Understanding the Importance of Digital Twin and its Applications

Though it sounds straight out of Sci-Fi movies, Digital Twin is finding huge scope and potential today

Digital twins have become important to business today. By producing a replica of the physical assets of a product or service in an industry, digital twin helps in analyzing the data, lends a platform to check the functioning beforehand so as to develop a solution for any potential problems. The term came into existence when Michael Grieves, then computer engineer at the University of Michigan, wrote about it in 2002 and was named one of Gartner’s Top 10 Strategic Technology Trends for 2017.  

Trip Down the History

Basically, the digital twin is composed of three components viz., physical entities in the real world, their virtual models and the connected data that tie the two worlds. NASA was the first to leverage the digital twin technology, when Michael mentioned the possibility of creating digital representations of physical systems that had their own entity during a talk with John Vickers, NASA’s Director of Technology. The key objective was to devise a solution that can enable it to mend or update or check on a machine in outer space where it is practically impossible to be physically present at any given point in time. This inspired NASA to develop a virtual replica that can work from the desired place and can fetch real-time data. Today, NASA uses digital twins to develop new recommendations, roadmaps, and next-generation vehicles and aircraft.  

How IoT, AI and other digital technologies help?

The rising popularity of the Internet of Things (IoT) has complimented the adoption of this new technology, as IoT has resulted in its cost-effective implementation. Using IoT sensors, digital twin collates information from a real-world counterpart and then simulates the physical object in real-time, in the process offering insights into performance and likely issues. Gartner reports that 13% of organizations implementing IoT projects already use digital twins, while 62% are either in the process of establishing digital twin use or plan to do so. It is predicted that by 2022, over two-third companies will be using digital twin technology in production. Apart from the Internet of Things, companies are employing big data, artificial intelligence, machine learning, and software analytics to enhance the capabilities of the digital twin. Even cloud connectivity facilitates a large-scale implementation of digital twin technology for companies in a variety of industries. Also by using a blend of cognitive technologies and computing in the testing phase, digital twins can determine which product tests must run more frequently and which needs to be retired. Moreover,  by identifying elements that are hindering or enabling strategy execution, it can also suggest specific recommendations that could be undertaken.  

Advantages of Digital Twin

This technology offers a multitude of benefits. One of the best advantages is that it allows engineers to have access to a detailed, intricate view of a physical asset that might be far away. It enables them to foresee maintenance failures through recreation models that catch data about different risk factors. It also helps companies develop new products as a service business model and drive innovations in manufacturing, R&D, supply-chain management, service and logistics. Some of the leading players in the digital twin sector are Oracle, General Electric, Microsoft, PTC, ANSYS, Siemens, IBM and Dassault System. Further, it eases the safe removal of unnecessary products, functionality, or components, saving time and money. For e.g., Chevron uses digital twin tech for its oil fields and refineries to save millions of dollars in maintenance costs.  

Applications of Digital Twin Across Industries

Manufacturing companies are already using digital twins to augment industrial processes and offer better approaches to decrease costs, monitor assets, streamline maintenance, diminish downtime and empower the making of connected products. For instance, German packaging systems manufacturer, Optima, digitally mapped and examined its transport system using digital twin technology by Siemens. It also helps to model how product customization will affect the production process and also change how the process works to accommodate this customization. Leveraging this technology enables the reduction of development costs of the next generation of machines by well over 50%. Similarly, in the automotive sector, a digital twin can enable the convergence of existing gaps between physical and virtual versions of product prototypes, shop floor and the actual vehicle on the road. Companies are also using it for predictive maintenance by identifying deviations and anomalies in company operations. Digital twin also helps developers to accurately see how customers interact and experience the product and/or service a company provides for them and troubleshoot any bottlenecks. In the real-estate industry, it can empower agents to integrate previously scattered systems like security to HVAC to wayfinding systems for gaining new insights, optimize workflows, and monitor processes remotely. It can also allow real-estate agents to save money on property, avoid future costs, increase occupancy rates, and improve overall asset value. In healthcare, digital twins are used to build computer-based or crypto models that can create individual and group data which helps in studies of diseases, new drugs and devices. It also proves resourceful for monitoring and predicting a patient’s well-being. Even doctors use it to observe potential changes in operational strategy, capacities, staffing and care delivery models. Furthermore, in the construction industry, digital twins can account for the behaviors and processes involved in construction all the way down to the individual materials and components. This allows construction companies to continuously track progress against the schedule laid out in a 4D BIM model. Plus, it offers automatic resource allocation monitoring and waste tracking, allowing for a predictive and lean approach to resource management, and qualitative detection of any discrepancies. With the number of ongoing developments in the field that are connected to the emergence of the Internet of things, cloud and artificial intelligence, the scope of digital twin is going to rise in the future.