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
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.