A few of us gathered for a round table discussion of Internet of Things while I was at Dell Technologies World at the beginning of the month. I arrived a little early and had a private round table for several minutes before others arrive and the discussion became broader.
Ray O’Farrell, CTO of VMware and GM of IoT at Dell Technologies, said the focus of last 6 months since the new Internet of Things organization was announced included these three points:
1. Dell is 7 companies, trying to achieve one cohesive strategy across all; one organization when facing customers.
2. Best way is to work within the ecosystem, that is history of VMWare.
3. Building technology and leverage solutions. This is a complex undertaking as not all challenges within IoT are alike—there are few cookie cutter applications.
The evolution of Internet of Things within Dell to Dell EMC to Dell Technologies constitutes an upward spiraling path encompassing the greater breadth of technologies and organization reflecting the post-merger company. When I first came along, the concept was building an ecosystem around selling an edge device appliance. Now the strategy is much broader bringing the goal of IT/OT convergence closer to reality. As I’ve mentioned before, the IT companies are attacking that convergence from the IT side after years of manufacturing/production oriented suppliers trying to accomplish the same thing from the OT side. Maybe like the old country song we’ll meet in the middle someday.
Everyone talks Artificial Intelligence (AI) these days, and Dell Technologies is not exception. However, AI is not the science fiction doom and gloom predicted by Ray Kurzweil, Elon Musk, and others. Mostly it entails machine learning (ML) from detected patterns in the data.
Or as Dell Technologies says, it is applying AI and ML technology to turn data into intelligent insights, drive a faster time to market, and achieve better business outcomes.
• Dell EMC PowerEdge expands portfolio to accelerate AI-driven workloads, analytics, deployment and efficiency
• Deepens relationship with Intel to advance AI community innovation, machine learning (ML) and deep learning (DL) capabilities with Dell EMC Ready Solutions
• Dell Precision Optimizer 5.0 now enhanced with machine learning algorithms, intelligently tunes the speed and productivity of Dell Precision workstations.
• Dell EMC uses AI, ML and DL to transform support and deployment
14th generation Dell EMC PowerEdge four-socket servers and Dell Precision Optimizer 5.0 are designed to further strengthen AI and ML capabilities.
According to the recently released update of the Enterprise Strategy Group (ESG) 2018 IT Transformation Maturity Curve Index, commissioned by Dell EMC, transformed companies are 18X more likely to make better and faster data-driven decisions than their competition. Additionally, transformed companies are 22X as likely to be ahead of the competition with new products and services to market.
“The Internet of Things is driving an onslaught of data and compute at the edge, requiring organizations to embrace an end-to-end IT infrastructure strategy that can effectively, efficiently and quickly mine all that data into business intelligence gold,” said Jeff Clarke, vice chairman, Products & Operations, Dell. “This is where the power of AI and machine learning becomes real – when organizations can deliver better products, services, solutions and experiences based on data-driven decisions.”
Unlike competitors’ four-socket offerings, these servers also support field programmable gate arrays (FPGAs)3, which excel on data-intensive computations. Both servers feature OpenManage Enterprise to monitor and manage the IT infrastructure, as well as agent-free Integrated Dell Remote Access Controller (iDRAC) for automated, efficient management to improve productivity.
Dell EMC is also announcing its next generation PowerMax storage solution, built with a machine learning engine which makes autonomous storage a reality.
Leveraging predictive analytics and pattern recognition, a single PowerMax system analyzes and forecasts 40 million data sets in real-time per array4, driving six billion decisions per day5 to automatically maximize efficiency and performance of mixed data storage workloads.
The new Dell Precision Optimizer 5.0 uses AI to automatically adjust applications running on Dell Precision workstations to maximize performance by:
• Custom-optimizing applications: Dell Precision Optimizer learns each application’s behavior in the background and uses that data to employ a trained machine learning model that will automatically adjust the system to optimized settings and deliver up to 394% improvement in application performance.
• Automating systems configuration adjustments: Once activated and a supported application is launched, the software automatically adjusts system configurations such as CPU, memory, storage, graphics and operating system settings.
