The concept of Digital Twin is not new. The technology has been in use since 1960s. NASA has been creating physically duplicate systems for its various space mission at ground level to test its equipment in a virtual environment. An example to this is Apollo 13 for which a Digital Twin was developed by NASA to assess and simulate conditions on board.
In recent past, Digital Twin has become one of the most promising technological trends. It is estimated that the technology will be utilized by half of the large industrial companies and approximately 21 billion digitally connected sensors by 2020, which could potentially save billions in maintenance repair and operation.
Digital Twins enables in-depth analyses by leveraging big data, IoT and AI solutions. It is very useful in detecting potential issues, preventing downtime and testing new business opportunities, plan future scenarios through simulation and customize production based on customer requirements.
With the technology it is possible to have immediate feedback about the activity in progress and apply eventual corrections in record time. With it’s this functionality, Digital Twins are particularly useful for the maintenance of connected heavy machines and infrastructure that generates and analyses large volume of data. However, the application of digital twin is more than this.
Let’s have a look at some of the use cases of Digital Twin
In healthcare digital twins of particular patient organs allow doctors to test different care delivery approaches and prevent conditions that are years apart and enable patient-specific surgery training to prepare for complex invasive procedures. With insight created by digital twins, healthcare organizations can create innovative practices to correct the problem and minimize the possibility of any kind of risk. Also, real-time epidemiology data can help hospital staffers to track where infections agents may exists and who could be at risk by contacts.
In utilities, the robust system enables efficient management of a wide range of document, including 3D models, 2D process schematics, as-built documents, instrumentation data and other business and critical Engineering & Design information. Here Digital Twin real-time data which This allows project manager at oil and gas companies to achieve a real ‘as-designed,’ ‘as-built,’ ‘as-operated’ visibility into their fleet of globally distributed assets, enabling them to quickly and efficiently re-plan and reposition the fleet to access new opportunities globally.
Earth’s climate is now changing faster than at any point in the history of modern civilization, primarily as a result of human activities. Global climate change has already resulted in a wide range of impacts across every region of the country and many sectors of the economy that are expected to grow in the coming decades. Fires, flood, and drought have become normal now. In such a scenario, Digital Twin can be used to build smarter infrastructure like dams, utility networks, emergency response plans, and zoning.
For insuring anything from any kind of risk it is important to understand the location of the risk. For example, insure a famous historical monument from risk of terrorist attack, a Digital Twin model can help to understand that which is the area from where terrorists can easily enter in the monument. Once the location is known it is easy to take protective measures. Another use case of Digital Twin in Insurance can be use of the technology while building any infrastructure, where it can help to access risks in advance.
Digital Twin can help cities to become more environmentally, economically and socially sustainable. It enable users to create models that guide their future plans and help provide solution to the complex issues that cities face. In case of any disaster like flood, Digital Twin provides useful information in real-time, like which areas are flooded, which infrastructure will be closed down, which hospitals could be affected and thus allowing city managers to take immediate action.
Explore more about digital twin at Geospatial World Forum 2020