ETH Zurich
Canvas Category Consultancy : Research : Academic
ETH Zurich – Where the future begins. Freedom and individual responsibility, entrepreneurial spirit and open-mindedness: ETH Zurich stands on a bedrock of true Swiss values. Our university for science and technology dates back to the year 1855, when the founders of modern-day Switzerland created it as a centre of innovation and knowledge. At ETH Zurich, students discover an ideal environment for independent thinking, researchers a climate which in-spires top performance. Situated in the heart of Europe, yet forging connections all over the world, ETH Zurich is pioneering effective solutions to the global challenges of today and tomorrow.
Assembly Line
Swiss-Mile secures over €19.8 million in seed funding, co-led by Jeff Bezos and HongShan
Swiss-Mile, a pioneering company connecting AI with the physical world using autonomous machines, announced the successful closure of over €19.8 million seed funding round. This round was notably co-led by Jeff Bezos, through Bezos Expeditions, and HongShan, with additional participation from the Amazon Industrial Innovation Fund and Armada Investment. The round also saw continued support from existing investor Linear Capital, underscoring the strong belief in Swiss-Mile’s vision and potential.
Swiss-Mile is a spin-off from the renowned Robotic Systems Lab at ETH Zurich and has been at the forefront of integrating artificial neural networks into robots with both legs and wheels. The company’s technology allows robots to walk, drive, stand upright on two legs, and manipulate objects with wheeled end effectors. This versatility is key to addressing real-world challenges in both mobility and manipulation, positioning Swiss-Mile as a leader in the next wave of robotic automation.
Apheros secures $1.85M to cool down data centers, using high performance cooling systems
Data centers are the backbone of the digital age, with unprecedented demand for digital infrastructure driven by the surge in the use of AI, machine learning, and supercomputing. However, their energy consumption is skyrocketing. By 2030, an estimated six percent of global energy consumption will be used specifically for cooling data centers. A shift from traditional cooling methods to more cost- and energy efficient liquid-based solutions is inevitable. Enabling this transition, deep tech startup Apheros is announcing a $1.85m funding round seizing this critical moment to introduce its innovative metal foam technology, offering a superior solution to this pressing industry challenge.
The pre-seed funding round, led by venture capital firm Founderful, will accelerate development and deployment of Apheros’ revolutionary metal foam-based cooling solutions.
The Apheros patented manufacturing process creates unique foam structures with completely open porosity and unparalleled surface area, surpassing traditional solutions by a factor of thousand, which translates into exceptional heat transfer and flow properties. Ideal for high performance cooling applications, Apheros’ metal foams are easily integrated within its customers’ existing cooling systems. They address customers’ urgent needs of reduced energy consumption and cooling costs.
Flink Robotics gets €156,000 kick to transform industrial robots in into dynamic workers
Industrial automation startup Flink Robotics has received €156,000 (CHF 150,000) from Venture Kick to enable robots to adapt to dynamic environments. Flink Robotics will use the CHF 150,000 from Venture Kick to accelerate its go-to-market strategy and undertake additional pilot projects.
Flink Robotics is an ETH spinoff emerging from the Computational Robotics Lab and affiliated with the ETH AI Center. Its founding team includes CEO Dr. Moritz Geilinger, CTO Simon Huber, and CSO Prof. Dr. Stelian Coros.
Flink Robotics transforms robots into adaptable, plug-and-play workers suitable for a variety of dynamic material handling tasks. Its software, FlinkAutonomy, has built-in physical intelligence that enables robots to perceive and react to changes in their environment and collaboratively solve material handling tasks.
Polyplastics invests in NEMATX to advance 3D printing of liquid crystal polymers
Japanese engineering materials company Polyplastics Co. Ltd recently invested in Switzerland-based startup NEMATX AG, a spin-out from ETH Zurich that specializes in industrial material extrusion 3D printing. This strategic investment will enable the companies to develop and bring to market high-performance polymer grades that will expand end-use additive manufacturing applications in industries like automotive, aerospace, electronics, semiconductor, medical and more.
Through the investment, Polyplastics will leverage NEMATX’s 3D printing solution, while NEMATX will incorporate the Japan-based firm’s experience in LCP processing in its own product development. The partnership will also ultimately support the adoption of NEMATX’s NEX 01 platform in specialized markets around the globe, including the electrical and semiconductor industries, which can benefit from the ability to print precision components from LCPs like connector housings for PCBs and thin-film components for printed electronics.