Speaking of partners and collaboration, Dell Technologies and Microsoft join forces to build secure, intelligent edge-to-cloud solution featuring Dell Edge Gateways, VMware Pulse IoT Center, and Microsoft Azure IoT Edge
• Joint IoT solution helps simplify management, enhances security and help lowers cost of deployment at the edge
• Built on innovative analytics applications, management tools and edge gateways to enable network security from edge devices to the cloud
• Accelerates IoT adoption in industry verticals key to economic growth and development
The joint solution offers an underlying IoT infrastructure, management capabilities, and security for customers looking to deploy IoT for scenarios like predictive maintenance, supply chain visibility and other use cases. The solution will deliver:
• Intelligence at the edge with Microsoft Azure IoT Edge: This application extends cloud intelligence to edge devices so that devices can act locally and leverage the cloud for global coordination and machine learning at scale
• Management and monitoring of edge devices with VMware Pulse IoT Center: This provides more secure, enterprise-grade management and monitoring of diverse, certified edge devices including gateways and connected IoT devices, bios and operating systems. This ecosystem will be built over time involving deeper integration and certification to support customer requirements.
• High-performance, rugged Dell Edge Gateways: IoT devices with powerful dual-core Intel® Atom™ processors connect a variety of wired and wireless devices and systems to aggregate and analyze inputs and send relevant data to the cloud
VMware Pulse IoT Center will serve as the management glue between the hardware (Dell Edge Gateways or other certified edge systems), connected sensors and devices and the Microsoft Azure IoT Edge. Initially, Pulse will help to deploy the Microsoft Azure IoT Edge to the requisite edge systems so that it can start collecting, analyzing and acting on data in real-time.
Hannover Messe was the place to learn the latest about all things digital—digital twin, Industry 4.0, Industrial Internet of Things (IIoT). SAP was one of the many stops in my itinerary advancing the trend.
My contact at the SAP booth at Hannover wasn’t around when I arrived for my appointment, so I left—only to get a text a half-hour later that he had arrived. But I was off to another appointment by then. However I did glean this information from the company at and following the show.
SAP enters the digital twin era
SAP SE has introduced SAP S/4HANA Cloud for intelligent product design, a new solution for collaborative research and development.
The solution, which is built on SAP Cloud Platform using SAP’s latest digital twin technology, is one of the building blocks for a network of digital twins to enable new business models.
Powered by SAP Leonardo and integrated with business processes in the digital core, SAP S/4HANA Cloud for intelligent product design enables customers to accelerate product design and development with requirement-driven systems engineering and instant collaboration across an extended network of suppliers and partners.
“The solution provides shared views of digital twin information for customers to gain live insights on new products and to store, share and review engineering documents with internal and external participants,” said Bernd Leukert, Member of the Executive Board of SAP SE, Products & Innovation.
SAP’s network of digital twins synchronizes the virtual, physical, conditional, and commercial definitions of assets and products in real time to accelerate innovation, optimize operating performance, predict service requirements, improve diagnostics and enhance decision-making. It enables new levels of collaboration among manufacturers of products, operators of assets, suppliers and service companies. The approach combines digital twins with manufacturing solutions from SAP, cloud networks and SAP Leonardo capabilities, including machine learning, blockchain and Internet of Things (IoT), to optimize the product lifecycle with:
• Digital representation: SAP synchronizes digital twin business data, product information, asset master data and IoT-connected data from both on-premise and cloud solutions enabling companies to represent the world digitally. Solutions including SAP Predictive Engineering Insights, SAP Predictive Maintenance and Service and the SAP 3D Visual Enterprise applications provide access to rich data processing capabilities and live configuration, state, condition and control information.
• Business process: Rich enterprise-grade data processing capabilities allow customers to create, access and update digital twins to support business processes. SAP solutions provide an integrated data model from design, production and maintenance to service, including packaged integration to existing systems for computer-aided design, ERP, and product lifecycle management. Offerings providing end-to-end process support for manufacturers and operators include SAP S/4HANA, the SAP Engineering Control Center integration tool, SAP Hybris Service Cloud solutions, and the SAP Manufacturing Integration and Intelligence and SAP Manufacturing Execution applications.
