Have you ever imagined a scenario where tangible assets, objects, or machines could replicate themselves virtually and realize their twin? Exactly like a human twin that shows similar appearance and behavior. Well, the concept of digital twins is no longer a theory and has evolved remarkably since its inception around two decades ago. Thanks to the advent of Industry 4.0, some notable advancements have been witnessed in sensing, monitoring, and decision-making tools.
These advancements have paved the way for the precise implementation of Digital Twin for the real-time monitoring and optimization of the process across several applications. Citing its speedy adoption by the industries in order to develop new and improved products, paired with other factors, the Digital Twin Market size is predicted to grow at a whopping 58% CAGR during 2023-28, says Markntel Advisors in its recent report. Thanks to the ever-increasing demand for asset monitoring, rising penetration of Industrial IoT (IIoT), and the growing number of smart building infrastructures to ensure optimum energy consumption that enabled the technology to expand at such a significant growth pace.
Digital Twin: The Striking Convergence Between Physical and Virtual Products
As the name clearly depicts, Digital Twin is a virtual representation of physical objects across the lifecycle that can be integrated with real-time data or a simulation model that acquires data from the field and triggers the operation of physical devices. The four technologies that encompass DT are Artificial Intelligence (AI), Internet of Things (IoT), Cloud, and Extended Reality (XR).
Over the years, the technology has made its way to plenty of use cases in industries. Numerous industries, particularly engineering, and manufacturing, are not shying away from implementing the virtual representation of their actual unique product or service and simulations of operational processes via digital twin. Let’s spill the beans on a few use cases and applications.
Digital twins are extensively used in the manufacturing industry, primarily in applications such as product development, design customization, shop floor performance improvement, and predictive maintenance. Engineers leverage them to test and adjust new product designs, offer personalized products, monitor end-product performance, and predict machine downtimes for efficient maintenance. In aerospace and automotive manufacturing, they ensure safety and optimize production processes by addressing issues with airframes, engines, and components. They are particularly valuable for self-driving car development, minimizing unexpected damage and injuries through comprehensive testing.
Construction and Real Estate Industries
Digital Twins can automate project control by providing real-time insights into construction progress and enabling early detection of deviations from the budget or schedule. Resource planning and logistics can be improved by monitoring resource allocation and waste, optimizing efficiency and productivity. The technology also contributes to construction safety by tracking and addressing potential safety risks, offering real-time monitoring and targeted training for workers. Quality control and assessment can be enhanced by analyzing images to identify issues or defects, ensuring the quality of the construction process. Additionally, it can be used to assess building performance by simulating various conditions and scenarios, evaluating energy efficiency, comfort, and indoor environmental quality.
In the context of smart cities, the connectivity enabled by the Internet of Things (IoT) enhances the effectiveness of digital twin solutions. In the energy sector, where power systems are becoming more complex, digitalization of power assets is a prominent topic. The technology proves valuable for optimizing assets and can be applied throughout the energy sector to improve maintenance, production planning, plant efficiency, and risk mitigation. A recent study proposes the use of such technology to create a digital power grid, digitizing the entire process and elements of the physical power grid, including human and physical events. This digital power grid solution facilitates power grid planning, design, construction, management, and services, leading to improved efficiency in energy resource utilization and information allocation within the power grid.
Healthcare and Life Sciences
Digital Twins have transformative potential in healthcare and life sciences, advancing research, treatment, and operational efficiency. In drug discovery and development, virtual representations are used to simulate and test new drugs for safety and effectiveness, speeding up clinical trials and aiding in the selection of optimal antigens for vaccine development. They also play a role in advanced diagnosis and preventive treatment by simulating patient characteristics and predicting their behavior and response to specific situations. They have the potential to revolutionize clinical research methodologies, allowing for predictions of experimental treatment outcomes and providing insights without risking patient safety.
Personalized medicine is also enhanced, enabling physicians to model a patient’s best course of treatment based on numerous variables. These solutions are also employed in facility and operations design, optimizing hospitals, capacity planning, workflows, staffing systems, and care delivery. Additionally, they support education and training in healthcare, offering simulated learning experiences and enhancing medical education. Diagnosis and therapy benefit from digital twins through their ability to generate replicas of cells, genomes, or organs, aiding in surgical planning and identifying risks associated with procedures.
Coming to an End,
Although in its infancy, the concept of Digital Twins has materialized much faster in recent years. With suitable integration with more technologies such as augmented reality, speech capabilities, IoT, and artificial intelligence, the idea of replicating objects virtually is all set to revolutionize the industry by streamlining and ensuring smooth operations, quickly detecting and solving physical problems, designing and building better products and realize value and benefits relatively faster.