As complex systems evolve, some of the previous strategies used to modify them, maintain them, enhance them, and train users to operate them, have needed to change too. It is simply no longer practical to perform developmental or change work on the main live systems. Changes and updates can place the main platform at great risk and incur unexpected downtime. Likewise, conducting training on the live systems might be foolhardy at best.
Now, along with the digitization of work, and the tremendous growth for the Internet of Things (IoT), there is a strategy to create a replica or to mimic the core systems within a digital software defined system. The duplicate platforms are designed to be a sandbox to play, change, and innovate the main platform, albeit without the inherent risks of working on the actual live systems. We can use the software based mimic platform to experiment and test; we can try out ideas and fail. Evolving critical systems is complex and difficult work, so playing around on a live platform is simply too risky. The concept is to create a shadow system to replicate the main system; it is commonly referred to as a “digital twin”.
Most systems today, are real-time. They tend to be loaded with IoT sensors, actuators, microcomputers, and edge processing, storage, and analytics. The data generated by this IoT model can be fed into the digital twin as well as be utilized by the core systems. But, in the digital twin, we get to try “what-if” scenarios. We get to play, experiment, and most importantly fail without the negative ramifications that would be realized on the live system. The sandbox strategy has been around for a long time. Twenty years ago, when I built a Direct-to-Home satellite teleport for example, there was a sandbox for the encryption systems to permit the hardening and testing of next generation security before it was placed into service on the core teleport uplink transmission systems. This “mini me” model was fantastic as it defused the risk inherent in the process of deploying complex security that could instantly and adversely impact millions of paying customers. These customers had zero tolerance for service downtime. The cost of downtime for the teleport operator was expensive.
Digital shadow systems and digital twins have been seen in manufacturing for the past few years, but now they are becoming mainstream and moving beyond the factory floor. They are a fundamental concept in the Industry 4.0 movement in factories. The best digital twin systems learn from historical data, they can adapt to working conditions, workflows, production levels, quality standards, and workers.
Now beyond the factory floor, we are seeing digital twin systems being used with power generation plants, wind turbines, HVAC control systems, offshore drilling rigs, jet engines, and railroad locomotives.
Once I saw a fully operational digital twin solution for military tanks. They were used to explore upgrades and enhancements to the weapon systems, train new operators to drive the tank and fire the guns. All done in simulation in a software defined environment that precisely duplicated the same feel and control of a physical tank in the field.
Pilots have used lifelike simulators for decades. Today, these simulators are so realistic, that a pilot can earn certification and accreditation in the simulator first, before ever stepping into the actual aircraft. Having once tried to land a Boeing 737 airplane in a simulator and with little prior knowledge and experience, I can assure you that it feels real. My dress shirt was soaked with sweat from being in the sim. Even the latest high tech virtual reality (VR) graphic systems have nothing on these commercial flight simulators. My heart was racing, my body was reacting, and my mind was convinced that it was real, even when I knew full well that I was comfortably sitting in a bolted down, three-axes flight simulator. It was real to me. I was even starting to feel a wee bit air sick.
Digital twins have only recently come to the centre stage with the advent of cloud computing and cognitive computing. These two innovations permitted the digital twin concept to grow and flourish rapidly and the expand to a myriad of new use case scenarios previously not possible.
IBM’s Chris O’Connor describes the digital twin concept this way. Digital twin is a virtual/digital representation of a physical entity or system. It involves connected “things” generating real-time data. That data is analyzed in the cloud, and combined with other data related to the thing / context around it. It is then presented to people in a variety of roles, so they can remotely understand its status, its history, its needs, and interact with it to do their jobs. It’s a marriage of physical and digital worlds in a way that gives people a new level of visibility into the things that matter to them or their business.
The real magic happens when people across the organization have the exact digital twin view they need of a product at every stage in its life cycle. This has never been possible before because each stakeholder group has its own set of data and applications, and they don’t talk to each other. What’s possible now: with a single, powerful interface to the Digital Twin, multiple views can be created for different stakeholders, using the same underlying data streams but with visualizations and supplemental data sources tailored to the needs of each particular user. This capability is known as digital thread.
IBM’s author Lynn Slowey wrote, in Airbus, we have a tremendous challenge to design industry leading, state of the art aircraft. It’s a very competitive, and a key challenge is to make engineering more efficient. Missing delivery deadlines for orders can not only cost millions of dollars, but can permanently damage brand reputation.
Digital twin means that engineers can be sure they are using the right data, data that is appropriate for their point of view. Think about an aircraft wing. There are several engineering disciplines involved with designing a wing, all of which need to collaborate. The wing has a structural component, an aerodynamic component, and an aero-elastic component. All of these engineers need to work together, and need a digital twin that supports their particular objectives.
The Airbus vision of a digital twin isn’t limited to just wings as explained by Axel Mauritz of Airbus: “If a problem is discovered with a plane, we need the digital thread that links throughout the product lifecycle so we can explore whether the problem is due to improper service, a poor manufacturing process, or a design flaw. Our engineers need to understand how the plane will be built and operated so that they can design it properly.”
So, is a digital twin solution a part of your future development systems? Yes, very likely as the economics are compelling. With the need to speed to market and get it right out of the gate, the digital twin is a solution to seemingly integrate with other engineering strategies such as agile, iterative, and just-in-time design. If you work with complex systems that cannot tolerate downtime, than consider the digital twin approach.
About the Author:
Michael Martin has more than 35 years of experience in broadband networks, optical fibre, wireless and digital communications technologies. He is a Senior Executive with IBM Canada’s GTS Network Services Group. Over the past 12 years with IBM, he has worked in the GBS Global Center of Competency for Energy and Utilities and the GTS Global Center of Excellence for Energy and Utilities. He was previously a founding partner and President of MICAN Communications and before that was President of Comlink Systems Limited and Ensat Broadcast Services, Inc., both divisions of Cygnal Technologies Corporation (CYN:TSX). Martin currently serves on the Board of Directors for TeraGo Inc (TGO:TSX) and previously served on the Board of Directors for Avante Logixx Inc. (XX:TSX.V). He served on the Board of Governors of the University of Ontario Institute of Technology (UOIT) and on the Board of Advisers of five different Colleges in Ontario as well as for 16 years on the Board of the Society of Motion Picture and Television Engineers (SMPTE), Toronto Section. He holds three Masters degrees, in business (MBA), communication (MA), and education (MEd). As well, he has diplomas and certifications in business, computer programming, internetworking, project management, media, photography, and communication technology.
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