Millennials have a reputation for embracing technology to share information, stay connected, and improve their productivity. The Industrial Internet of Things (IIoT) is doing the same for production machines.
Many of the life-changing advancements brought to bear by the Internet of Things (IoT) stem from cloud storage and cloud analytics: controlling your home with your voice, seeing inside your fridge with an app, and storing and accessing every picture ever taken of your children on any smart device from anywhere in the world. These technical marvels would be pure wizardry to anyone living 50 years ago.
Timing is essential to IIoT networking
The Industrial IoT (IIoT) doesn’t get as much mainstream attention as its consumer-oriented cousin, but it will arguably have an even greater impact on our society. The IIoT can be defined as a vast number of connected industrial systems that are communicating, coordinating, and acting on shared data to improve the performance of operational technology (OT).
By this definition, it’s tempting to think of the IIoT as simply a hardier variant of the IoT. This line of thinking has given rise to devices like IIoT gateways, which can be thought of as the fax machines of the IIoT, translating OT data for the IT infrastructure. Although gateways enable the communication of OT data to the cloud (or fog), they usually scrape away something fundamental to most IIoT systems: time.
We tolerate (barely…) some level of lag, delays, and reloads while streaming Game of Thrones on HBO GO. But these glitches cannot exist between two high-speed assembly robots or, worse yet, between a geofenced safe zone and the brakes of an autonomous earthmover.
Edge Nodes: the key to maximizing IIoT speed and reliability
Employing the IIoT to monitor and control our farms, test facilities, power grid, and factories means we must do more than simply collect and share operational data; we must also understand the importance of data latency and synchronization between our connected, industrial assets. Put simply, IIoT success hinges on the communication of the right data at the right time.
This IIoT fact of life has given rise to a layered architecture defined by the Industrial Internet Consortium (IIC) called the Industrial Internet Reference Architecture. This IIoT architecture consists of three tiers: the Edge Tier, Platform Tier (on-premises IT), and Enterprise Tier (cloud-based IT).
In the IIoT, decisions can happen at all three tiers, and the volume and timing requirements of the data normally dictate how to architect a system. Maximizing performance and reducing unnecessary data transfers are two primary reasons for pushing decision-making down to Edge Nodes deployed at or near OT assets. In this light, IDC predicts that by 2019, at least 40% of IoT-created data will be stored, processed, analyzed, and acted upon close to, or at the edge of, the network.
Edge Nodes, like CompactRIO, can certainly maximize the speed and reliability of IIoT control loops. They also serve an important role in data reduction, feature extraction, and decision-making. For instance, by pushing machine learning models for predictive maintenance to the Edge Tier, CompactRIO can locally detect an anomaly and determine what the potential impact of the anomaly is on the lifetime performance of the asset, without burdening the IT infrastructure. From there it can work, through the less time-critical Platform and Enterprise tiers, to schedule the appropriate repair/replacement service. Flowserve, one of the world’s largest suppliers of industrial and environmental machinery, is working with PTC, HPE, and our own teams to implement such a solution for their customers today.
Though the IIoT megatrend is taking the OT world by storm, our customers have been quietly adding distributed measurement and control systems to their assets for decades. With connectivity to any sensor, nanosecond analysis and control, open and connected software, and world-class ruggedness, we're uniquely positioned at the IIoT edge.
Time-sensitive networking, IIoT Lab: what we're doing to advance the IIoT
Looking to the future, we're working tirelessly with our partners to create industry standards and prove out IIoT concepts. We recently opened the Industrial IoT Lab, which showcases the latest IIoT technologies and provides a collaborative space for an expansive ecosystem of partners with different expertise to work on solutions that will change the way businesses operate.
One vital IIoT technology featured in the Industrial IoT Lab (and mentioned previously in this blog) is Time Sensitive Networking (TSN). TSN is the evolution of standard Ethernet (IEEE 802.1) to provide deterministic data transfer and Edge Node synchronization down to 100 ns. By using standard Ethernet components, the cost to achieve TSN levels of determinism and synchronization for the IIoT will be much lower than using specific cabling or boutique Ethernet variants.
We’re confident that the IIoT will benefit greatly from TSN, ensuring the secure, predictable, reliable and uninterrupted flow of information from sensor to cloud.
Kyle Voosen, Ali Bravo, and I recently represented NI at the Q1 2017 Industrial Internet Consortium (IIC) meeting in Reston, Virginia, near Washington, DC. NI is a member of the IIC, which hosts this meeting for industry leaders from around the globe to accelerate the development and adoption of the Industrial Internet of Things (IIoT).
As the IIoT matures, the areas of focus for the IIC have become clearer. The meeting introduced the concept of “hotspots” that exist at the intersection of IIoT use cases and IIoT vertical industries, where IIoT interoperability is especially challenging or undefined.
