What are digital twins?

Introduction

Imagine a world where every physical object, system, or process – such as an appliance or industrial machinery – has a digital counterpart: a virtual twin that reflects it in real-time. This is the core concept of digital twins, a groundbreaking technology impacting multiple industries. These twins gather data from their environment and constantly update their digital replica to mirror reality, enabling simulations and accurate predictions, and providing valuable insights for decision-making.

In this blog post, I will explore the definition of digital twins, their key components, and practical use cases, offering concrete examples. Additionally, we’ll look at how the development of digital twins can reshape operations in an increasingly data-driven world.

The evolution and market of digital twins

Originally, the use of digital twins was limited to the aerospace and manufacturing industries, where they played a crucial role in simulating and optimizing complex systems. As technology and computational power advanced, the use of digital twins quickly expanded across various sectors. Today, digital twins are not just limited to physical products or systems – their application field is vast. They have evolved from static models into dynamic, real-time representations of physical objects, enabling more comprehensive monitoring, analysis, and forecasting of products and ecosystems.

Looking at the market, the global digital twin market is growing exponentially. It is expected to rise from $11.5 billion in 2023 to $137.63 billion by 2030. From aerospace to healthcare, digital twins are becoming essential tools for efficient and data-driven operational management.

Key components of a digital twin

What makes up a digital twin, and what are its key building blocks? The core elements of a digital twin include:

Data Integration: Sensors collect data that is integrated into a unified platform. This real-time data enables the twin to operate in sync with the physical counterpart, providing a comprehensive view of the object’s state.

Modeling and Simulation: Digital twins use simulations to predict how changes will impact the entire system. For instance, in manufacturing, they can forecast production line efficiency and product quality.

Real-Time Monitoring and Management: Digital twins provide continuous feedback on the performance of the physical object, allowing for quick decision-making and responsive actions.

Use cases for digital twins

How can digital twins enhance operations across industries? They offer solutions for optimizing production, logistics, construction projects, and healthcare. Next, I will explore the various use cases of digital twins across industries through concrete examples.

Manufacturing: Digital twins allow for virtual modeling of production lines and machines, optimizing processes, reducing downtime, and predicting maintenance needs.

For example, Konecranes has developed a Smart Factory solution that provides a real-time view of factory operations and maintenance.

Construction: Digital twins of buildings assist in design, construction, and maintenance, enhancing energy efficiency and space utilization.

For example, YIT leverages digital twins in its smart buildings to improve energy management and resident comfort, as well as optimize operations during construction projects. YIT also created a digital twin of the Kruunusilta bridge project.

Offices and property management: Digital twins enable virtual modeling of building interiors, allowing real-time tracking of occupancy rates, energy consumption, and indoor air quality. This enhances space usability, energy efficiency, and optimizes maintenance activities.

For example, at DSB, we developed a digital twin called Empathic Building for property management and office environments. It visualizes building data for users and helps them navigate the space more efficiently.

Transportation and logistics: Digital twins model transport networks and vehicles, improving route planning and fleet management.

For example, KONE uses digital twins in its elevators and escalators to ensure optimal performance and predictive maintenance.

Energy sector: Energy companies create digital twins of power plants and distribution networks, enabling real-time monitoring and efficient energy management.

For example, Fortum uses digital twins to enhance the efficiency and reliability of their power plants.

Healthcare: In healthcare, there are two main types of use cases for digital twins, which can be employed both to optimize individualized treatment plans for patients and to manage the internal spaces of healthcare facilities.

For example, Milton Keynes University Hospital (MKUH) utilized our digital twin platform to enhance the tracking of equipment and staff locations, as well as to manage the environment through real-time data.

Another use case is illustrated by a research team at Tampere University, which developed a digital twin for acute myeloid leukemia. This twin leverages clinical and molecular-level patient data to aid in disease monitoring and treatment.

Aerospace and aircraft maintenance: Digital twins are particularly valuable in aerospace, enabling real-time performance monitoring of aircraft engines and other critical components. This reduces maintenance costs and increases safety by allowing proactive identification and resolution of issues.

For example, Patria uses digital twins in aircraft maintenance and performance optimization, increasing aircraft availability and improving safety. Through digital twins, Patria can simulate flight situations and plan precise maintenance actions without grounding aircraft for long periods.

Challenges and solutions

There are several challenges associated with the use of digital twins, such as the complexity of data integration, high computational power requirements, cybersecurity concerns, and the complexity of the models. The solution lies in investing in efficient tools, such as cloud-based platforms and edge computing, and adhering to strict regulations to ensure data protection. Another challenge is the shortage of skilled local professionals who can manage both the creation of complex models and the necessary technologies, such as IoT platform development and data integration. At DSB, we are one of the few providers in the field specializing in digital twin development. We provide end-to-end digital twin services, encompassing everything from data integration and IoT platform management to custom software development.

The future of digital twins

In the future, digital twins will revolutionize various industries, including healthcare, education, and urban planning. They will enable more precise and personalized solutions, such as individualized treatment plans and sustainable city designs. Digital twins will also support the development of autonomous systems, including the testing of vehicles and robots. Digital twins will transform how we design and manage our environments, bringing unprecedented opportunities for increased efficiency and innovation.

If you are interested in learning more about the possibilities of digital twins, feel free to reach out – let's discuss how we can elevate your development to the next level.