Living
TABLE
OF CONTENTS
SECTION 1: Executive Summary
SECTION 2: Demographics
SECTION 3 : The Edge in the New OT Ecosystem
SECTION 4: Edge Forms and Types
SECTION 5:
SECTION 7:
SECTION 8 : Recommendations and Resources
Executive Summary Section 1
Executive Summary
Edge computing is one of today's leading disruptive digital technologies . Until recently, it was overshadowed by the Cloud with its power, scalability, and as-a-service platform capabilities . However, there is an increasing realization that both have their place in the Industrial Internet of Things (IIoT) environment and that Edge offers a number of capabilities and advantages that make it a key player in the new Operational Technology (OT) Ecosystem, as well as in evolving Operational Architectures . This study builds on LNS Research's 2018 report: Enabling an Operational Architecture for Applications and Analytics. Moreover, this ebook discussed the evolution of Edge computing, where it came from, and where it is going, including illustrative case studies in the process, hybrid/ batch, OEM, and discrete industries . We will address the Edge market, plus recommendations on selection criteria and guidelines on applications, with expected benefits As we shall see, perhaps no other disruptive technology comes in so many different sizes and formats with its metamorphic ability to complement or replace existing hardware, or constitute an entirely new system, as well as support new capabilities, such as analytics at the Edge
THE EDGE COMPUTING WORLD
Section 2 Demographics
Survey Responses
LNS Research executed a global survey on the state of Industrial Transformation (IX) programs and related use cases We surveyed executives, management, IT, engineering, quality, and operations personnel across a wide range of industries and geographies . The survey had more than 300 respondents across the process, batch/ hybrid, and discrete industries Questions on analytics, Edge computing, and cybersecurity were included in the survey
Survey Responses (Cont.)
JOB TITLE
AREA OF RESPONSIBILITY
Section 3 Edge in the New OT Ecosystem
Edge in the New OT Ecosystem
Today's leading disruptive digital technologies are having a significant impact on the traditional Operational technology (OT) system architecture which, for years now, is based on the 1990s Purdue Enterprise Reference Architecture model embodied in the ISA 95 standard With the advent of the Cloud, big data, advanced analytics, including artificial intelligence (AI) and Machine Learning (ML), and low-cost computing, these Information Technologies have migrated into the OT environment to stay
CONNECTIVITY BUS
THE NEW OT ECOSYSTEM
Edge in the New OT Ecosystem (Cont.)
The result is that data can now be acquired from anywhere on the factory floor and across the supply chain, and computing capability can take place almost anywhere between the on-premise corporate data center and the data source itself This has led to two common definitions of what we know as Edge First, the IT definition of Edge where computing takes place anywhere outside of the corporate data center that is closer to the source of the data; and second, the OT definition which says that computing takes place at on, or very near the source of the data…on the pump, near the tank, on the equipment, or integrated with the machine
EDGE COMPUTING DEFINITIONS - How Do You Define Edge Computing?
a) Computing outside of the IT data center, nearer the data source
b) Computing at, on, or integral to the field device or equipment
Edge in the New OT Ecosystem (Cont.)
Thus, data acquisition from the process or factory operations is no longer limited to flowing through the control system, be it a Distributed Control System (DCS) or a Programmable Logic Controller (PLC) In addition, with the dawn of wireless technologies such as Wi-Fi and cellular communications, e g ., 4G and now 5G, many Edge devices will be wireless No matter which definition, Edge is an integral part of IIoT, where Edge’s role is to connect and deliver data to where it is needed, and in many cases, do much, much more
The ramifications of Cloud and Edge in the OT Ecosystem are pronounced, especially with Edge devices whose roles fall under both IT and OT IT/OT convergence has affected how roles and organizational structures are changing and positively impacting the need for focus on Edge . With IT generally leading the selection of Edge devices, OT needs to step up its roles and skillsets to deal with Edge . OT needs a greater understanding of operating systems, LINUX in particular, microservice architectures, communications protocols, and programming languages such as Python and Java, in addition to its traditional control system environment
Section 4 Edge Forms and Types
Edge Forms and Types
Edge devices also have roots in several sources and are used in multiple ways in the IIoT environment:
1 Traditional IT networking and computing devices
2 . Derived computing platforms
3 . Board level platforms
4 . Control system components
Traditional IT networking and computing devices include gateways, such as routers and switches, standard PCs and servers, devices long used in both IT and OT networks, and computing centers that are renamed Edge devices even though the devices haven’t essentially changed .
