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Fraunhofer IAPT

R&D Institution

www.iapt.fraunhofer.de/Hamburg, Germany

About

The Fraunhofer Institute for Additive Production Technologies (IAPT) in Hamburg is one of the leading institutions for the industrialization of Additive Manufacturing. We focus primarily on socially relevant sectors such as Life Sciences, Energy, Mobility and Security. Our research ranges from component design and processes to factory planning and digitalization: we look at the entire production route. Numerous spin-offs and patent applications underline the value of our innovations. You too can develop the additive manufacturing of the future together with industry and public institutions.

Additive Manufacturing is considered a digital manufacturing technology, but there are still many open challenges on the way to full industrialization. That is why we are working closely with industry to develop real-time and data-driven digital twin technologies for the digital additive production of tomorrow.

Other enabling technologies

Manufacturing and machine learning, e.g., to increase the flexibility of industrial processes, modular approaches, reduce use of materials, quality assurance and certification of products)Robotic / handling - and assistance systems(Advanced) Materials and additive manufacturingLife cycle assessment / Product life cycle management – e.g., Digital Twin / Digital Product Passport

Data technologies, data ecosystems and cross-linking

(AI based) recognition systems (e.g. image recognition) to evaluate materials, components and products and determine the best use paths(AI based) process and system control technologies(AI based) Material and Product Design, Decomposition and SeparationDesign of an adaptable Digital Product Pass

Representatives

Lennart Waalkes

Team Lead Sinter AM

Fraunhofer IAPT

Marketplace (1)

  • Expertise

    Increasing Material Efficiency in Sinter-based Additive Manufacturing

    Enhancing material efficiency in sinter-based additive manufacturing using in-house-developed 3D printers and deep learning.

    • Industry 4.0 technologies
    • AI-driven diagnostic systems
    • Manufacturing and machine learning
    • (Advanced) Materials and additive manufacturing
    • (AI based) process and system control technologies
    Author

    Lennart Waalkes

    Team Lead Sinter AM at Fraunhofer IAPT

    Hamburg, Germany