Industry IoT Consortium Publishes the Digital Twin Core Conceptual Models and Services Technical Report

Digital Twins form the core technology to Industry 4.0, Industrial Metaverse, and Digital Transformation. (Did I hit all the hype hot buttons there?) All joking aside, digital twins—making digital designs available across platforms—are important. The Industry IoT Consortium (IIC) has published this month the Digital Twin Core Conceptual Models and Services Technical Report.

The report guides technical decision-makers, system engineers, software architects, and modelers about connecting the foundational IT infrastructure with industry-specific business applications powered by digital twins in industrial settings.

The report describes digital twin fundamental concepts and basic requirements, core conceptual models and services, enabling architectures and technologies, and supported business applications. It provides high-level technical considerations in implementing the digital twin core layer, aligned to the Virtual Representation section of the Digital Twin Consortium (DTC) Platform Stack Architectural Framework: An Introductory Guide. The IIC report also includes a survey of relevant standards and can be used as input for standards development for digital twins.

The Industry IoT Consortium is a program of the Object Management Group (OMG). 

Honeywell Connect 2023

Honeywell Connect 2023, the user conference of Honeywell Connected Enterprise the software business unit of Honeywell, was held in Dallas this year October 10-12. I had been waiting for some documents from Honeywell and got busy. I’ve written several news stories from Honeywell Connect over the past six months. This Strategic Business Unit of Honeywell has been quite busy.

This event was sort of a 5th anniversary celebration. I’m a slow learner and it took some time before it sunk into my consciousness just what was up with Honeywell Connected Enterprise and Honeywell Forge. Honeywell corporately has five strategic business units. Four are vertical business. Honeywell Connected Enterprise is the software arm that cuts across all the other SBUs plus reaches out in its own right.

CEO Kevin Dehoff referred to Forge as the “premier Industrial IoT Architecture.” At a time when other companies who had touted IIoT were moving to other marketing slogans, HCE proudly discusses IIoT as the connected of the Connected Enterprise. I think they are continuing on the correct track. After all, I named my new website 10 years ago as The Manufacturing Connection because I saw that connecting things (and processes and people and businesses) was where we as an industry needed to go.

Discussion centered on outcomes. I also like that approach. Too many product companies focus on features. Customers are interested in outcomes. 

Everything connected becomes a hacking risk. HCE acquired SCADAfence a few months ago to strengthen an already rich cyber security portfolio. Shortly after the acquisition, the company announced CyberWatch and CyberInsights. Expect to see growing robustness from the cybersecurity portfolio.

No software event can be complete without bowing to Digital Transformation. “Digital Transformation isn’t an event—it’s an ongoing journey.” HCE talks of technology augmenting humans. Another topic here is the potential use of AI as an enabler of autonomous control—another sub theme of the conference.

Some ideas in this vein include AI co-pilots, cyber forensics and recovery, closed loop sustainability.

Digital Transformation as the sum of process, people, technology, and data.

Sustainability continues to be a strong theme. Companies are continuing the trend from manual to automated data collection. Carbon and demand management continue as an important trend. HCE continues to see opportunities with instrumentation for monitoring emissions, as well as, applying process control technologies to mitigate those.

One final thought. The last session I saw was with Vimal Kapur, Honeywell CEO. HCE has been developed to solve customers’ big problems. Doing so, Honeywell is building the largest industrial software company. “Maybe we already have.”

This is interesting because earlier this year I was at the Siemens Digital event where executives extolled the division as the market’s leading industrial software company. The week following AVEVA held its annual conference—a continuation of the OSIsoft PI user conference. Meanwhile, Emerson has been aggressively promoting itself as a software company. Yet, Rockwell Automation had been touting its software for a few years, but it has become the “digital transformation” company for the past year or more.

Where will software take all these companies? Is this where growth lies? Instrumentation and control are stable, but mature markets? I wonder.

MongoDB Launches Atlas for Manufacturing and Automotive

Is your knowledge or experience limited to your historian or perhaps also an SQL database? It’s worth your time following the variety of database products that may help you in your manufacturing digital transformation. This release is from MongoDB. I am retaining all the “about” paragraphs below the news in case you are not sure who this is and may want additional information.

The news in brief:

  • New MongoDB Atlas for Manufacturing and Automotive initiative helps organizations deploy applications that use real-time data to optimize processes and reimagine end-user experiences with connected technologies
  • AWS, HiveMQ, Share Now and Digitread Connect among partners and customers working with MongoDB in the automotive and manufacturing industries

MongoDB on Sept. 21, 2023 at MongoDB.local Frankfurt, announced MongoDB Atlas for Manufacturing and Automotive, a new initiative that helps organizations innovate with real-time data and build applications that take advantage of intelligent, connected technology. 