Researchers at ETH Zurich develop the fastest possible flow algorithm
Imagine you are using the European transportation network and looking for the fastest and cheapest route to move as many goods as possible from Copenhagen to Milan. Kyng’s algorithm can be applied in such cases to calculate the optimal, lowest-cost traffic flow for any kind of network – be it rail, road, water or the internet. His algorithm performs these computations so fast that it can deliver the solution at the very moment a computer reads the data that describes the network.
Using the algorithm, computing time and network size increase at the same rate – a bit like going on a hike and constantly keeping up the same pace however steep the path gets. A glance at the raw figures shows just how far we have come: until the turn of the millennium, no algorithm managed to compute faster than m1.5, where m stands for the number of connections in a network that the computer has to calculate, and just reading the network data once takes m time. In 2004, the computing speed required to solve the problem was successfully reduced to m1.33. Using Kyng’s algorithm, the “additional” computing time required to reach the solution after reading the network data is now negligible.
AI robotic arm to tackle labour shortages: Swiss startup mimic grabs $2.5M funding
In the race to develop the first commercially available humanoid robot primarily concentrated in the US, mimic has closed a pre-seed round of $2.5 million. The round was led by early-stage Swiss investor Founderful, which invested in Isospec Analytics, together with participation from German-based fund another.vc, UK-based Tiny.vc, which invested in UltiHash, and a lineup of angel investors.
Spinning out from the research university ETH Zurich, mimic was founded by researchers Elvis Nava, Stefan Weirich, Stephan-Daniel Gravert, and Benedek Forrai in 2024. The founding team was working at the intersection of robotics and AI under Professor Robert Katzschmann’s Soft Robotic Labs when they became increasingly convinced that the latest developments in large-scale generative AI models would upend a multitude of industries, beyond just language and image generation.
As per the company, its solution will enable a robot with humanoid hands to understand and imitate any behaviour, simply by watching a human perform it. This deviates from the conventional robotic solutions and focuses on specific use cases. Since each use case requires expensive ad-hoc engineering and comprehensive pre-programmed movements, robots are only able to complete the narrowly specific task they are designed for. Most use cases are stationary and do not require a full humanoid robot with legs, so they have developed a robotic arm.
ETH spin-offs develop high-performance batteries
Moritz Futscher and Abdessalem Aribia, the two founders of BTRY, have therefore developed a solid-state battery that consists of thin layers, which can shorten the charging time many times over. The two researchers entirely forego liquids both during the manufacturing process and for the components of their battery. The solid-state batteries that are currently being developed by BTRY have the major advantage of being very resistant to temperature fluctuations. They can therefore be used both at very high temperatures, such as in sensors that detect vapour leaks, and at very low temperatures, for example during the transportation of medicines.
ETH spin-off 8inks stands out from other battery manufacturers with its innovative production technology. It aims to use this to replace the manufacturing standard for lithium-ion batteries that has remained largely unchanged for the last 30 years – the so-called slot die technique. Paul Baade, founder of 8inks, has developed a technique called “multilayer curtain coating”. By applying several thin coats of the active material in which the lithium-ion is stored, the coating technique can be tailored to the applicable requirements. Owing to the variety in terms of the thickness and material properties of the individual layers, the technique supports, among other things, the scaling of solid-state batteries. Another advantage of the technique is that the coating speed of the battery electrodes can be vastly accelerated and is therefore optimally suited to meet the rising demand.
Automated machine tool dynamics identification for predicting milling stability charts in industrial applications
As the machine tool dynamics at the tooltip is a crucial input for chatter prediction, obtaining these dynamics for industrial applications is neither feasible through experimental impact testing for numerous tool-holder-spindle combinations nor feasible through physics-based modeling of the entire machine tool due to their sophisticated complexities and calibrations. Hence, the often-chosen path is a mathematical coupling of experimentally measured machine tool dynamics to model-predicted tool-holder dynamics. This paper introduces a novel measurement device for the experimental characterization of machine tool dynamics. The device can be simply mounted to the spindle flange to automatically capture the corresponding dynamics at the machine tool side, eliminating the need for expertise and time-consuming setup efforts thus presenting a viable solution for industries. The effectiveness of this method is evaluated against conventional spindle receptance measurement attempts using impact tests. The obtained results are further validated in the prediction of tooltip dynamics and stability boundaries.
ABB acquires Sevensense, expanding leadership in next-generation AI-enabled mobile robotics
ABB announced that it has acquired Swiss start-up Sevensense, a leading provider of AI-enabled 3D vision navigation technology for autonomous mobile robots (AMRs). Sevensense was founded in 2018 as a spin-off from Swiss technical University, ETH Zurich.