WHO'S USING WHAT? - Which Edge Device Companies Are You Currently Using?
Edge Forms and Types (Cont.)
The second group is computing platforms These include mini-PCs derived from standard hardware but modified for industrial use with special capabilities such as advanced graphics, built-in Wi-Fi, high availability and redundancy, hardened environmental enclosures, and other features . To date, most of the installed base to date of standard mini-PCs is in the batch/hybrid and discrete industries, while the derived versions with special characteristics are more likely found in the process industries .
WHO'S USING WHAT IN OT? - Which Edge Device Companies Are You Currently Using?
Edge Forms and Types (Cont.)
The third group includes board-level computing platforms, typically running Linux or micro-services, a good example of which is Raspberry Pi Here we also find several startups in the oil & gas upstream industry segment who have new novel designs and form factors that combine data acquisition, storage, control capability, application programmability, wireless communications, and battery backup all in one device .
SAMPLING OF EDGE DEVICES FOR UPSTREAM OIL & GAS
The last major category includes Edge devices from control systems vendors, both major DCS vendors, as well as smaller independent players Some of these vendors allow very flexible “rollyour-own” systems that combine traditional PLCs or controllers with Edge devices, standard input/output modules (I/O), human-machine interfaces (HMIs), and applications for a customizable solution . As traditional control systems “open up,” we have begun to see more hybrid architectures incorporating edge devices in various roles .
Finally, we note that many traditional field devices have been renamed Edge devices as additional capabilities, such as built-in sensors, on-device memory, programmability, and communication were added to improve operability LNS won’t identify this as a separate category, only to say that Edge capabilities can be added to traditional hardware .
UPSTREAM OIL & GAS
Section 5 Edge in Operational Architecture
Edge in Operational Architecture
In addition to Edge device location, Edge devices can also be categorized by the role they play in the operational architecture LNS Research sees five primary roles for Edge devices:
1 Connectivity and Access
2 . Data Acquisition
3 . Analytics
4 . Control
5 . Cybersecurity
Connectivity includes routers, switches, and other gateways, devices for connecting and controlling flow between and within networks and devices
The second use category is data acquisition . Edge devices, along with lower-cost sensors, are used to collect additional data from and around equipment, machines, and processes The data is usually passed on through the IIoT to the Cloud for advanced analytics, such as Digital Twins, but can be delivered anywhere on-premise, to a control system, to a historian, or to an advanced computing server running MES/MOM application Likewise, location, inventory level, and status in the supply chain are also common applications . Intelligent wearables that monitor worker location and biometrics can also be considered a form of Edge devices .
Edge in Operational Architecture (Cont.)
The third category combines data acquisition with analytics at the Edge . In this case, the Edge device may consume a smaller set of the overall data that might be processed in the Cloud, but because of its location in the plant or on the factory floor, lag time is minimal, and insights can be delivered faster for better decision-making
The fourth category takes it one step further and adds control functionality . Not unlike SCADA capabilities found in oil & gas, utilities, and water and waste, where PLCs, RTUs, and other control devices are distributed in the field, Edge devices now join the system to bring new capabilities to operating companies across all industries
LNS recognizes a fifth category, cybersecurity . While the majority of current cybersecurity software runs on standard servers, LNS sees the need for distributed cyber defense where active and passive techniques constantly monitor devices at all levels, particularly at ISA 95 levels 1, 2 and 3, which were once air-gapped from the upper levels, but are now integrated from the sensor to the Cloud Edge devices will allow cyber defense within and across IT and OT networks
Section 6 Edge in Service
Edge in Service
Let’s explore three use cases that illustrate the flexibility and adaptability of Edge devices .
