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Touring Tomorrow's Digital Factory

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ARC Advisory Group Vice President Craig Resnick and Inductive Automation Chief Strategy Officer Don Pearson discuss a new type of IIoT architecture that can increase data throughput, provide greater agility, and improve enterprise-wide communication. Learn how IIoT could reshape the way industrial organizations implement system architectures, and deepen your knowledge of the key factors driving this movement.

Explore megatrends in manufacturing:
- Digital enterprise/IIoT platforms
- Edge computing
- Open enterprise architectures for the IIoT age
- Virtual and augmented reality in factory environments
- The factory workforce of the future
- Cybersecurity needs and solutions
- And more

Published in: Software
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Touring Tomorrow's Digital Factory

  1. 1. Moderator Don Pearson Chief Strategy Officer Inductive Automation
  2. 2. About Inductive Automation • Founded in 2003 • HMI, SCADA, MES, and IIoT software • Installed in 100+ countries • Over 1,600 integrators • Used by 48% of Fortune 100 companies Learn more at: inductiveautomation.com/about
  3. 3. Used by Major Companies Worldwide
  4. 4. Ignition: Industrial Application Platform One Universal Platform for SCADA, MES & IIoT: • Unlimited licensing model • Cross-platform compatibility • Based on IT-standard technologies • Scalable server-client architecture • Web-based & web-managed • Web-launched on desktop or mobile • Modular configurability • Rapid development & deployment
  5. 5. Guest Presenter Craig Resnick Vice President, Consulting ARC Advisory Group
  6. 6. Megatrends Driving the Digital Factory of the Future Digital Enterprise/IIoT/Edge/Advanced & Operational Analytics • Understand Manufacturing Process: Past, Present & Future, Data Value, Dashboards • Industrial Digital Enterprise/IIoT Platforms, Edge 3D Printing/Additive Manufacturing Advanced Robotics/ Digital Twin/Machine Learning • Virtual Design, Pattern Recognition, Artificial Intelligence Virtual & Augmented Reality Factory Environment • Virtual Production Simulation, Virtual Operations, Augmented Reality Workforce for the Factory of the Future • Highly Skilled and IT-literate Millennials, Importance of the Data Scientist Open Automation • Eliminate non-ROI projects, Maintain Levels of Safety, Security, And Financial Risk Cybersecurity • What’s Needed to Secure Industrial Systems, Anomaly & Breach Detection Solutions
  7. 7. The Emerging Smart Production Environment (IIoT, I4.0, etc.) The Edge Can be Found Throughout the Plant and Ecosystem Connected Operations Self-Planning Systems Flexible Worker Schedules Access Control Services Location/Nav Services Video Presence (Expert Help) Augmented Reality Smart Tools Connected Worker Mobile Devices Wearables Smart ComponentsAutonomous Inventory Movement Smart Carriers RFID Smart Warehouse Connected Supply Chain Smart Logistics Smart Products Connected Products Smart Metrology 3rd Party Services Plant Systems and Assets Enterprise Systems Connected Enterprise IIoT Smart Module Remote Monitoring & Services Connectivity Platform Advanced AnalyticsApps Smart Machines - Connected - Software-defined - Agents, Apps - Sensors e.g. vibration, ultrasound, infrared etc. Connected Machine Smart Containers
  8. 8. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 9 Fog Production Equipment Sensors, Actuators Automation Systems Plant S/W Enterprise S/W Distributed,AdvancedAnalytics Data Intelligence Analytics Embedded Systems at the Edge Connectivity Edge Management Cloud Platform Digital Enterprise Wearables, augmented reality, mobile devices, smart carriers, smart containers, smart components, smart products, autonomous machines, video, geofencing, 3rd party services, social, additive manufacturing, voice control, remote sensing, production equipment, etc.. Current Production Concept Digital Enterprise – A Rational Response To A Rapidly Emerging, Data-rich, Connected Reality
  9. 9. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 10 Digital Enterprise – Industrial Digital Enterprise/IIoT Platforms Fog Compute Platform Cognitive computing, data management, ML, etc.. 21st Century S/W platform Containerization, Microservices, etc.. e.g. Cloud IaaS IIoT Device Level PlatformDevice authentication, connectivity, apps, etc. Network Communications PlatformGateways, etc.. Embedded Compute/Comms Platforme.g. Intel, Qualcomm chips, boards, O/S, etc. Mobile Device PlatformTablets, phones, glasses, etc.. Cloud Edge Axeda, Telit, etc. Cisco, Intel, etc.. Intel, Qualcomm, Wind River, Mentor Graphics etc. Apple, Samsung, etc. Cloud Application Platform GE Predix, IBM Watson, Siemens Mindsphere, etc. GE Predix, SAP Cloud Platform, Siemens Mindsphere, etc. AWS, Microsoft Azure etc. Docker, KubernetesContainer Mgmt. Platform Analytics Platforms