MongoDB Atlas for Manufacturing and Automotive includes expert-led innovation workshops, tailored technology partnerships, and industry-specific knowledge accelerators to provide customized training paths designed for the wide range of use cases that developers in these industries work with—from digital twins of manufacturing facilities to predictive maintenance of factory equipment to highly engaging applications for connected cars.

To be effective, organizations need the ability to collect, process, and analyze high-volume data from different sources in real time—a process that is extremely challenging. For example, the data that IoT devices and sensors generate comes in many different formats and must be normalized, combined, and processed before advanced analytics can begin. Even then, many organizations often lack the expertise required to build applications that can analyze real-time data for use cases like identifying potential defects in vehicle fleets for safety improvement or detecting anomalies in factory machinery to prevent equipment failure. Because of the many challenges involved with collecting, processing, and analyzing vast amounts of real-time data, many organizations in the automotive and manufacturing industries are unable to build and deploy modern applications that take advantage of connected technologies to transform their businesses.

“The automotive and manufacturing industries are embracing a foundational transformation from manual assembly-line type operations to intelligent organizations based on software and automation. New vehicle drivetrains and complementary technologies provide access to vast amounts of data that is not only available in real-time but needs to be processed in real-time as well,” said Boris Bialek, Field CTO of Industry Solutions at MongoDB. “This industry-wide transformation is in its early stages, and many companies are just starting to figure out what they need to effectively collect, process, and analyze all of this data so they can make better business decisions and enhance end-user experiences. MongoDB Atlas for Manufacturing and Automotive accelerates this transformation by providing a set of expert-led industry initiatives to help organizations quickly go from ‘overwhelmed by data’ to ‘deriving valuable insights from data’ with modern applications.”

  • MongoDB Atlas for Manufacturing and Automotive includes dedicated executive engagement with industry experts from MongoDB and the MongoDB Partner Ecosystem to ideate client-specific solutions using best practices. Innovation workshops are tailored to address the unique challenges and opportunities organizations in the automotive and manufacturing industries face so they can develop data-first application strategies.
  • MongoDB Atlas for Manufacturing and Automotive provides access to MongoDB’s industry-specific partner integrations and toolchains to help accelerate application development. The MongoDB Partner Ecosystem includes systems integrators and technology consultants with industry-specific expertise—including AWS and HiveMQ—to help organizations adopt the right solutions for their specific use cases. MongoDB also works closely with industry-specific technology alliances like COVESA that provide open solutions for automotive industry challenges.
  • Organizations can engage with the MongoDB Professional Services team to take advantage of automotive and manufacturing industry expertise to accelerate projects from concept to prototype to production in less time.
  • MongoDB Atlas for Manufacturing and Automotive provides tailored MongoDB University courses and learning materials, including unlimited access to curated webinars and solutions sessions, to help developers learn how to quickly build modern applications for the automotive and manufacturing industries.

Partner program on AWS

  • HiveMQ makes it possible to move data from device to cloud in a secure, reliable and scalable manner. “The HiveMQ MQTT Platform makes it easy for companies to stream IoT data from devices to the cloud to ensure they are maximizing value,” said Dominik Obermaier, Cofounder and CTO at HiveMQ. “Adding a pre-built integration with MongoDB allows our customers to eliminate the need for manual integration and harness the power of MongoDB for data management and real-time, application-driven analytics.”
  • Share Now is a car-sharing joint venture between car2go and DriveNow with over 10,000 vehicles in 16 cities across eight countries. “We needed new versatile, automated database environments that could handle all of our microservices and database clusters without breaking a sweat. This would help us efficiently and accurately process incoming data,” said Stephan Kaufmann, Head of Cloud Engineering, SHARE NOW. “Deploying MongoDB Atlas was a seamless and pain-free project for us. MongoDB Atlas helps us innovate through integrating our data sets and back-end management while delivering better ROI than any other solution on the market.”
  • Digitread Connect provides KYB, an Industrial IoT platform that helps track performance of machinery and industrial assets through sensors: “Time-series data is our bread and butter, and MongoDB made it simple for us to handle this,” said Christoffer Lange, CEO, Digitread Connect. “We were amazed by the simplicity and the performance. Using MongoDB Atlas really showed us that we don’t have to worry about the nitty-gritty details of how to treat the database. We got the solution live for our customers in a very short time.”

About MongoDB Atlas for Industries

MongoDB for Automotive and Manufacturing is part of MongoDB Atlas for Industries, a program that helps organizations accelerate cloud adoption and modernization by leveraging industry-specific expertise, programs, partnerships, and integrated solutions. 