• Business networks: With leading network offerings such as SAP Ariba solutions, SAP Asset Intelligence Network, and the SAP Distributed Manufacturing application, SAP is uniquely positioned to provide a virtual platform for collaboration on products and assets. The network of digital twins enables secure data access, sharing and governance on a global scale.
• Networks of digital representation: SAP enables twin-to-twin connections in systems within a specific asset and on an asset-to-asset level. SAP solutions such as SAP Asset Intelligence Network provide semantic and industry-standards support in an asset core modeling environment to enable live enrichment during the product or asset lifecycle.
Digital Manufacturing Cloud
SAP Digital Manufacturing Cloud helps companies optimize performance, elevate production quality and efficiency, and ensure worker safety.
Drawing on SAP’s expertise in the Industrial Internet of Things (IIoT), predictive analytics and supply networks, the solution enables manufacturers to deploy Industry 4.0 technologies in the cloud.
The new cloud solution extends and complements the digital manufacturing portfolio of on-premise solutions from SAP and is available in different bundles to serve manufacturers of varying sizes in both discrete and process industries and roles within their respective organizations.
SAP customers can choose from the SAP Digital Manufacturing Cloud solution for execution, which provides all solutions in the manufacturing cloud portfolio, or the SAP Digital Manufacturing Cloud solution for insights, which focuses on performance management and predictive quality.
“Manufacturers in the era of Industry 4.0 require solutions that are intelligent, networked and predictive,” said Leukert. “Our manufacturing cloud solutions help customers take advantage of the Industrial Internet of Things by connecting equipment, people and operations across the extended digital supply chain and tightly integrating manufacturing with business operations.”
SAP Digital Manufacturing Cloud includes the following:
• SAP Digital Manufacturing Cloud for execution: Industry0-enabled shop floor solution features “lot size one” and paperless production capabilities. It integrates business systems with the shop floor, allowing for complete component and material-level visibility for single and global installations.
• SAP Digital Manufacturing Cloud for insights: Centralized, data-driven performance management enables key stakeholders to achieve best-in-class manufacturing performance and operations.
• Predictive quality: This helps manufacturers gain valuable insights to conform to specifications across processes and streamline quality management. It also allows manufacturers to apply predictive algorithms that can reduce losses from defects, deficiencies or variations, and recommend corrective actions.
• Manufacturing network: The network provides a cloud-based collaborative platform integrated with SAP Ariba solutions connecting customers with manufacturing service providers, such as suppliers of 3D and computer numerical control (CNC) printing services, material providers, original equipment manufacturers (OEM) and technical certification companies.
Also at Hannover Messe 2018, SAP announced SAP Connected Worker Safety, a solution designed to reduce risks, costs and protect employees. Information from wearables and other sensor-enabled equipment can help companies react immediately to a hazardous situation or incident while proactively managing worker fatigue and other hazard inducers. Real-time information allows monitoring of compliance at all times against regulatory and other parameters.
Amongst the cloud and manufacturing IT booths in Hannover was a sizable booth nestled in the middle housing Arm, the processor company. Here Ian Ferguson, Vice President, Ecosystem Development, met with me to discuss some of the latest embedded computing news.
Arm licenses chips which are optimized to the OS for customer companies to use and customize.
Its software business includes a device manager for small device apps for provisioning and connecting. It has also announced a bridge to IBM Watson.
Its software product, Embed, runs on ARM. Among the areas of focus is smart meters and tracking of small assets. Ferguson also mentioned smart buildings–especially lighting.
Security is a key focus working at the chip level to detect intrusions, “device health”.
• Rapid industry adoption of Mbed Platform with more than 300,000 developers (>30% growth over the past year) and 80 partners
• Arm expands integration with IBM Watson IoT, and partners with Cybertrust and GlobalSign to deliver BYOC (Bring-Your-Own-Certificate) flexible IoT security authentication
• Mbed drives IoT business value for logistics, utilities and smart cities as organizations shift to Industry 4.0
Help organizations take advantage of the opportunities offered by IoT data and combine this with their business data to create valuable business outcomes. However, in talking with these organizations, many feel that pursuing opportunities to achieve these business outcomes through IoT opens themselves up to more IT complexity and greater security concerns.