1 Edge devices that replace traditional servers
2 . Edge devices for data acquisition and control in IIoT
3 . Edge analytics in IIoT
Edge Devices ‘Edge Out’ Traditional Servers
Traditional server technology running Windows or Linux-based applications has underpinned SCADA and DCS HMI consoles for many years . In the past, high availability or even redundant versions have been limited to hard drive disk mirroring (RAID) or custom hardware solutions Unfortunately, this does not make the balance of the system hardware and operating system fully redundant . Today’s new Edge computing technologies solve this problem by providing high availability or full redundancy in mini-PC form factors, such that high performance and space savings are achieved cost-effectively . Some manufacturers allow high availability to be upgraded to full redundancy should availability requirements change Some Edge servers are self-managing, requiring little to no administration, postinstallation and commissioning . Set it and forget it… Edge to the rescue .
Edge in Data Acquisition and Control
The fastest-growing segment for Edge devices is their use in acquiring data from the plant, factory floor, field, and along the supply chain Here we see a wide gamut of form factors and capabilities depending on the application and industry These Edge devices usually support a variety of device protocols, as well as on-board memory, battery backup, wired communication, such as OPC-UA, or wireless communications, such as Wi-Fi, Radio, Cellular, BlueTooth and Low Power WAN . Some devices also feature control capabilities, usually aimed at specific fit-for-purpose functionality rather than a more general controller offering, such as PID algorithms or PLC ladder logic
EDGE DEVICES IN THE FIELD AND ON-PREMISE
Edge In Service (Cont.)
Edge Analytics in IIoT
Taking the data acquisition and control devices a step further in capability, Edge analytics devices provide onboard programmability, using languages like Python, such that advanced analytics, e .g , Anomaly Detection and Machine Learning algorithms, can be implemented to provide rapid analysis and insights Thus, Edge facilitates the layered analytics approach that LNS Research has identified in the market:
1 Self-Service
2 . Systematic
3 . Global/Cross-Functional
Self-service analytics are focused on tools to support problem identification and analysis and are usually implemented on-premise on user desktops or from a shared server with web access . However, the systematic analytics and global-cross functional are far more likely to use hybrid architectures with at least a portion of their analytics implemented on-site, making Edge devices the perfect companion hardware Analytics at the Edge means low latency, improved security, and cost-effective implementation
Edge is particularly important for original equipment and machine builders who want to equip their products with functionalities, such as remote monitoring and advanced analytics, making them Smart Connected Products Rather than leave this to the operating company or system integrator to implement, the builder can leverage an Edge device with open communication capability, such as OPCUA, to implement their custom application . Then post-installation, the Edge device is only an Ethernet cable away from a connection to the plant or factory network
SMART CONNECTED ASSETS
Edge In Service (Cont.)
Edge Analytics in IIoT (cont.)
Second, the cybersecurity vendors, who also leverage advanced analytics, but with a specific fit-for-purpose application for detecting, containing, and recovering from cyberattacks . This allows cybersecurity solutions to be effectively distributed across all levels of plant and factory operations . Surprisingly, most cybersecurity applications are run on standard server hardware that requires administration and is less than 100% reliable . If cybersecurity is our sentinel at the gate, why would we want to tolerate any downtime?
Finally, except for Edge devices as stand-alone replacements for traditional servers, Edge in data acquisition, control, and analytics will all be part of an IIoT solution that manages the devices and the data that flows to and from them . IIoT and analytics providers usually provide this service, but increasingly we see the hyperscalers entering this very competitive space . While the hyperscalers (e .g ., Microsoft, Amazon, Alibaba, etc .) may initially lack domain applications, the fact that they can provide both ends of the hybrid architecture, Cloud and Edge, with an analytics and data storage platform for developing applications, is expected to appeal to those organizations that want to build their own solutions .
