Digital Twins: What They Are and Why Every IT Leader Should Know About Them

Apr 26th 2017 | Posted by Domenic Colasante

As IoT, digital modelling, and data analytics become increasingly powerful, more companies are using digital twin technology to improve the efficiency, reliability, and functionality of processes and systems. The technology is becoming one of the most popular new trends of 2017, named one of Gartner’s top 10 strategic technologies of the new year. Used for prediction, quality analysis, design, and maintenance, these solutions have had a major impact on the way companies do business. The solutions are so effective, even organizations like NASA are using it to design, build, and test mission critical equipment for spaceflight. By allowing them to work on expensive equipment in a digital environment, digital twins help to cut costs and improve reliability and safety. But what are digital twins, and how can you use them to make the business more effective?

What is a digital twin?

A digital twin is a digital representation of a physical process, system, or service. The term was coined by GE to describe a new line of products; however, the category has grown to include a wide range of digital blueprint technologies. By using IoT sensors, physics data, and advanced modeling, it is possible to analyze a physical object digitally, predict potential problems, find ways to improve efficiency, and test how it will respond to changing real-world conditions. They represent the next evolution in modeling, allowing technicians, process managers, and other skilled professionals to work on systems, even when they aren’t physically present.

How can I use them to drive business goals?

Digital twin technology represents a major leap from traditional monitoring, modelling, and analytics capabilities. The ability to fully model a physical thing digitally can have many implications for the real world, allowing organizations to design better solutions, operate more efficiently, and work collaboratively.

Improved collaboration - In the past, each group would have its own data set and lack the ability to coordinate on problems effectively. With digital twins, people all across the organization can have the same access to a realistic digital model at every stage of the product life cycle. This allows companies to harness the full power of their resources to solve problems and create innovative solutions.

Improve system reliability - With unprecedented access to system conditions and predictive modelling, technicians can identify problems before they occur. This makes systems and processes more reliable than ever.

Foster innovation - Digital twins allow product and systems designer to explore various scenarios, tweak variables, and test conditions with the click of a button. This allows for unprecedented innovation and the ability to test new ideas while lowering product development costs.

More data is more insight - Digital twins allow companies to fully exploit the data they collect from IoT sensors. Every new minute of operational data will provide greater insight into the model and allow users to more effectively design, test and monitor physical assets in digital space.

Digital twins represent a revolution in system and process monitoring, design, and collaborative work. With the technology’s ability to allow users across the organization to accurately model the inner workings of physical things, it is possible to dramatically reduce costs and create new, better solutions in areas that before were impossible. This is one of the most significant implications of the IoT revolution and will likely continue to grow in importance in the coming years.

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