About MongoDB Atlas Developer Data Platform

MongoDB Atlas is the leading multi-cloud developer data platform that accelerates and simplifies building applications with data. MongoDB Atlas provides an integrated set of data and application services in a unified environment that enables development teams to quickly build with the performance and scale modern applications require. Tens of thousands of customers and millions of developers worldwide rely on MongoDB Atlas every day to power their business-critical applications. 

About MongoDB

Headquartered in New York, MongoDB’s mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. Built by developers, for developers, our developer data platform is a database with an integrated set of related services that allow development teams to address the growing requirements for today’s wide variety of modern applications, all in a unified and consistent user experience. MongoDB has tens of thousands of customers in over 100 countries. The MongoDB database platform has been downloaded hundreds of millions of times since 2007, and there have been millions of builders trained through MongoDB University courses.

Belden Acquires CloudRail To Enhance IIoT Presence

Some years ago Belden was searching for a greater IoT presence in a manner I felt was not strategically aligned. This acquisition makes sense even given the rather garbled marketing justifications in the news release. Although a few companies are investigating other means than Cloud, certainly having a presence in the Cloud is essential for many applications. Belden announces here the acquisition of German-based Industrial IoT (IIoT) specialist CloudRail.

With the acquisition of CloudRail, Belden continues its strategy to deliver the infrastructure that makes the digital journey simpler, more smart and secure. Belden is moving beyond connectivity – from what we make to what we make possible through a performance-driven portfolio, forward-thinking expertise and purpose-built solutions with a leadership position in the evolving IIoT sector.

I found that paragraph a little confusing. They really meant what they said here.

While Belden already had a strong portfolio of products in the areas of data acquisition, edge computing, and security, the industrial automation market also encounters a clear shift from on-premise systems to the cloud.

“CloudRail literally connects the factory to the Cloud. The founders of the company recognized this trend early and gained a unique leadership position. CloudRail complements our solution portfolio by adding sensor data ingestion capabilities to our Belden HORIZON DataOperations Platform and it fully supports the Belden Industrial EDGE strategy”, says Brian Lieser, Executive Vice President at Belden. 

CloudRail offers solutions for industrial customers to connect assets to cloud platforms like AWS or Microsoft Azure.

Three Tips from Moxa on Getting IIoT Networks Ready for the Future

If you’ve been around automation for the past 20 years, you’ve no doubt experienced how the job changed from isolated control connected to I/O to one or more field buses to one or more variety of Ethernet. We’ve now experienced the Internet of Things explosion (at least in hype). That latter is mostly Ethernet-based using IP (Internet Protocol). 

If you’ve not been careful, you could be working with a mess of networks right now. I received this document of networking tips from networking infrastructure supplier Moxa. I thought it useful to pass along.

Tip One: Achieve Greater Integration with Unified Infrastructure

Over the years, various devices using different protocols have been deployed on industrial networks to provide diverse services. Under these circumstances, network integration usually costs more than expected or becomes more difficult to achieve. Manufacturers can either choose the status quo, that is, maintain their pre-existing isolated automation networks with numerous purpose-built protocols of the past, or seek solutions to deterministic services and that can integrate these “islands of automation” into one unified network.

If the goal is to be ready for future demands, the choice is obviously the latter. The rule of thumb is to take potential industrial protocols into consideration and ensure you can redesign networks in case any new demands arise in the market. One approach is Time-Sensitive Networking (TSN), a set of new standards introduced by the IEEE 802.1 TSN Task Group as an advanced toolbox. With TSN, you can build open, unified networks with standard Ethernet technologies that reserve flexibility for the future.

Tip Two: Enable Anywhere Access with Hassle-free Cloud Services

Cloud-based remote access offers many benefits to IIoT customers, such as reducing the travel time and expenses of sending maintenance engineers to multiple remote sites. Furthermore, cloud-based secure remote access can offer flexible and scalable connections to meet dynamic, fast-changing requirements. However, operational technology (OT) engineers may find it cumbersome to set up and maintain their own cloud servers for new services and applications. Indeed, there is considerable effort associated with setting up new infrastructure, even in the cloud. Fortunately, OEMs and machine builders can now deliver secure cloud-based services and remote access to their customers, therefore eliminating the need to maintain in-house cloud servers.