Section 7 Edge in the Market
Edge in the Market
Now that we have discussed the what, how, and where Edge is used, let’s take a look at its status of adoption . As we can see, the industry is still in the early phases of adoption outside of gateway Edge devices, with less than 20% implemented and no more than 30% in pilot stages . Of concern is that nearly half of process industry respondents reported that they have no plans to implement Edge yet, perhaps indicating that the case to add Edge into the plant data acquisition, analytics, and control environment has yet to be made . Thus, it would seem little progress has been made since LNS Research's initial study in 2018.
EDGE INITIATIVES: Has Your Company Started an Initiative to Implement and Utilize Edge Computing Platforms?
Implemented
Edge in the Market (Cont.)
So what is holding Edge back? Between being tied up with other initiatives and budget limitations, Edge has yet to garner significant attention . This situation is further bolstered by the data that show that respondees have yet to fully define their Edge strategies and primary reasons for implementing Edge A second reason is that most companies have yet to realize the differences and advantages of Edge devices over industrial PCs Since IT departments typically look to their major suppliers for Edge computing devices, they find new product offerings in different form factors, but don’t always see the new and innovative Edge devices coming to market from OT and other independent hardware suppliers
WHY NOT EDGE? Why Has Your
We are busy with existing major IT projects
Budget Constraints
Lack of understanding about Edge
Difficulty hiring personnel for technology partners
Please specify.
Organization Not Launched or Planned and Edge
Program?
Edge in the Market (Cont.)
Our research also shows that most companies, regardless of industry segment, including OEMs, are still exploring and testing, with few corporate-wide roll-outs or adding Edge with analytics to their product lines
DRIVERS FOR EDGE? What is Your Company's Primary Driver for Implementing Edge Computing Platforms?
Gathering IIoT data for new apps. e.g., Digital Twins, emissions monitoring, etc.
Supplementing current control systems capabilities
Exploring the potential replacement of current field devices. e.g., RTUs, PLCs, etc.
Eliminating the need to collect all high-resolution data through the control system to the process historian
Reducing the response time latency of applications
Other drivers. Please specify.
In addition, the major Distributed Control Systems (DCS) vendors have been slow to incorporate Edge devices into their architectures, for concern that they will only speed up the substitution or even disintermediation of their own hardware with lower cost and lower margin Edge devices . The primary exception is the very active oil & gas upstream onshore segment where operating companies are searching for alternatives to existing field hardware, much of which is generations old and cannot be upgraded with modern communications, control, analytics, and security capabilities .
Section 8 Recommendations and Resources
Operating Companies
The lessons from IX Leaders provide a set of guidelines that operating companies should follow in adopting new technologies, especially when considering Edge computing and in light of what LNS Research's data is telling us:
1 The Power of More means that companies should have a larger functional scope, breadth, and focus for Edge because of its broad applicability In addition, as is the case for all IX technologies, funding at the margins or reallocating funds away from existing initiatives has proven unproductive Allocate extra funds to pursue Edge
2 Second, take a top-down and bottom-up approach . While IT will play a significant role in choosing and deploying Edge technologies, leaving the plant or factory management and OT personnel out of the equation will impede success . IT needs to work with the plant, factory, and supply chain personnel to improve ways of collecting data to drive better decision-making, and thus how and where Edge is deployed and what it should do
3 . Closely related to the approach is the focus on business problems and opportunities to use IIoT and Edge to bridge data acquisition and processes across silos, rather than just within silos OT personnel should consider Edge when planning for or expanding control and other operational systems, especially with IIoT beginning to permeate the OT Ecosystem Now is the right time to get started . Use your initial business cases to test Edge computing in your OT environment
4 Finally, since leaders have a high degree of commonality across plants and factories and work to harmonize systems and, most importantly, data collection across plants, it follows that Edge solutions should also follow the same guidelines. Many companies have a variety of control systems solutions across their plants that are not easy to harmonize, nor would make economic sense to do so, until obsolescence forces the issue . Why repeat the same with Edge? Keeping the types of Edge devices to a minimum, which are capable of carrying out multiple missions, is highly desirable .