To help address these “hotspots,” the IIC focused on testbeds that prove out ways to overcome challenges and realize the benefits of the IIoT sooner. The IIC plays a strong role in shepherding the development of testbeds that demonstrate the usefulness and viability of IIoT technologies, applications, and processes. This meeting provided testbed leaders the opportunity to update the membership on their progress.
IIC member companies are actively developing 21 testbeds that range from Condition Monitoring & Predictive Maintenance to Communication and Control for Microgrid Applications. They’re even developing the Smart Airline Baggage Management Testbed, which I wish would hurry up! Though testbeds are diverse, Mitch Tseng from Huawei reminded the crowd that, “From 36,000 feet, every testbed looks the same,” which means they all adhere to the three-tier IIoT model described in the Industrial Internet Reference Architecture. This model consists of the Edge Tier, Platform Tier, and Enterprise Tier. The Edge Tier often lists CompactRIO as the edge node of choice when testbeds require advanced measurements or computational power at the edge.
Time Sensitive Networking (TSN) Wins the Testbed Showcase
The meeting featured the first-ever Testbed Showcase that educated attending members on the strategic value provided by eight key testbeds, half of which involve NI. I presented an overview of the Time Sensitive Networks for Flexible Manufacturing Testbed. I began by reminding the audience that for the IIoT to be successful, a network is essential, data communication is vital, and siloed, proprietary systems are bad.
TSN is the evolution of standard Ethernet (IEEE 802.1) to provide deterministic data transfer and edge node synchronization down to 100 ns. By using standard Ethernet components, the cost to achieve TSN levels of determinism and synchronization for the IIoT will be much lower than using specific cabling or boutique Ethernet variants.
Nineteen companies, including NI, Cisco, Intel, and Bosch, are working together on the TSN Testbed to ensure network performance and interoperability among vendors. This level of activity helps explain why the TSN Testbed was voted the Most Valuable Testbed by IIC meeting attendees at the Testbed Showcase! Votes were based on criteria like vision, goals, impact, and benefit, along with innovation and experimentation, and outputs and results.
The meeting wasn’t all about testbeds, though. We’ll continue to play an active role in developing testbeds for the IIoT, but there are many projects and “tasks forces” in flight. Look for other updates from the quarterly meeting soon!
Embedded World is one of the world’s largest gatherings for embedded technology, bringing more than 30K people to Nuremberg, Germany from across the globe to experience the latest tech impacting the embedded industry. Here's a summary of what happened at the event, though our NI lens.
So why is time-sensitive networking so important for embedded this year? We address this directly in our TSN keynote at NIWeek 2016 last fall. Here’s an updated transcript of that keynote, featuring our own Jamie Smith and Todd Walter, Intel’s Kevin Stanton, and Cisco’s Paul Didier. You can also watch the keynote above.
The internet of things (IoT) continues to capture headlines around the globe, as technology companies everywhere begin to leverage the opportunities and competitive advantages connected devices bring to business. 2017 will be a big year for embedded monitoring based on the industrial internet of things (IIoT): millions of connected monitoring devices providing big data about machine/grid performance. Embedded World 2017 in Nuremberg will give us a great look at how companies are leveraging the IIoT, and how the industry is adapting.
This summer we commissioned a study from research agency IDC, studying the best practices for internet of things (IoT) implementations and how companies can prepare themselves for IoT-based operations.
Here are the best practices for taking on any IoT project as a business:
Have a clear understanding of business objectives and what business value an IoT project will deliver.
Start with an objective that has organizational pull and already has identified business value.
Have an executive champion who will make the project a priority.
Have a start-up mentality. Start small, such as with a pilot project, and establish clear milestones.
Build in security from the start. Security and privacy concerns are the number 1 hindrance to the deployment of an IoT solution.
Own the data that will result from the project, and know if you’ll manage it yourself or will need to have others manage it for you.
Connect the IT and operations teams in your org to the end customer that will be served by the IoT project. This connection along the value chain of your project provides a level of trust that will smooth its approval, implementation, and use.
Small and medium-sized businesses with limited IT departments should plan on having systems integrators and other partners work onsite as much as possible.
Use products based on standard platforms as opposed to custom platforms as possible. Standards help ensure the compatibility and scalability of the end solution.
Use products that are flexible and extensible. Ideally based on software, such products can adapt after their initial deployment to evolving requirements with no hardware changes.
Companies that’ve already worked to define and implement IoT projects and access the IoT’s value are trailblazing an immature and evolving environment.
By applying these best practices for implementing IoT in your org, you can access the benefits of this huge emerging market while avoiding the significant pitfalls experienced by these trailblazers.
We’ve built a new pair of cRIO controllers and teamed up with Cisco to enable creation of distributed systems that perform synchronized I/O, code execution, and deterministic communication, all using the latest additions to standard Ethernet. Together those controllers create technology engineers are already using to help vet the technology in ecosystem activities, including the Industrial Internet Consortium TSN Testbed for smart manufacturing.