  10. 10. Digital Enterprise - Opportunities
  11. 11. What the Industrial Edge is and What Makes It Different? Technology Infrastructure located on or near production operations for: • Data collection • Data analysis • Data storage Operating at the Edge has unique characteristics: • Can be in remote locations • No local IT skills to provide service • Multiple applications running at the Edge i.e. Analytics • Criticality of local data • Unique security needs • Used on devices, such as PLCs/PACs, Drives, etc. where plant will not embrace the cloud Edge Devices Are One of the Fastest Growing Areas of Industrial Automation Oil and Gas Food and Beverage Agriculture Rail and Transit
  12. 12. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 13 The IIoT/14.0 Network Edge Connecting Devices, Sensors, and Assets Devices, sensors, assets Edge Infrastructure Enterprise Applications Ethernet Gateways Cellular Gateways Wireless Gateways Ethernet Switches Routers Wireless Access Points Analytics ERP PLM Supply Chain Asset Management DBMS Demand Planning Purchasing Etc.
  13. 13. Factory of the Future Will Run on Advanced Analytics • Operational Intelligence powered by Machine Learning will determine best practices, avoid risk, and optimize production operations • Manufacturing processes and records represents the largest repository of Big Data across all of business and industry (Bureau of Labor Statistics) • Prescriptive Analytics, will bring together big data, statistical sciences, rules-based logic, and machine learning to empirically discover and reveal the origins of the complex problems, and then determine decision-based options to resolve them.
  14. 14. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 15 Categories of Advanced Analytics DESCRIPTIVE & DIAGNOSTIC What happens/happened and why Focus on Performance Focus on past and current performance Data discovery tools What to do Knowledge base Options and implications Automation of decision processes PRESCRIPTIVEPREDICTIVE What is likely to happen Structured, unstructured data Big Data, data science, machine learning, business rules Toolkits and sandbox environments Important for reactive decisions in real-time Important for proactive decisions and a well planned approach (usually weeks or months)
  15. 15. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 16 More data, more compute & storage power, better tools Advanced Analytic Tools
  16. 16. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 17 3D/Additive Manufacturing Moves To Mainstream Manufacturing • Aerospace & Defense, Automotive, Machinery & Heavy Equipment, Oil & Gas, and Other Industries Adopt Additive Manufacturing for Production Parts • Today’s Hybrid Machine Tools can Produce Finished Parts by Building Up Very Complex Geometries with Additive Processes, and Machining to Close Tolerances and Surface Finishes • AM Can Produce Complex Parts That Would Be Impossible To Manufacture Using Conventional Processes.
  17. 17. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 18 Advanced Robotics • Advanced Robotics or Cobots will move beyond production work cells to work with humans and other robots • Production lines will be run by Physical-Cyber Systems that will be able to self-optimize, self-heal, and run autonomously • IIoT will be driven by a new generation of Intelligent Edge Devices powering Predictive and Prescriptive Analytics that enable the Digital Twin
  18. 18. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 19 Machine Learning • Pattern recognition, Artificial Intelligence • Machine mimics human behavior • Related to data mining and statistics • Method of teaching computers to make predictions without programming
  19. 19. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 20 • Businesses Need an IIoT Strategy • Shift Towards Industrial Platforms • Edge Computing is a Critical Component of IIoT Discussion
  20. 20. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 21 Virtual and Augmented Reality in Manufacturing • Connecting the Real and the Virtual: Machines, Products, Operations • Connecting Virtual Product Design to Smart Production Systems Enables the Smart Factory • Augmented Reality Connects Virtual Design to Physical Equipment for Operations and Maintenance • Virtual Simulation Connects Mechanical, Electrical, and Controls Software to Validate and Commission Production Systems
