Capgemini Engineering and ETH Zurich’s research partnership

A new generation of high-performance architectured lattice structures – produced economically and efficiently through 3D printing – are poised to transform modern industry. Anne-Laure Cadène explains how.

We all know there is always room for improvement. In manufacturing, for instance, industries constantly seek more from the materials they use, in terms of performance, efficiency, flexibility, or all of these and more. But conventional materials can’t always meet these stringent and growing demands.

This is why Capgemini Engineering is working in partnership with the world-class university, ETH Zurich (ETHZ), to create something better. Together, we are developing the methods and tools to design architectured lattice structures to be printed using additive manufacturing (‘AM’, sometimes called ‘3D printing’).

Architectured lattice structures are engineered materials with repeating cells, which can be used to form lightweight, strong, and functional components.

Why architectured lattice structures?

These materials offer several potential benefits:

  • Lightweighting: They can reduce mass while maintaining, or even enhancing, mechanical performance.
  • Energy absorption: Their geometry allows efficient force distribution, making them ideal for impact mitigation in products like bicycle helmets, body armor, and automotive safety components.
  • Thermal management: The high surface-area-to-volume ratio of lattice networks enhances heat dissipation, supporting applications in heat exchangers, electronics cooling, and aerospace thermal systems.
  • Biomedical integration: Lattice structures can be used to fabricate implants with porous architectures. This can lead to faster recovery thanks to better morphological biocompatibility, better mechanical behavior and customized patient-specific designs. For example, in the case of an artificial knee cap, they could better reproduce its natural shape and movement mechanics.

The challenges of developing these materials

An old proverb states that ‘nothing worth having comes easy’. It is true here – there are many scientific and developmental issues to overcome before 3D printing additive lattice structures at scale becomes a reality.

First, it’s essential to develop advanced design software and simulation tools capable of handling the complex geometries and material behaviors of architectured structures.

Second, the AM processes themselves must be developed, improving speed, precision, and material compatibility, while also reducing costs. Efforts in this area can make the future large-scale production of architectured materials more viable and cost-effective.

It’s vital, too, to be able to characterize physical properties accurately, so their mechanical strength, durability, and fatigue resistance can be properly understood and validated.

And then there are the broader challenges. Sustainability is a case in point: some additive manufacturing techniques (like laser-based technologies) are energy consumption-intensive, compared to traditional high volume manufacturing. AM can also pose recycling problems for multimaterial structures. We must learn how to mitigate these factors in the context of a world increasingly concerned with sustainability.

Quality and certifications are also an issue. Most products are expected to conform to standards specified for their category, and in some cases, like aerospace and healthcare, those standards are rightly rigorous. New approaches to manufacturing must demonstrate conformity, even as they blaze new trails.

The task is substantial. To achieve our goal of developing and then manufacturing these materials at scale, we need some of the world’s brightest researchers to work with some of the world’s best engineers. This is exactly what we are doing with ETHZ.

Research meets development: ETH Zurich and Capgemini Engineering

For over 170 years, ETH Zurich has focused on the disciplines of science, technology, engineering and mathematics (STEM). In contrast, Capgemini has leveraged technology to enable business transformation for more than 50 years, drawing on deep industry expertise and a command of the fast-evolving fields of cloud data, artificial intelligence, connectivity, software, digital engineering, and platforms. In the context of the challenge, our skills are complementary.

This project is part of our Strategic University Research Partnerships Program. This is a unique initiative, where we work alongside leading academics in selected focus areas of research and development to address key industrial and social challenges over a three to five year horizon. The objective is to deliver high-level research outputs, thought leadership, practical, game-changing and real-world benefits.

For this project, a Capgemini team, including Yosra Rahali, a highly experienced mechanical and physical engineer that is technically led by Ramon Antelo, Chief Technology Officer for Manufacturing and Industrial Operations, has joined forces with a group of researchers supervised by Professor Markus Bambach, from ETHZ’s Advanced Manufacturing Laboratory.

Since April 2023, the two teams have been working together on a three-year project to develop AI solutions in the design of multi-material structures for AM.

Meeting these challenges with digital engineering

Let’s look briefly at each of their solutions in turn:

The team developed two complementary tools. The first enables the intuitive design of a wide range of single-material lattice structures, with embedded features, like relative density, design checks and export options. The second tool automates the generation of large, varied datasets of lattices for machine learning applications, and also supports multi-material integration

The team’s researchers have also been working with a combination of experimental and computational methods to capture the behavior of architectured structures under different loading conditions (for instance, compression). These include computational methods, like finite element analysis (FEA), to simulate and predict material responses.

The Capgemini team is developing new approaches to additive manufacturing. These include using digital engineering to simulate thermal gradients, residual stresses, and material flow. We are also applying machine learning (ML) models to analyze historical 3D printing data, including material testing results, to detect defect-prone settings and optimize process parameters in real time.

Additionally, the team is also exploring AI-driven design parametrization, where machine learning models adjust geometric and material parameters—such as cell size, wall thickness, and topology—to optimize component performance for energy absorption, lightweighting, and thermal management

Sustainability in AM technologies

As we have seen, additive manufacturing presents its own sustainability challenges.

However, Additive manufacturing (AM) is reshaping production paradigms by introducing sustainable practices across the value chain. Unlike conventional subtractive methods, AM enables precise material deposition, which significantly limits waste. In powder-bed fusion techniques, such as selective laser sintering or metal AM, unfused powder can be recovered and reused, contributing to resource efficiency and aligning with circular economy principles.

Nevertheless, the sustainability impact of AM technologies remains multifaceted, especially when dealing with architectured lattice materials that involve complex geometries and multi-material systems. In this context, a global sustainability assessment is essential to capture the full spectrum of implications all along the life cycle. ETH Zurich and Capgemini Engineering are jointly developing a comprehensive evaluation framework that integrates environmental and social life cycle analysis to support responsible innovation in AM-based manufacturing.

Quality and certifications

The good news about certifying quality and fitness for purpose with AM techniques is that the topic is increasingly well-structured, as many of the evaluation criteria are adapted from traditional manufacturing standards.

What’s more, most of the traditional quality tests are also applicable to additive manufacturing while addressing the specific challenges of AM (such as the thickness of the structures or elements used, as struts, for example). For example, X-ray computed tomography (CT) and light microscopy can be used to inspect grain structure and phase distribution – which can, amongst other things, reduce production defects. Also, non-destructive testing (NDT) methods and in-situ monitoring during the build process further enhance quality control, making AM increasingly viable for certified, real-time applications.

Conclusion: answering the big question

As part of the Capgemini Engineering Strategic University research partnerships program, the overarching question that every partnership project seeks to answer is this:

“What are the key challenges of a more intelligent industry in our society?”

This strategic framework helps us to ensure that each project of the program targets one or more of our three strategic pillars: to push back boundaries in current approaches to engineering, thanks to new paradigms; to accommodate and master complexity; and to accelerate sustainability.

As we hope you can see here, that’s exactly what our partnership with ETH Zurich sets out to achieve.

Learn more about Capgemini Engineering’s Strategic University Research Program and Framework and how we’re shaping the future of intelligent industry.

The revolution of innovative architecture structures.

When design meets efficiency.