Security and complexity of integration are legitimate concerns that addressed with Arm Mbed Platform. This platform provides the necessary IoT building blocks including, connectivity, device management, security and provisioning with the support of a 300,000+ strong developer community that has grown more than 30% in the past year.
It’s also supported by a growing ecosystem of 80 contributing partners such as IBM, which is bridging the Mbed Cloud with IBM Watson IoT Platform. We’ve integrated Mbed Cloud with Cybertrust and GlobalSign to provide more flexible security authentication for IoT devices.
Mbed Cloud and Mbed Cloud On Premises were designed to provide device management, connectivity and provisioning that customers demand, supported across multiple public and private clouds, on-premises and hybrid environments.
IoT security should be easy to implement, not an inhibitor. The new integrations between Mbed Cloud and Cybertrust and GlobalSign enable customers to BYOC (Bring-Your-Own-Certificate) for flexible and secure IoT authentication, leveraging the public key infrastructure they already use. Security should also be built into development, which is why Arm is planning to make its free open-sourced development platform, Mbed OS, the first OS to support PSA-Compliant trusted boot, storage and opaque cryptography.
However, even when security is built-in, software updates are often needed to maintain a strong security posture, which is a challenge when there are millions of devices already deployed out in the field. Through an expanded integration with IBM Watson IoT Platform, its users can now manage, provision and update firmware over-the-air for their IoT devices through Mbed Cloud.
Walking through one of the Halls at the Hannover Messe, you suddenly find yourself in the Cloud—computing that is. There was Amazon Web Services, Microsoft Azure, and Google Cloud. The Manufacturing IT section just keeps growing. And getting more interesting.
One interesting aspect—I’m beginning to see articles speculating on the “end of Cloud computing.” Wonder what could come next?
Meanwhile, here is one piece of Cloud news I picked up. Amazon Web Services (AWS), an Amazon company, announced the general availability of AWS IoT Analytics, a fully-managed service that makes it easy to run simple and sophisticated analytics on massive volumes of data from IoT devices and sensors, empowering customers to uncover insights that lead to more accurate decisions for their IoT and machine learning applications.
AWS IoT Analytics collects, pre-processes, enriches, stores, and analyzes IoT device data at scale so companies can easily identify things like the average distance traveled for a fleet of connected vehicles, or how many doors are locked after work hours in a smart building, or assess the performance of devices over time to predict maintenance issues and better react to changing environmental conditions. With AWS IoT Analytics, customers don’t have to worry about all the cost and complexity typically required to build their own IoT analytics platform. AWS IoT Analytics is available today in the US East-1 (N. Virginia), US East-2 (Ohio), US West (Oregon), and EU (Ireland) regions, with support for additional regions coming soon.
“AWS IoT Analytics is the easiest way to run analytics on IoT data. Now, customers can act on the large volumes of IoT data generated by their connected devices with powerful analytics capabilities ranging from simple queries to sophisticated machine learning models that are specifically designed for IoT,” said Dirk Didascalou, VP, IoT, AWS. “As the scale of IoT applications continues to grow at a rapid rate, AWS IoT Analytics is designed to provide the best tools for our customers to mine their raw data, gaining insights that lead to intelligent actions.”
AWS IoT Analytics also has features like a built-in SQL query engine to answer specific business questions and more sophisticated analytics, enabling customers to understand the performance of devices, predict device failure, and perform time-series analysis. Also, AWS IoT Analytics offers access to machine learning tools with hosted Jupyter Notebooks through seamless integration with Amazon SageMaker. Customers can directly connect their IoT data to a Jupyter Notebook and build, train, and execute models at any scale right from the AWS IoT Analytics console without having to manage any of the underlying infrastructure.
