chanelink logo
CHANELINK
English

EOS and AMCM will open a new UK Additive Manufacturing Excellence Center

934
2024-04-15 16:56:09
See translation

The University of Wolverhampton (UK), along with global 3D printing leaders EOS and AMCM, will collaborate to establish a new Centre of Excellence (AM) for Additive Manufacturing in the UK. This partnership will provide cutting-edge technology from EOS and AMCM, and focus on developing advanced materials and processes for high demand applications in industries such as aerospace, automotive, aerospace, electronics, and quantum computing.

The center is partially funded by the Regional Innovation Fund (RIF) in the UK and will be located at the Elite Manufacturing Skills Center (ECMS) at the University of Wolverhampton Springfield campus. It will serve as a center for knowledge exchange and research commercialization activities, providing services to local, regional, and global clients in various fields.

Desire for innovation in additive manufacturing
The additive manufacturing research group and its spin off company Additive Analytics at the University of Wolverhampton will lead materials and process development activities. Industries from automobiles and electronics to quantum computing and aerospace have expressed interest and emphasized the widespread applicability of copper additive manufacturing in thermal management and electrification due to its excellent thermal and electrical performance.

Although copper has ideal properties, laser processing it poses challenges and hinders its widespread adoption in additive manufacturing. The alliance's work aims to address this issue by utilizing cutting-edge technology, processes, and expertise to improve efficiency and reduce material waste.

Decades of expertise in additive manufacturing
Building on a 20-year partnership between the University of Wolverhampton and EOS, the new Center of Excellence will be supported by the adoption of AMCM 290 FLX, the next-generation laser powder bed fusion system capable of handling challenging materials such as copper. The AMCM 290 FLX is a customized EOS M 290 machine equipped with the most advanced nLIGHT beam shaping laser technology, high-temperature processing capabilities, and excellent oxygen control. This system enables enterprises to obtain the latest technologies and research results as early as possible and easily.

Professor Arun Arjunan, Director of ECMS and Engineering Innovation and Research at the University of Wolverhampton, said, "The establishment of the UK Centre for Excellence in Copper Additive Manufacturing marks an important milestone in the field of additive manufacturing, laying the foundation for innovation, sustainable development, and responsible manufacturing in the new era. Future projects will explore the integration of laser processing data, machine learning, and artificial intelligence technology to achieve efficient material and laser processing development."

EOS UK Sales Manager Nathan Rawlings added, "The UK manufacturing industry has always driven and embraced innovation. Additive manufacturing using materials such as copper brings huge benefits to product designers, but may require high demands from manufacturers. This new center of excellence will create and test processes that can reliably and consistently achieve material benefits in the manufacturing of components in the real world."

Source: Laser Net

Related Recommendations

  • Accelerating electrons by emitting laser light into a nanophotonic cavity

    The laser driven particle accelerator on silicon chips was created by two independent research groups. With further improvements, this dielectric laser accelerator can be used in medicine and industry, and even in high-energy particle physics experiments.Accelerating electrons to high energy is usually accomplished over long distances in large and expensive facilities. For example, the electron ac...

    2023-10-28
    See translation

  • Scientists demonstrate a new optical neural network training method that can crush electronic microprocessors

    The current deep neural network system (such as ChatGPT) can quickly improve energy efficiency by 100 times in training, and "future improvements will greatly increase by several orders of magnitude. Scientists from MIT and other institutions have demonstrated a new optical neural network training method that can crush state-of-the-art electronic microprocessors.Moreover, the computational density...

    2023-09-27
    See translation

  • By 2030, the global market size of medical laser fiber will reach 1.369 billion US dollars

    According to a recent report by Congic Business Intelligence, the global medical laser fiber market is expected to grow significantly at a compound annual growth rate of 6.9% from 2023 to 2030. This growth is attributed to the increasing popularity of minimally invasive surgery worldwide.The medical laser fiber market is expected to expand strongly, reaching $1.369 billion by 2030. The market is v...

    2023-10-27
    See translation

  • Is CTC technology in the booming new energy industry likely to disrupt the fiber laser industry?

    Recently, the term CTC technology has become a hot topic in the new energy vehicle industry. During the relatively slow period of electrochemical innovation, this structural innovation effectively helped the new energy industry reduce costs and increase efficiency, while also increasing the range of new energy vehicles to a certain extent. However, recently the author learned that the concept of C...

    2023-09-18
    See translation

  • Researchers propose NeuFlow: an efficient optical flow architecture that can solve high-precision and computational cost issues

    Real time and high-precision optical flow estimation is crucial for analyzing dynamic scenes in computer vision. Although traditional methods are fundamental, they often encounter issues with computation and accuracy, especially when executed on edge devices. The emergence of deep learning has driven the development of this field, providing higher accuracy, but at the cost of sacrificing computati...

    2024-03-23
    See translation