Original Equipment and Machine Builders
Equipment and machine builders have the opportunity to expand their products by adding Edge products for remote monitoring and diagnostics . While these functions are not new, older designs limit their functionality, particularly in handling large volumes of data and analytics Edge devices offer a unique platform in which to consolidate this service, including support for subscription-based business models
Original equipment and machine builders have a plethora of options to choose from; so like operating companies, those vendors who offer flexibility, scalability, connectivity, and minimum support, which can run whatever application, will be your best bet Given big goals, small budgets, and an organizational challenge around IT/OT, OEM and machine builders need to be flexible and scalable when it
EDGE IN OEM AND MACHINE BUILDERS
comes to future computing, application, and analytics needs – able to plug and play into a diverse set of architectures and do it with limited support from IT For example, avoid Edge devices that tie your applications with the hardware as this will only lead to higher costs and limit upgradeability .
Consider the fact that OEM, plant, factory and field IT and OT personnel are likely already challenged to manage the sheer number of devices under their purview, especially those that are remote .
The more reliable the Edge device is and the less administration it requires, the more it will simplify their jobs and lower the overall Total Cost of Ownership (TCO), even if the Edge device may cost more initially or some downtime is tolerable . Thus, it pays to do a thorough TCO evaluation
Vendors
It is critically essential for vendors to know what markets and applications they are serving, and why, as well as understand their customers' operations, how data is acquired and flows to decisionmakers These requirements will drive your designs and product line offerings . Note that converting existing products or renaming them Edge devices generally will not cut it Edge devices should be looked at as lean, multi-purpose “swiss knives” able to fit in any architecture in any location . Given that 90% of Edge devices currently cost between $500 and $5,000, sales volume will be the name of the game to lower the costs of manufacturing and generate acceptable margins Specialized niche players with unique value propositions will also do well . Remember that IT is in the lead for choosing Edge devices, even for OT applications, so that they will bring a different perception to evaluating Edge devices than OT, i .e , standardization, connectivity, scalability, compatibility, manageability, and of course, cost . With the decoupling of software from hardware and virtualization, vendors should focus on flexibility and adaptability And expect to meet the demands of both IT and OT
CHOOSING AN EDGE DEVICE
Edge criteria include but is not limited to:
Role/Application
Size and form factor
Power requirements
Enclosure and environmental rating
Hazardous area classification
Memory capacity
Programming languages supported
Communication protocols & connectivity
Security
Reliability
Scalability and upgradeability
Administrative requirements
As we previously noted, Edge devices come in all shapes and sizes, from general-purpose to industry and application-specific designs, and Edge vendors range from Big Tech to automation to large and small to startups . While the major Cloud vendors can be counted on one hand, counting Edge device vendors begs for centipedes . Overall, market growth is strong, but adoption is still relatively early, particularly for data collection, analytics, and control applications . Standard designs have yet to fully emerge and scale in volume across the majority of industries, with discrete leading the way through the use of the mini-PCs, which are readily adaptable to the factory floor environment . Who, how, and where they will break through remains to be seen
What’s next for Edge? Are we still in the hype phase, or have we passed? Unlike many other technologies that pass through the hype curve, Edge is not a technology that is not understood or that does not work . Rather, it is a technology that hasn’t fully matured technically, outside of gateways and servers, nor found its rightful place in the new OT Ecosystem . Thus, there is a way to go until we reach the plateau of productivity .
Nevertheless, LNS Research expects a degree of consolidation in the market as vendors realize what designs best serve customers' needs, and customers become more aware of what they want in an Edge device Within the next 1-2 years, Ecosystem architectures will begin to include Edge devices in their networks . Part of the progress is timed with the opening up of control systems and the OPA initiative The exception will be in the upstream oil & gas segment where several startups are battling for position with traditional Big Tech and automation vendors in this highly diverse market with no clear winner yet in sight .
Industrial Transformation Resource Guide
Companies use digital technology to drive transformation across the value chain Use these resources to learn how to align the people, processes, and technologies required to achieve Operational Excellence in your organization .