Using AWS IoT Analytics, customers can apply machine learning algorithms to device data to produce a health score for each device in a fleet, prevent fraud and cyber intrusion by detecting anomalies on IoT devices, predict device failures, segment fleets of devices, and identify other rare events that may have great significance but are hard to find without analytics. And, by using Amazon QuickSight, a fast, cloud-powered business analytics service, in conjunction with AWS IoT Analytics, it is easy for customers to surface insights in easy-to-build visualizations and dashboards.
AWS IoT Analytics can accept data from any source, including external sources using an ingestion API, and integrates fully with AWS IoT Core. Launched in 2015, AWS IoT Core is a managed cloud platform that lets connected devices easily and securely interact with cloud applications and other devices. AWS IoT Analytics also stores the data for analysis, while providing customers the ability to set data retention policies.
Modjoul, Georgia Pacific, Teralytic, Siemens, OSIsoft, Pentair, 47Lining, Domo, NetFoundry, and Laird Technologies are just a few of the customers and Amazon Partner Network members using AWS IoT Analytics to uncover valuable insights within their data and use those findings to innovate across their specialized businesses.
Modjoul is a data invention company for wearable technology that is focused on keeping employees safe. “Our mission is to keep industrial workers safe, whether they’re working in or out of a vehicle,” said Eric Martinez, CEO and Founder, Modjoul. “In an eight-hour shift, we collect data 28,800 times per day from our connected activity tracker worn by each of our employees that includes 40 metrics including heart rate and activity level. With AWS IoT Analytics, we not only analyze all that health data, but also enrich it with location and environmental data, such as outdoor temperature, to get accurate analytics that prevent injuries and save lives. Today, we’re operating better and faster.”
Georgia Pacific is one of the world’s leading makers of tissue, pulp, paper, packaging, building products, and related chemicals. “At Georgia Pacific, our industry-leading dispensers allow us to deliver solutions to customers, not just sell products,” said Erik Cordsen, IoT Program Architect and Product Leader, Georgia-Pacific. “Now we are focused on making our dispensers ‘smart’ by adding sensors and connectivity that allow us to improve customer experience by providing real-time information about product levels and other statistics. With thousands of endpoints continuously feeding in data, we are using AWS IoT Analytics to enrich messages with location and product metadata in order to calculate platform health and value to our customers. AWS lets my team focus on solving the business problem instead of wrestling with technology.”
Teralytic is a soil health company focused on improving farmer’s yield by monitoring and improving the condition of their soils. “We have a network of soil-sensing IoT devices embedded in the soil from which data are collected, fed, and analyzed for us to understand the health of our customers’ agricultural ecosystems,” said Dan Casson, Vice President of Engineering, Teralytic. “We chose AWS IoT Analytics for its ability to filter outlier readings from our calculations and proactively detect issues as they arise so we can resolve them faster. In some cases, we’re able to identify and prevent issues before they occur. With AWS IoT Analytics, we use Machine Learning models to help detect situations where nutrients in the soil are at risk of leeching into ground water or runoff into surface water so the farmer can adjust the watering schedule, if needed. In addition to the environmental benefits, these machine learning models can help reduce a farmer’s costs as well as potentially increasing their yield.”
47Lining develops big data solutions and delivers big data managed services — built from underlying AWS building blocks like Amazon Redshift, Kinesis, Amazon Simple Storage Service (Amazon S3), and Amazon DynamoDB — to help customers manage their data across a variety of verticals including energy, life sciences, gaming, and financial services. “Because AWS IoT Analytics is designed around time-series data, it’s a great fit for our customers in industrial, energy, and oil & gas, who seek real-time decision support and process optimization,” said Mick Bass, Senior Vice President, Big Data Practice, 47Lining.
Domo is a computer software company that specializes in business intelligence tools and data visualization. “Since our inception in 2010, AWS has been a trusted service provider that keeps up with the demands of our dynamic business,” said Jay Heglar, Chief Strategy Officer, Domo. “We extended our relationship with AWS to IoT Analytics because we wanted a flexible option to enable faster access to machine-generated data for our customers. Through our proprietary connector to AWS IoT Analytics, we are ensuring our customers have access to one of the most innovative solutions, allowing them to leverage machine-generated data at scale.”
