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

2. Moderator
Don Pearson
Chief Strategy Officer
Inductive Automation

3. 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

4. Used by Major Companies Worldwide

5. 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

6. Guest Presenter
Craig Resnick
Vice President, Consulting
ARC Advisory Group

7. 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

8. 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

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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

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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

11. Digital Enterprise - Opportunities

12. 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

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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.

14. 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.

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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)

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More data, more compute & storage power, better tools
Advanced Analytic Tools

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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.

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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

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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

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• Businesses Need an IIoT Strategy
• Shift Towards Industrial Platforms
• Edge Computing is a Critical Component of IIoT
Discussion

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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

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• 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)

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• 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

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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

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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.

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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

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• Software for the Factory Workforce of the Future
• Extract Value from Data
• Open Process Automation Initiative
Discussion

28. 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.

29. • 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?

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• Cyber Security Is Not Just a Feature, It’s a Mindset.
• Cyber Security Is Not Just a Destination, It’s a Journey.
Discussion

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• 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

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• 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

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• 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

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• 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

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• 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

36. 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

37. 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

38. 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

39. 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

40. VISION, EXPERIENCE, ANSWERS FOR INDUSTRY © ARC Advisory Group • 40
• Build from the Bottom Up
• Ignition is the Right Platform for Open
Enterprise Architectures
Discussion

41. In Summary - The Factory of the Future is Now!

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