  21. 21. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 22 • VR immerses the user in a virtual world – a headset isolates you from the real world • Hardware examples include Oculus Rift, HTC Vive • Unlimited virtual worlds possible • Limited physical range for the user – tethered to a powerful computer • Non-tethered: smartphone systems  Google Cardboard  Samsung Gear VR  Limited immersion Virtual and Augmented Reality in Manufacturing - Augmented Virtual Reality (VR)
  22. 22. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 23 • Augmented reality (AR) is a live director or indirect view of a physical, real-world environment whose elements are augmented (or supplemented) by computer-generated sensory input such as graphics or sound. • Information is overlaid on the environment • Users moves around freely in the real world • Self-contained, battery-powered user platform • Examples include DAQRI Smart Helmet (right), Microsoft HoloLens (bottom) Virtual and Augmented Reality in Manufacturing - Immersive Augmented Reality
  23. 23. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 24 The Workforce for the Factory of the Future • Factories will tend toward flatter management structures with a more highly skilled and IT literate workforce • There will be a change from “doing” the manufacturing to monitoring automated processes in real time and responding to feedback from machines and equipment to optimize the process capability and efficiency • Finding the talent to run these factories will be very important, along with a new focus on educating a highly technical and competent workforce able to implement and maintain advanced technologies • Greater collaboration is required between education, government, and industry to insure that those leaving (secondary and higher ed.) are equipped with the skills required for these future manufacturing environments
  24. 24. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 25 The Workforce for the Factory of the Future - Data Scientist is Important The data scientists are creating tools that contextualize and find the data, analyze the data and visualize the data…and give intelligence needed for valuable insights. Data is the New Oil Engineers, operations, operators and process experts are still important because they need to be able to make correlations and make actionable decisions based on the insights.
  25. 25. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 26 Open Process Automation: ExxonMobil Overall Scope and System Architecture Reference: http://wps1705.international-bc-online.org/wp-content/uploads/2017/09/1.-Forbes-ENG.pdf
  26. 26. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 27 • Software for the Factory Workforce of the Future • Extract Value from Data • Open Process Automation Initiative Discussion
  27. 27. Cybersecurity – What are We Trying to Protect? • Endpoints • Included - Devices that are used are commonly used within plants or remote SCADA systems and have a direct impact on operations – e.g. Servers, Workstations, PLCs, DCS, RTU, embedded systems, etc.. • Included – Laptops and other equipment that may be brought into plants or remote SCADA sites for maintenance, etc.. • Excluded – Personal devices like smartphones, IIoT devices located outside the plant, etc.. • Networks • Included - Industrial networks used within plants or remote SCADA systems to interconnect control system endpoints – e.g. networks for Levels 1, 2,3, and DMZs. • Excluded - Networks used by applications outside the plant or remote SCADA system to communicate with the control system – e.g. SCADA networks, enterprise networks, etc.
  28. 28. • Premises • Network and endpoint security solutions have become commonplace in industrial control systems (anti-malware software, next-gen firewalls, etc..). • Adoption of advanced solutions like application whitelisting and deep packet inspection (DPI) firewalls is also growing. • Despite these efforts, cyber intrusions continue and remain a serious concern for industrial companies. • Questions Manufacturers Have: • Is lack of cybersecurity maintenance the major issue? • Have we reached the practical limit of what can be done with technology to keep attackers out of our systems? • Do we need some other technology solutions to address gaps in the current solution set? • Do we have to accept that attackers will get into our assets and shift our attention to rapid detection and better incident management? Cybersecurity – What’s Really Needed to Secure Industrial Systems?