Laird Technologies designs, develops, manufactures, and supports wireless systems solutions and performance materials for wireless and other advanced electronics applications. “By combining our long range wireless sensor and gateway products with AWS IoT, our customers have been able to quickly and securely get data from their devices into the cloud,” said Paul Elvikis, Business Development Director for Industrial, Laird Technologies. “Unfortunately, they would often get overwhelmed with the amount of sensor data that would start coming in. Customers would struggle to figure out how to do anything with it. AWS IoT Analytics has been a great help in extending our capabilities to solve that issue for our customers.”
NetFoundry gives its customers and their applications control of their networks without any telco, hardware, or private circuit constraints. “The capabilities of AWS IoT Analytics in enabling the transformation of vast amounts of data into actionable information, without the high costs and steep learning curve of other IoT platforms, enables NetFoundry’s IoT customers to get the ROI they need,” said Michael Kochanik, Co-founder and Global Head of Channel Revenue, NetFoundry.“With AWS IoT Analytics, we can integrate IoT networking capabilities to provide our IoT customers with ‘one-stop shopping’ including data collection, networking, analysis, transformations, storage and visualization. Partnering with AWS enables our customers to get integrated, end-to-end agility, security, performance and cost efficiency at scale.”
AWS offers over 125 fully featured services for compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT), mobile, security, hybrid, virtual and augmented reality (VR and AR), media, and application development, deployment, and management from 54 Availability Zones (AZs) within 18 geographic regions and one Local Region around the world, spanning the U.S., Australia, Brazil, Canada, China, France, Germany, India, Ireland, Japan, Korea, Singapore, and the UK.
Hannover Messe continues to reflect the trend of companies joining alliances to develop and promote standards and interoperability. While I did not have an interview with the Avnu Alliance while I was in Hannover, I talked with some members and obtained other information. Avnu Alliance promotes adoption of the Time Sensitive Networking (TSN) extension to Ethernet.
Specifically, Avnu Alliance is a community creating an interoperable ecosystem of low-latency, time-synchronized, highly reliable networked devices using open standards. Avnu creates comprehensive certification programs to ensure interoperability of networked devices. The foundational technology enables deterministic synchronized networking based on IEEE Audio Video Bridging (AVB) / Time Sensitive Networking (TSN) base standards. The Alliance, in conjunction with other complimentary standards bodies and alliances, provides a united network foundation for use in professional AV, automotive, industrial control and consumer segments.
The adoption pace of TSN from 2017 to 2018 was amazing.
I always drop by the Industrial Internet Consortium (IIC) area at Hannover and check out the TSN Testbed for Flexible Manufacturing. The testbed was developed with two major goals – to show TSN’s readiness to accelerate the marketplace; and to show the business value of TSN in converged, deterministic IIoT networks. Momentum is increasing for the testbed, with the IIC hosting its 10th plugfest in an 18-month timeframe at the Bosch Rexroth facility in Frankfurt, Germany and its 9th plugfest, which was held in Austin, TX in February at National Instruments (NI) headquarters following a joint workshop on interoperability with Avnu Alliance. The TSN Testbed recently integrated test tools from Avnu Alliance members, Calnex, Ixia and Spirent into plugfest activities, and demonstrated interoperability of TSN devices from more than 25 companies performing real-time automation and control automation functions over TSN.
Any Avnu Alliance member is welcome to join the IIC TSN Testbed or to participate in a plugfest. Upcoming plugfests will be held in Austin, TX from June 26-29, 2018 and in Stuttgart from July 24-27, 2018.
The Edge Computing Consortium (ECC) along with members and Avnu Alliance, hosted a press conference to announce new developments surrounding the newly created OPC UA TSN testbed. The testbed demonstrates six major IIoT scenarios mimicking processes found in smart manufacturing settings and utilizing products across different TSN vendors. Avnu Alliance is a key partner supporting the development of the testbed with the ECC in the shared goal of enabling manufacturers to test their products for interoperability and conduct trials of real-world systems as an early check for problems.
