Digital Twin is the ultimate representation of the next technological leap: the union of the physical world with intelligent virtual models, which are even considered pioneers in what we know as the Fourth Industrial Revolution.
Born from NASA's tech-mirroring concept in 2002, digital twins are no longer just a concept resulting from the growth and expansion of the Internet of Things (IoT). In fact, Gartner ranked them as one of the 10 Strategic Trends in the last two years for their ability to learn and provide data continuously.
Companies across industries such as automotive, healthcare, retail and finance are applying digital twins to design and operate complex products and processes, from turbines and banking to supermarket shelves. Gartner also predicts that by 2021, half of large industrial companies will have adopted this technology, enabling them to accelerate product and service development, optimize performance, and perform predictive maintenance.
How does it work?
Sensors are placed on the real models in order to collect data on the state of the process, product or service. Then, based on this information, a virtual prototype is made on which the tests will be carried out.
Its main advantages include:
- Preventing problems and failures before they occur
- Low-cost testing of different risk scenarios
- Simulate possible uses of products and services
- Develop new business opportunities
- Create predictive behaviors
- Customize production to customer requirements with the possibility of modification.
In addition, it is estimated that Digital Twins are capable of reducing time-to-market by almost 50%, as well as increasing productivity by up to 20%. At the same time, virtual testing helps to reduce energy use by up to 70%, as well as the emission of polluting gases.
Frequent uses
In the automotive industry it is used to perform thousands of tests with different and possible scenarios in virtual environments, without the cost of creating and destroying real prototypes.
Inbanking, it is implemented to track our evolution as individuals and how fraud and our evolution against it can evolve as we go through different stages of our lives: from student, to young professional, to parent, for example.
In the case of VU, we use it to simulate a secure testing environment to implement VU solutions in banks. This allows us to apply the secure onboarding process with facial recognition and fraud prevention, for example, to make sure it works properly before deploying it live to our customers. This process helps to ensure smooth operation, decrease transactional friction caused by errors and guarantee a successful transition to digital transformation.
The Digital Twin, combined with Artificial Intelligence and Machine Learning is growing and evolving with us and modifying the thresholds of evaluation, protection and positive and negative results of the model to ensure our safety at all times.
Written by Sebastián Stranieri
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