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Practical Uses of Big Data in Automation Workshop

This workshop presentation explores the different types of signals, their transmission and reception, as well as practical uses of big data in automation. Learn about the concepts behind big data and how it can be utilized to improve processes and decision-making. Discover the benefits of advanced analytics, predictive and prescriptive analytics, and data visualization strategies in automation. Join the discussion on data sources, challenges, and the potential of acquiring and using more data in your organization.

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Practical Uses of Big Data in Automation Workshop

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  1. Automation Committee WorkshopPresentation 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 • 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. 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. 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 CMMS/ Asset Databases Process Control/ SCADA Instrumentation

  18. 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?

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