Tom Weingartner, Avnu Alliance member and Analog Devices’ marketing director for Deterministic Ethernet Technology Group, represented the Alliance at an announcement ceremony.
Paul Didier, Avnu Alliance member and IoT solutions architect, Cisco delivered a talk at the Industrie 4.0 meet the Industrial Internet Forum, in a presentation titled “Time Sensitive Networks – Where does the technology stand and what to expect”. He will provide an update on TSN and how manufacturers, alliances and liaison groups are working together to advance the technology and its implementation in the IIoT.
Paul will present an additional lecture for the Forum on “Modernizing Your Industrial Manufacturing Network”. The presentation will follow the findings coming out of the IIC TSN Testbed and its capabilities, including information on how manufacturing automation and control infrastructure vendors and key decision-makers can leverage TSN for a variety of operational benefits, including increased connectivity between devices and the ability to extract and analyze valuable information through interconnectivity.
“HANNOVER continues to be a key industry event for both Avnu Alliance members and liaison groups that we work with to educate and increase awareness of TSN as a solution for the growing IIoT,” said Todd Walter, Avnu Alliance Industrial Segment Leader and Chief Marketing Manager at NI. “Whether through the developments coming from the TSN testbeds, speaking engagements or product demonstrations, our members and partners are committed to creating an interoperable TSN network that gives all industrial devices a more streamlined path to participating in the TSN ecosystem.
A small group of companies proposed a marketing initiative promoting OPC UA over a new Ethernet standard called Time Sensitive Networking (TSN) in 2017 at Hannover Messe. I was privileged to sit in a meeting to listen to the proposal and subsequently wrote a white paper about it. I believe this is revolutionary technology for the information part of manufacturing technology.
Meanwhile, Rockwell Automation is beginning to regularly surprise me. They first went out of their twice to talk about truly adopting OPC UA and introduced a module for its control platform using it. The company has a long standing reputation for getting involved in standards it doesn’t directly control for the purpose of delaying adoption. But this seemed like a genuine adoption of interoperability recognizing that customers are demanding freely flowing information from a variety of sources.Just to add to my surprise was an announcement I heard about at Hannover that Rockwell Automation has joined that group of OPC UA over TSN companies, now dubbed the “Shapers”. This group is rapidly moving toward critical mass with rumors swirling about companies not (yet) a part of it.
The press release (I haven’t yet had an interview) states Rockwell Automation is joining industry leaders ABB, Belden, Bosch Rexroth, B&R, Cisco, Hilscher, KUKA, National Instruments, Parker Hannifin, Phoenix Contact, Pilz, Schneider Electric, TTTech and WAGO (collectively known as Shapers) to create a communication solution for real-time and sensor-to-cloud applications in industrial operations.
The solution will be based on the OPC UA protocol, which allows easy and secure sharing of information across different vendor technologies and the time-sensitive networking (TSN) suite of standards, which helps improve latency and robustness in converged industrial networks.
“Connecting technologies across an industrial organization while maintaining multivendor interoperability requires a harmonized, interoperable solution that uses consistent information models, communication and application behavior (together known as application profiles),” said Paul Brooks, business development manager, Rockwell Automation.
“That’s what this group of automation leaders are combining their expertise to create. Our solution will give manufacturing and industrial organizations best-of-breed I/O device control, motion and safety application profiles,” said Sebastian Sachse, B&R Industrial Automation.
To ensure the emerging OPC UA TSN solution supports interoperability of different vendor technologies on the same network, the companies are engaging with industry consortia such as Avnu, IEEE, IIC, LNI 4.0 and OPC Foundation. The companies are also planning an announcement in the coming months on how to achieve unified application profiles, which is the last hurdle to device harmonization. They aim to provide one-stop-shop certification of the overall solution up to the device-profile level.
The companies have already published whitepapers on OPC UA TSN technology, such as an IIC whitepaper on converged traffic types. They have also made significant contributions to the recently released PubSub extension of OPC UA, and plan to set up a collaboration between the IIC and LNI testbeds.
This potentially holds great promise for end user companies and systems integrators. We can only hope it progresses.