Ever since dealing with complex issues, people have been using certain tools including drawings, pictures, and models to aid them. Luckily, modeling capabilities have become more and more sophisticated over time having outdated previous methods with advanced modeling systems being able to simulate a products’ geometry, operation as well as behavior.
There has been a long history of using high-fidelity simulation and a direct physical replica to support the operation and maintenance of an asset, dating back to the 1970s and NASA’s Apollo 13 mission. However, back in the day, building digital twins was a complex and costly task based on technologies that were neither advanced nor mature enough.
Thanks to rapid development in the Internet of Things (IoT), Artificial Intelligence (AI), Augmented, Mixed & Virtual Reality (AR/ VR), Cloud Computing, and API, & Open Standards, digital twins are a new innovative phenomenon that manages to close the gap between model and reality, linking previously offline physical assets to digital models that consist of data stemmed from the changes experienced by the physical object. The underlying and key enabling technologies, comprising low-cost data storage and computing power, the availability of robust, high-speed wireless networks, and cheap, reliable sensors have reached the level of maturity that is necessary to support the use of digital twins for enterprise applications. Nowadays, many products, for instance, consumer electronics, automobiles, and even household appliances include sensors and data communication capabilities as standard features.
Digital twins extend the benefits of IoT already being applied today, generating valuable insights from operational data, and thus aiding organizations in planning, designing, visualizing, monitoring, managing, and maintaining their assets as well as the entire global supply chain more effectively. The adoption of digital twins in, for instance, manufacturing within and across industries positively impacts decision-making in the physical world, and thus leads to significantly improved operation of supply chains and logistics processes.
Corporate interest in adopting digital twin solutions keeps growing while technology providers, including large enterprise technology companies, automation systems manufacturers, and start-ups, enter this potentially lucrative space to grab opportunities matching demand with supply. The digital twin market is projected to grow approx. 38% annually over the coming years, passing US$26 billion in 2025.
To dive into a little bit of detail, digital twins come in many forms and need to be clearly distinguished from other types of computer models and simulations. So what exactly is a digital twin? Here are some key characteristics of a digital twin:
■ virtual representation or, in other words, digital counterpart of a real ‘thing’
■ simulates the physical state as well as the behavior of the thing
■ unique representation of a single, specific instance of the thing
■ connected to and associated with the thing, updating itself in relation and response to known changes to the thing’s condition and/ or context
