRead(grp,300,60)
# something with the data
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7. logi.DIAG: Predictive Maintenance
Research project
Two companies: logi.cals, Messfeld
Two universities: University of Vienna, Vienna University of Technology
Funded by FFG/FWF in Austria
One major goal is „predictive maintenance“
Process and production automation normally 24/7
Downtime is very costly
As few maintenance hours as possible
Planning maintenance is required
Possible approach
Apply statistical methods to „predict“ failures
Use R for statistics
Acquire data using OPC
-> ropc
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About logi.cals
Founded 1987 in Austria
Provides software for automation
Planning of plants (function plan, VGB R170C, ISA S5.2,...)
Target-system neutral programming system, IEC
Runtime systems for real-time execution of code
Visualization systems (web-based)
Configuration and testing software
Our customers‘ businesses
Rolling mills
Chemical and specifically Pharmaceutical plants
Power plants
Automotive
Safety systems
...
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