How Digital Twins create ideal 3D prints

Digital twins are a technology increasingly used across many industries, including 3D printing. To provide a deeper understanding of the concept and its applications within 3D printing, we asked our AM team manager, Anders Hjermitslev , to share his extensive experience with digital twins.

Perhaps you are already familiar with digital twins, or maybe the name just rings a bell. That wouldn't be surprising, because while the concept of digital twins has existed for several years, it has really gained momentum over the past 4-5 years. This is partly due to advancements in data collection, analysis, and computing power, which have made it possible to create more accurate and detailed models. But why exactly is it so smart?

What are Digital Twins?

At its core, a digital twin is a virtual representation—a model—of a physical process, object, or system. This model reflects what happens (or will happen) in the real, physical world. It allows us to simulate, analyze, and optimize different scenarios without having to perform physical tests.

In 3D printing, digital twins are especially valuable in the production of critical and complex components. These components are typically those where precision, durability, and reliability are paramount. This includes parts for aviation, medical devices, and advanced industrial machinery.

Two main functions in 3D printing

Digital twins are used in many contexts, but within 3D printing, there are particularly two main functions that stand out.

For one, digital twins are used before a component is printed to predict whether the given component will be able to withstand the expected load. If not, one might consider adjusting some parameters—such as which material is used for printing—and see if it changes the outcome. It may also be that based on the digital twin's prediction, production is abandoned. In that case, time, money, and materials are saved.

Another significant function is design optimization. This is often done through a process called topology optimization, where an area is defined within which the component must fit, as well as the loads and requirements it must withstand. Using digital twins, different design scenarios can be simulated to find the most optimal geometry that meets all the requirements. This can include demands for deflection, material stresses, and heat transfer. The result is a component that is lighter, stronger, and cheaper to produce.

DILAPRO shows the way

In the not-too-distant future, a new function will emerge. It relates to the DILAPRO Project , in which we at the Teknologisk Institut Institute are deeply involved. The DILAPRO project focuses on optimizing 3D printing by integrating advanced simulation and data analysis directly into the printing process. This means that with a digital twin, one can monitor what is actually happening in the print chamber as it happens. This opens up a range of new possibilities and improvements.

One of the most exciting aspects of DILAPRO is the possibility of online quality assurance. By collecting and analyzing data from the 3D printer in real-time, we can ensure that every component printed meets the necessary quality standards. In other words, it can be validated even before it leaves the printer. This means that the need for extensive subsequent testing can be reduced or even eliminated, saving time—sometimes weeks or months—and resources.

The results from DILAPRO will also, in the future, enable the introduction of new materials in 3D printing. By simulating how new materials behave during the printing process, print parameters can be quickly and accurately adjusted to achieve the best results. This opens up a wider range of applications and enhances production flexibility.

Digital Twins in the future

With DILAPRO and similar projects, we see a future where digital twins play an even greater role in the 3D printing industry. The models are continually improved and more user-friendly, making them accessible to more people. Integration with existing software tools will further increase the use of digital twins, as it becomes easier for companies to implement the technology into their existing processes.

This increased use of digital twins will improve production quality and efficiency, but it will also enable faster innovation and adaptation to new materials and technologies.