One key issue that definitely demands scrutiny is the cloud server license scheme. Often, upfront costs may seem low for limited server hosts. Yet these apparent cost savings on server hosts may actually make a project uneconomical due to a limited scale of connections. Second, you may also need to consider central management capabilities in order to flexibly expand remote connections as your needs change. With this said, carefully weigh the costs and benefits of incorporating secure remote access to industrial networks. Always select solutions that minimize hassles and will help deliver more value to customers.

Tip Three: Use Management Software for Better Visibility of Network Status

When complexity increases due to greater connectivity on industrial networks, it can become very difficult to identify the root cause of problems and maintain sufficient network visibility. Control engineers often have to revert to trial and error to get the system back to normal, which is time-consuming and troublesome.

In order to facilitate and manage growing industrial networks, network operators need integrated network management software to make informed decisions throughout network deployment, maintenance, and diagnostics. In addition, as systems continue to grow, it is important that you pay attention to a number of network integration concerns. First, only managing industrial networks in local control centers may not be feasible three or five years from now, especially when existing systems need to be integrated with new ones. It is therefore important to use network management software with integration interfaces, such as OPC DA tags for SCADA system integration or RESTful APIs for external web services. Furthermore, an interface to facilitate third-party software integration is also a key criterion for ensuring future flexibility.

OPC, MQTT, IoT, Edge, Power Future Manufacturing Technology

There was a time when I would take information from OPC Foundation and chat with the MQTT people and then return the favor. It was much like being in the midst of a religious war.

My response was (is) that the market will decide. Individual engineers will choose the solution that best fits their needs at the time. If both technologies have sufficient benefit to enough engineers to form a market, then both will survive. I think there is room in the market for both, since they sort of do the same thing, but actually each provides unique benefits.

I’ve been thinking about this for a while since I’ve had so many other things to digest. The impetus came from a couple of directions—OPC Foundation President Stefan Hoppe’s editorial in the June newsletter and from Stacey Higginbotham’s IoT Newsletter recently that discussed edge.

Hoppe wrote, “Still to this day people only think of OPC UA merely as a secure protocol to move information. It is so much more than that. It is a modeling language in cloud applications and digital twins. It is capable of file transport (since 2009). Most people know that OPC UA started as an initiative in the OT world and expanded from the PLC control plane to SCADA and later to MES and ERP. More and more people are realizing that OPC UA via MQTT is the bridge between OT and IT and is able to push information directly into Microsoft and AWS cloud dashboards without the need for an adapter.”

From Data to Data Sources

Stacey Higginbotham writing in Stacey on IoT Bringing AI to the farthest edge requires new computing.

Stacey writes about IoT generally. Most of her topics are commercial/consumer and chips (her reporting background). She does follow the IoT trail into manufacturing at times. In this newsletter she broaches into something I’ve been expounding for a long time, that is, how edge devices have become smarter with better communications. Then the IT world came up with the term Edge, which is, of course everything manufacturing.

We’re in the midst of a computing shift that’s turning the back-and-forth between cloud and edge computing on its head. This new form of computing has been creeping to the forefront for the last few years, driven by digital transformations and complicated connected devices such as cars.

But the more recent hype around AI is providing the richest examples of this shift. And it will ultimately require new forms of computing in more places, changing both how we think about the edge and the types of computing we do there. In short, the rise of AI everywhere will lead to new forms of computing specialized for different aspects of the edge. I’m calling this concept the complex edge.

As part of this shift in computing, we have to become more nuanced about what we mean when we talk about the edge. I like to think of it as a continuum moving from the most compute and power-constrained devices such as sensors to the most powerful servers that happen to be located on premise in a factory. In the middle are devices such as tablets, smartphones, programmable logic controllers (PLCs), and gateways that might handle incoming data from PLCs or sensors.

Moreover, each of these devices along the continuum might run their own AI models and require their own specialized type of computing to compare the data coming into those models. For example, I’ve written about the need for sensors to get smarter and process more information directly.

Smart sensors turn to analog compute

Cameras or image sensors are popular examples of such devices. This vision sensor from Useful Sensors, which can do person detection on a $10 device, runs a simple algorithm that looks for people and counts them. At a higher level, which requires more processing power, sensors from Sony or chips from CEVA are able to detect specific movements, faces, or other options.

A few weeks ago at the Sensors Converge event, a company called Polyn Technology showed off a version of a chip designed to take raw data and quickly convert it into an insight. To quickly process analog signals from the environment (such as vibrations or sound), the Polyn chip uses analog processing to process the signal and then sends the “insight” to another computer for more processing.

We not only have cameras shooting pictures for QA purposes, but also they are streaming video for applications from industrial engineering to surveillance to predictive maintenance. This is a vast amount of data. 

We have tools, but we will need more. Chips with built in communication and analytics are a start.

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