  29. 29. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 30 • Cyber Security Is Not Just a Feature, It’s a Mindset. • Cyber Security Is Not Just a Destination, It’s a Journey. Discussion
  30. 30. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 31 • Concept of Enterprise Architecture, linking Plant Floor Operations with Business Operations across Enterprise has existed in many sectors • Making concept a reality is challenging for companies without huge IT staffs or budgets • Industrial Internet of Things (IIoT) promise of accessing, aggregating, and analyzing data from standard assets and systems • Improved decision support and business performance represents further distribution Creating Modern, Open Enterprise Architectures in the IIoT Age
  31. 31. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 32 • Before ”Industrie 4.0” or “IIoT”, different data, hardware, and software at each plant • No easy way to get plant data to corporate level • With IIoT, high demand to acquire, view, and analyze more data from plant, turn into actionable information • Save millions, improve decision-making, centralized management, machine learning and predictive analytics • Transition to Enterprise System Architecture is a challenge • To meet demands, needs automated process to deliver plant information to corporate level that is accurate, standardized, efficient, and secure Creating Modern, Open Enterprise Architectures in the IIoT Age
  32. 32. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 33 • 1st Step: Shift away from spate OT & IT, align OT & IT so operational data shared with business applications • Avoid top-down, centralized enterprise architecture demand comes from top, but should be built bottom up, starting at sensor level, eye toward business objectives • Don’t think of plant as an island, but part of larger corporate system, common standards and data transport mechanism • Ask what is Needed To Do at plant level to support enterprise, answer always requires secure connectivity Creating Modern, Open Enterprise Architectures in the IIoT Age
  33. 33. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 34 • Balancing need for security with need for data • Existing technologies get data to central system in open format w/o compromise • “Air Gapping” was security measure, but isolates OT from IT • Separating IT & OT won’t help enterprise’s data needs • To ensure proper security, data should be encrypted when shared across sites • Place edge gateway next to PLC, get data into open format while keeping secure Creating Modern, Open Enterprise Architectures in the IIoT Age
  34. 34. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 35 • Build systems with central visualization & administration, essential to develop standards across entire enterprise • Plants with different PLCs, tags, addressing schemes, into standardized system, employ open-source protocol • Open standards: OPC UA, MQTT, get data from devices SQL: working with SQL databases: APIs (OPC UA, SOAP, REST) integrate with other systems • Once organization chooses open standard, standardize data models so all plant data looks same when sent to corporate • Protocol should have built-in encryption & “Stateful Awareness,” tells if connected to specific devices • Encryption & stateful awareness provides approach for getting operational data to business in standardized way without compromising operational security Creating Modern, Open Enterprise Architectures in the IIoT Age OPC UA & MQTT Protocols Both Offer Built-in Security & Stateful Awareness
  35. 35. Creating Modern, Open Enterprise Architectures in the IIoT Age • Open architectures that decouple applications from devices enables enterprise to get needed data without interrupting operations at plants • Example: Coupled architecture using a poll-response protocol on left; decoupled architecture using publish-subscribe protocol on right • Conventional System Architecture: Intelligent devices such as PLCs, coupled to applications through proprietary protocols, any application can interact with any connected device • SCADA software communicates with PLCs software often used as middleware because it has protocols needed to do so
  36. 36. Creating Modern, Open Enterprise Architectures in the IIoT Age • Decoupled Architecture: Applications not connected to devices, devices connected to infrastructure so applications can subscribe to required data • Rather than using SCADA as middleware, decoupled architectures often use message- oriented middleware, i.e.: MQTT • Devices publish data by exception up to central MQTT broker (on-premise or cloud), SCADA can subscribe to data, same data as ERP, MES, BI, etc. • Programs have direct access to data, plug & play device interoperability • Decoupled architecture provides single source of truth for tag info, better & simplified connectivity between sensors & applications across enterprise
  37. 37. Creating Modern, Open Enterprise Architectures in the IIoT Age • MQTT differentiated by lightweight overhead of two- byte header, publish/subscribe model, & bi-directional capabilities, need minimal network bandwidth • MQTT collects data from many devices, transports data to IT infrastructure, real-time, mission-critical SCADA systems, payload is data-agnostic • Used in applications: Facebook Messenger, Amazon’s AWS IoT service, IBM’s messaging middleware systems • Ignition’s OPC UA server provides connectivity to multiple protocols • Ignition’s open API facilities interaction & data-sharing between applications driver development for protocols, i.e.: MQTT
  38. 38. Creating Modern, Open Enterprise Architectures in the IIoT Age • Companies with multiple, disparate brownfield plants must standardize data & data models • Need tools to convert data to interoperable format • Edge gateways next to PLCs poll PLC data into decoupled, message-oriented middleware structure • Develop while existing SCADA directly communicates with PLCs then transition to new architecture • Vital to have solution that integrates tools for business intelligence, machine learning, open-source software, IoT, Edge computing, and business management Going forward, invest in solutions that integrate with other solutions to avoid data islands
  39. 39. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 40 • Build from the Bottom Up • Ignition is the Right Platform for Open Enterprise Architectures Discussion
  40. 40. In Summary - The Factory of the Future is Now!
  41. 41. Jim Meisler x227 Vannessa Garcia x231 Vivian Mudge x253 Account Executives: Myron Hoertling x224 Shane Miller x218 Ramin Rofagha x251 Maria Chinappi x264 Lester Ares x214 Kristen Azure x260 Call us at: 800-266-7798 Panelist: Craig Resnick Follow @CraigDResnick on Twitter Read Craig’s blog posts on arcweb.com Director of Sales: Melanie Hottman x247 Questions & Comments

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