Sevensense’s pioneering navigation technology combines AI and 3D vision, enabling AMRs to make intelligent decisions, differentiating between fixed and mobile objects in dynamic environments. Once manually guided, mobile robots with Visual Simultaneous Localization and Mapping (Visual SLAM) technology create a map that is used to operate independently, reducing commissioning time from weeks to days and enabling the AMRs to navigate in highly complex, dynamic environments alongside people. Maps are constantly updated and shared across the fleet, offering instant scalability without interrupting operations and greater flexibility compared to other navigation technologies.
Holcim launches Phoenix, the first-of-its-kind circular 3D-printed concrete bridge
Holcim launches Phoenix, the first-of-its-kind 3D-printed concrete masonry bridge built with 10 tons of recycled materials, at its Innovation Hub in Europe. Using its proprietary ECOCycle® circular technology, Holcim developed a custom concrete ink for Phoenix with recycled materials inside. Phoenix demonstrates how circular construction combined with 3D concrete printing can enable low-carbon infrastructure applications.
Circular construction, using computational design and 3D printing, allows for a reduction of up to 50% of the materials used with no compromise in performance. Circular by design, Phoenix stands solely through compression without reinforcement, with blocks that can be easily disassembled and recycled. Holcim and its partners are now exploring how Phoenix could be scaled up to provide more generalized sustainable infrastructure solutions.
This 3D printer can watch itself fabricate objects
Researchers from MIT, the MIT spinout Inkbit, and ETH Zurich have developed a new 3D inkjet printing system that works with a much wider range of materials. Their printer utilizes computer vision to automatically scan the 3D printing surface and adjust the amount of resin each nozzle deposits in real-time to ensure no areas have too much or too little material.
Since it does not require mechanical parts to smooth the resin, this contactless system works with materials that cure more slowly than the acrylates which are traditionally used in 3D printing. Some slower-curing material chemistries can offer improved performance over acrylates, such as greater elasticity, durability, or longevity.
In addition, the automatic system makes adjustments without stopping or slowing the printing process, making this production-grade printer about 660 times faster than a comparable 3D inkjet printing system.
SonoPrint: Acoustically Assisted Volumetric 3D Printing for Composites
Advancements in additive manufacturing in composites have transformed various fields in aerospace, medical devices, tissue engineering, and electronics, enabling fine-tuning material properties by reinforcing internal particles and adjusting their type, orientation, and volume fraction. This capability opens new possibilities for tailoring materials to specific applications and optimizing the performance of 3D-printed objects. Existing reinforcement strategies are restricted to pattern types, alignment areas, and particle characteristics. Alternatively, acoustics provide versatility by controlling particles independent of their size, geometry, and charge and can create intricate pattern formations. Despite the potential of acoustics in most 3D printing, limitation arises from the scattering of the acoustic field between the polymerized hard layers and the unpolymerized resin, leading to undesirable patterning formation. However, this challenge can be addressed by adopting a novel approach that involves simultaneous reinforcement and printing the entire structure. Here, we present SonoPrint, an acoustically-assisted volumetric 3D printer that produces mechanically tunable composite geometries by patterning reinforcement microparticles within the fabricated structure. SonoPrint creates a standing wave field that produces a targeted particle motif in the photosensitive resin while simultaneously printing the object in just a few minutes. We have also demonstrated various patterning configurations such as lines, radial lines, circles, rhombuses, quadrilaterals, and hexagons using microscopic particles such as glass, metal, and polystyrene particles. Furthermore, we fabricated diverse composites using different resins, achieving 87 microns feature size. We have shown that the printed structure with patterned microparticles increased their tensile and compression strength by ∼38% and ∼75%, respectively.
Using process mining to improve productivity in make-to-stock manufacturing
This paper proposes a data-driven procedure to improve productivity in make-to-stock manufacturing. By leveraging recent developments in information systems research, the paper addresses manufacturing systems with high process complexity and variety. Specifically, the proposed procedure draws upon process mining to dynamically map and analyse manufacturing processes in an automated manner. This way, manufacturers can leverage data to overcome the limitations of existing process mapping methods, which only provide static snapshots of process flows. By bridging data and process science, process mining can exploit hitherto untapped potential for productivity improvement. The proposed procedure is empirically validated at a leading manufacturer of sanitary products. The field test leads to three concrete improvement suggestions for the company. This research contributes to the literature on production research by demonstrating a novel use of process mining in manufacturing and by guiding practitioners in its implementation.