INDUSTRIAL TRANSFORMATION
BLOG | Introducing the Industrial Transformation (IX) Reference Architecture
View Blog
RESEARCH | Industrial Transformation Success: How to Secure Operations' Buy-in to Create Effective Leadership
View Research
BLOG | Understanding Industrial Transformation: Definition and Framework for Success
View Blog
RESEARCH | Industrial Transformation: Architecture and Analytics
Just the Beginning
View Research
RESEARCH | Industrial Control Systems and Edge Computing: Enabling an Operational Architecture for Applications and Analytics
View Research
INDUSTRIAL ANALYTICS
RESEARCH | Build a Flexible Industrial Analytics Strategy for Today and Tomorrow: Why Business Leaders Should Adopt a Use Case Approach
View Research
BLOG | How the Right Operational Architecture Powers the Analytics That Matter
View Blog
RESEARCH | Analytics Really Do Matter: Driving Digital Transformation and the Smart Manufacturing Enterprise
View Research
FACTORY OF THE FUTURE
RESEARCH | Factory of the Future: Industrial Transformation is Changing How We Run Our Factories
View Research
BLOG | The Factory of the Future and People
View Blog
RESEARCH | Improving Continuous Improvement: Reinvent Lean Today with Digital Technology
View Research
RESEARCH | Forging the Digital Twin in Discrete Manufacturing: A Vision for Unity in the Virtual and Real Worlds
View Research
RESEARCH | MOM and PLM in the IIoT Age: A Cross-Discipline Approach to Digital Transformation
View Research
Industrial Transformation Resource Guide (Cont.)
4.0
RESEARCH | APM and Risk Management: A Comprehensive Approach Beyond Asset Reliability View Research
BLOG | APM 4.0 and Risk Management — Industrial Transformation (IX) Leaders Connect the Dots
View Blog
Solution Selection Guide | Asset Performance Management (Platform Vendors), 2018 Edition
View Solution Selection Guide
RESEARCH | APM 4.0: Prescription for Better Profitability in Operations View Research
RESEARCH | The Road to Digital Transformation Success: A Methodology to Modernize Operational Excellence
View Research
RESEARCH | Unify EHS and Quality: Capture Synergies and Turn Policy into Action
View Research
RESEARCH | The Connected Worker: Mobilize and Empower People to Reduce Risk and Improve Safety
View Research
QUALITY, COMPLIANCE
RESEARCH | Quality 4.0 Impact and Strategy Handbook
View Blog
RESEARCH | Driving Operational Performance with Digital Innovation: Connecting Risk, Quality and Safety for Superior Results
View Research
RESEARCH | Roadmap to Supplier Status: Think Risk Performance, Not Compliance View Research
ENVIRONMENT, HEALTH AND SAFETY
RESEARCH | Futureproof EHS Management: Digitally Transform Safety, Risk, and Environmental Performance for Long-Term Value
View Research
WEBCAST | EHS 4.0: Using Technology to Reach New Levels of Safety and Environmental Performance
Watch Webcast
Industrial Transformation Resource Guide (Cont.)
INDUSTRY FOCUS
AUTOMOTIVE RESEARCH | IATF 16949-2016: A Pivotal Opportunity in Automotive Quality Management View Research
AUTOMOTIVE AND A&D RESEARCH | Manufacturing Performance: Automotive and A&D Gaining Momentum with Analytics View Research
LIFE SCIENCES RESEARCH | Digitalized Quality in Life Sciences: Roadmap to Sustainable Growth and Speeding Profitable, High-Quality Products to Market View Research
LIFE SCIENCE RESEARCH | Quality 4.0 in Pharmaceutical: Use Cases and Advantage in a Digitally Maturing Market View Research
METALS AND MINING RESEARCH | Data for Balanced Scorecard: Driving Profits in Mining, Metals, and Materials Industries View Research
POWER GENERATION RESEARCH | Driving Better Decision Making with Big Data: A Roadmap for Digital Transformation in the Power Generation Industry View Research
EDGE COMPUTING IN THE NEW OT SYSTEM
Living on the Edge
Authors:
Joe Perino
Principal Analyst
joe perino @lns-global com
Matthew Littlefield
President & Principal Analyst
matthew .littlefield@lns-global .com
Vivek Murugesan
Research Associate
vivek murugesan@lns-global com
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