The increase in use cases for digital twins is leading many organizations to implement this technology in search of an improvement in their processes. This is due to the proliferation of other technologies on which it is based, such as IoT, cloud or big data. Thus, thanks to the incorporation of data in real time, digital twins are making it possible to create virtual simulations to minimize risks. In addition, they can predict behaviors and improve the predictive capacity of companies, thus achieving greater efficiency in decision making.

Despite their current popularity, digital twins have their origins in NASA in the 1980s, when on the Apollo XIII mission they carried out simulations to see the behavior of spacecraft with the purpose of guaranteeing a safe mission. Since then, it has been adapted to become the accelerator of the future that it represents today.

In the era of smart industry[1], where organizations are digitally transforming their processes to remain competitive in the market, digital twins are being launched especially in those sectors dedicated to distribution or product design and in the automotive industry.

Likewise, aerospace and defense organizations are also turning to this technology to advance their digital transformation journeys. According to a report prepared by Capgemini, investment in digital twins in this sector has increased by 40% in the last year. These data speak of the clear commitment of organizations as a result of the growing confidence in the ability of this technology to generate benefits throughout the entire value chain, from manufacturing to ongoing operations.

Modernize development and manufacturing programs; save costs; accelerate development processes; minimize errors; increase sales. There are multiple key factors that are leading Aeronautics and Defense organizations to implement digital twins, especially in the design phase, since this is where short-term benefits are obtained.

Especially relevant is the role of digital twins in supply chains, which facilitate data-based decision making, simplifying processes and providing greater resilience. Everyone knows the recent crisis suffered in the supply chain of all sectors, which are now beginning to develop a virtual network environment to compose, simulate, monitor and analyze the performance and flow of products thanks to the application of digital twins, eager to counteract future disruptions and optimize current operations.

In many other cases, it is also providing added value to the organizations that use it, when it comes to improving the availability and reliability of their systems and equipment, and even managing to optimize production rates. Far from being a mere creation of 3D models of products and services, aerospace companies are beginning to realize that this technology offers precision when simulating each step of the creation process, from design to manufacturing, through the operations and applications in the real world.

To reinforce this great potential of digital twins, it is necessary for companies to have both a wide deployment of intelligent digital infrastructure and good data management and processing. In fact, for many organizations it is precisely this lack of a unified data platform that is the main barrier to launching digital twin initiatives.

In addition to advancing faster in digital transformation and allowing the application of intelligence to operations throughout the entire value chain, digital twins are a sure value for optimizing the use of resources – raw materials, energy, etc. -, so many organizations are using them to meet their ESG commitments and sustainability agenda. Not in vain, they offer flexible ways of working to mitigate risks and facilitate collaboration, which in itself constitutes an unbeatable opportunity to increase profitability and predict energy consumption and emissions. According to Capgemini research, those who have already started applying digital twin technology are achieving an average 16% improvement in sustainability metrics.

Currently, digital twins already constitute the core of the Smart Industry transformation and are expected to continue expanding. In the immediate future, they will allow automation at every point in the value chain, generating considerable cost reductions and driving innovation. Organizations now need to ensure they are prepared to harness the full potential of this transformative technology, with a