What is a digital twin?
A digital twin is a digital replica of an actual physical entity such as an automobile engine, building, solar farm, or even a whole city. The digital twin can be used to simulate different processes that this physical entity would undergo and predict its performance in those process conditions.
Digital twins are quite simply programs that use real world data to predict how a product or a process will perform. These programs integrate the internet of things, artificial intelligence and data analytics to enhance the output results.Â
Owing to its wide range of benefits which include driving innovation, avoiding cumbersome manual testing and preventing costly failures, this technology has earned its reputation in the modern industry.
It has solved a number of real-world problems including fatigue testing and corrosion resistance of offshore wind turbines, efficiency improvements in cars and modelling of hospital workflows to drive procedure and staffing improvements.
Pairing technology – The inception of digital twins in aerospace
In the early days of space exploration, NASA took a fancy to pairing technology – the mother of today’s digital twin. How do you operate, maintain and repair systems when you aren’t in physical proximity to them? This was the key question that NASA was trying to answer at the time.
Today, NASA uses digital twins to develop next generation space vehicles and aircraft.Â
“The ultimate vision for the digital twin is to create, test and build our equipment in a virtual environment,†says John Vickers, NASA’s leading manufacturing expert and manager of NASA’s National Centre for Advanced Manufacturing.Â
“Only when we get it to where it performs to our requirements do we physically manufacture it. We then want that physical build to tie back to its digital twin through sensors so that the digital twin contains all the information that we could have by inspecting the physical build.â€
A sneak peek into the functioning of this miraculous technology
The lifecycle of a digital twin starts when experts study the mechanics and operational parameters of a physical system to develop a mathematical model which simulates the original.
The developers build digital twins or virtual models, which can receive feedback from sensors connected to the actual physical system. The sensors capture vital operational data and the digital model mimics what is happening to the physical system in real time.
As a result, one can understand and analyse the performance of the physical system to identify opportunities for improvement. A digital twin allows users to explore solutions for product lifecycle extension, manufacturing and process improvements, product development and prototype testing.
The twin can be used with a prototype to offer feedback on the product as it is developed or can even act as a prototype by itself to model what could occur with a physical version when developed.
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Essential ingredients for a digital twin concoction
Data
A digital twin requires data related to the lifecycle of a product including design specifications, production processes, equipment, materials, etc. to model its response in a real-world application. It can also collect operational data such as real-time feedback, historical analysis, and maintenance records.
Modelling
The accumulated data can be used to create virtual models that predict states such as fatigue and analyse response. These models are based off different knowledge systems such as engineering, science, artificial intelligence, and mathematics. Ultimately, they can be displayed via 3D representations and AR modelling to deliver critical performance insights to the end-user.
Use-cases
Manufacturing: Digital Twins have a significant impact on the way products are designed, manufactured and maintained. It optimizes manufacturing and reduces downtime there by significantly increasing overall profit.
Automobile: Digital Twins can be used in the automobile sector to create the virtual model of a connected vehicle. It captures the behavioral and operational data of the vehicle and helps in analysing the overall vehicle performance.
Retail:Â Digital twin implementation plays a pivotal role in augmenting the retail customer experience by creating virtual twins for customers and modelling fashions for them on it.
Healthcare: Digital Twins along with data from IoT offer a range of solutions in the health care sector from cost savings to patient monitoring, preventive maintenance and personalized health care.
Smart Cities: The smart city planning and implementation with Digital Twins and IoT data helps enhance economic development, ensure efficient management of resources, reduce ecological foot print and increase overall quality of life. The digital twin model can assist city planners and policymakers in city planning by supplying actionable insights.
Industrial IoT: Digital twins can optimize an IoT deployment for maximum efficiency, as well as help designers figure out where things should go or how they should operate before they are physically deployed. They can effectively simulate how devices have performed over time to predict future performance and possible failure.Â
The bottom-line
Digital twin technology allows companies to provide a superior customer experience by gaining deep insights into customer requirements, upgrading existing products, operations and services, and reinventing businesses.
GE’s digital wind farm is testimony to the success of this technology: it uses a virtual twin to improve the configuration of each wind turbine prior to construction and achieve 20% gains in efficiency.
Ganesh Bell, chief digital officer and general manager of Software and Analytics at GE Power and Water says “For every physical asset in the world, we have a virtual copy running in the cloud that gets richer with every second of operational data.â€
As you get ready to embrace digital twin technology and usher in a new age of performance optimization, Hakuna Matata can serve as your strategic technology partner for a successful transition.
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