The tech specs The technology includes new CompactRIO controllers featuring Intel Atom processors and the Intel i210 TSN-enabled NIC for a high performance control system. These controllers use LabVIEW system design software to maintain synchronized time to the network and expose that time to code running on the real-time processor, as well as the code running on the FPGA.
LabVIEW’s already designed with time as a core concept using structures such as timed loops and single-cycle timed loops. Now these structures are synchronized to network time which makes it simple for users to tightly coordinate signal processing, control algorithms, and I/O timing with scheduled network transmission and between multiple systems distributed across a network. Additionally now with TSN these systems can deterministically send data across standard Ethernet networks to create reliable multi-controller coordinated systems.
How to get early access To get early access to these new controllers you can:
Join our Time Sensitive Networks on our online Community, where you’ll find example code and documentation, along with more detailed info on hardware and software capabilities, and details on the appropriate products/accessories you need to create deployable TSN systems.
Time-sensitive networking (TSN) enables the creation of distributed, synchronized, hard real-time systems over standard Ethernet. These systems use the same infrastructure to provide real-time control and communicate all standard IT data, powering convergence of control, measurement, configuration, UI and file exchange infrastructure. TSN’s expected to fundamentally change system design and maintenance by offering network convergence, secure control traffic and high performance!
We commissioned a study from research agency IDC, studying the best practices for internet of things (IoT) implementations and how companies can prepare themselves for IoT-based operations.
The study found the following key drivers necessary to prepare business operations for the adoption of IoT implementations:
Business uptime. Customers, competition, and government increasingly require organizations to function 24 x 7. Orgs are turning to implementing IoT as a way to maintain operations continuously and provide the tools to respond quickly and efficiently, and are looking to their solution providers — technology providers, contract manufacturers, OEMs, and so forth — to enable constant uptime and work in concert to provide new solutions that enable additional services. Example: the installation of sensors on equipment to enable remote diagnostics and predictive maintenance of systems. This enables operations to anticipate and schedule system downtime rather than shut down operations. Companies are depending on their technology providers to integrate systems without disrupting operations.
Automation. Orgs have realized 24x7 operations are beyond ordinary human abilities to assimilate incoming requests and respond efficiently. They’re looking to IoT to embed machine intelligence into their operations and automate complex processes that enable greater worker productivity. Example: embedding intelligence into tools so that the proper specifications (torque, depth, etc) are communicated to the operator and the final reading is taken and documented, verifying the completed operation.
Real-time data. Automation requires moving from sporadic, limited data collections to continuous, expansive, real-time data collection and analysis. IoT enables both the low-level collection of data and rudimentary machine analysis and the high-level human analysis for decision making. Companies are still determining whether to push embedded intelligence to the edge or expand the utilization of cloud capabilities. The operational business model, the model’s demand on data latency requirements, the connectivity environment, and costs are key decision key factorshere.
Environmental context. The IoT’s continuous collection of data enables constant input on the environmental conditions in which an organization operates. Data humans would miss can be captured and provide the context for improved understanding of the environmental conditions contributing to a particular outcome. The expanded usage of a wide array of sensors is driving the growth of data, storage, and bandwidth.
Connectivity. Connectivity of equipment is a basic building block of efficient operations. When equipment communicates automatically without human intervention, it can fundamentally change an organization’s capabilities, both human and machine. For example, internal applications can connect to remote applications. Humans can concentrate on enabling higher capabilities, such as managing, organizing, and analyzing the incoming data rather than just gathering data manually from disconnected systems. While there are a wide array of existing communication protocols, there are a number of organizations working to unify the various emerging standards. Location, environmental conditions, and operational demands are important considerations in the selection of the communication method and protocols.
Smart City. While orgs may be thinking primarily about their internal operations, IoT opens the prospect of interconnectivity with other IoT-enabled organizations. Scaling of cooperation from a single partner to a constellation of ecosystem suppliers will eventually enable Smart City IoT. Infrastructure, replacement cycle expectations, ownership and leasing contracts, and the potentially wide variety of governmental agencies necessary for approval must all be taken into consideration.
We’re bringing an unprecedented level of interoperability to operational technology (OT) and informational technology (IT).
Our open, software-centric platform forms the bedrock of the Condition Monitoring Tested at the forefront of machine learning. By adding SparkCognition’s data analytics to the mix, the testbed processes big data much faster - allowing you to proactively avoid unplanned equipment fatigue and critical asset failure faster by having advanced insights into equipment health and remediation solutions. The technology supports some serious operational improvements:
Increased operational efficiencies
Decreased maintenance costs
In a new age of big analog data, machine learning is a primary way to harness information. The ability to collect raw data and derive insights to improve operations, equipment and processes offers huge cost savings and competitive advantages as data warns operators about component failures before they occur, identify sub-optimal operating conditions, and assist with root-cause analysis.