1. Automation Committee Workshop Presentation 2
Life of a Signal
Practical Uses of Big Data

2. What is a Signal? As defined by Merriam-Webster Dictionary:
a detectable physical quantity or impulse (such as a voltage, current, or magnetic field strength) by which messages or information can be transmitted

3. Types of Signals Discrete (a.k.a. digital or binary) – on or off
Analog – continuously variable

4. Sources of Signals
Primary Instrumentation – directly connected to the process or equipment
Flow, pressure, level, temperature instruments
Analytical measurements such as pH, chlorine residual, turbidity
Machine conditions such as motor temperature, vibration, power consumption

5. Sources of Signals
Secondary Instrumentation  – performs automation and user interface functions
Control panels, programmable logic controllers (PLCs)
SCADA software
Laboratory management software
Maintenance management software

6. Signal Transmission
Discrete – output of switches - opens or closes an electrical circuit
Analog – output of transmitters - typically 4-20 mA current proportional to the process measurement

7. Signal Transmission Bit Byte
Digital Communications – discrete or analog signals represented by binary digits (bits) based on a network protocol
Bit
Binary digit, 0 or 1
Byte
A sequence of bits operated on as a unit, typically representing a letter, number or other character

8. Local Signal Reception
Signals received by local panels
For operator notification
For automatic control functions (e.g., safety shutdown)
Signals received at PLCs
For automatic control functions
For retransmission to other PLCs or SCADA computers

9. Remote Signal Reception (SCADA)
Network connections
PLCs to SCADA server
Instrument to SCADA server
SCADA server to operator workstation

10. SCADA Historian SCADA server pushes data to a Historian server
Signal values are saved at full scan rate or based on rules to minimize data
Analysis/reporting/trending software
Time series signals from Historian server are viewed in trend graphs
Signal values may be included in calculations and reports

11. Example “Life of a Signal”

12. Example “Life of a Signal”
Cloud Platform
Example “Life of a Signal”
Ethernet Switch
SCADA HMI
PLC/RTU
Ethernet Switch
SCADA Server
Historian Server

13. Practical Uses of “Big Data”

14. What is Big Data? As defined in Wikipedia:
a term used to refer to data sets that are too large or complex for traditional data-processing application software to adequately deal with

15. Big Data Concepts Volume – how much data Variety – the type of data
Velocity – the speed at which data is generated
Veracity – the quality or uncertainty of the data
Visibility – availability of the data
Value – the business reason to collect and analyze the data

16. Industry Trends Pressure to “do more with less”.
Emphasis on sustainability.
Growing reliance on data driven decision making.
Growing expectations to have access to data and information.
Big Data tools are at our finger tips!

17. Utility Management Systems Process Control/ SCADA
Connectivity
Access to diverse datasets to facilitate advanced analytics
Collaboration with other utilities
Immediate connection with customers
“Internet of Things” (IOT) enabled instrumentation can communicate directly to data management platforms
Utility Management Systems
Process Control/ SCADA
Instrumentation
CMMS/ Asset Databases

18. Hindsight Insight Foresight
What can we make happen?
Advanced Analytics Growth
What will happen?
Prescriptive Analytics
Facilitated by access to diverse data sets
Computing power
Solve complex problems
Resolve issues before they escalate
Machine Learning
What happened?
Predictive Analytics
Descriptive Analytics
Hindsight Insight Foresight

19. Data Visualization Strategies (Dashboarding)
SCADA HMI
Business Management Platforms (i.e. SAP, Sales Force, SAS).
“Big Data” platforms such as PowerBI, Tableau, etc…

20. Discussion Topics:
Describe the most important data sources used by your organization.
Describe additional sources of data that your organization intends to acquire and why.
What challenges does your organization face in acquiring or using more data?