AI as a Lever for Quality Assurance in Additive Manufacturing

Experts from the Fraunhofer IAPT will present the current state of artificial intelligence, machine vision, and learning systems for cost-effective quality assurance in additive manufacturing during an online session on October 16, 2025.

Hamburg-Bergedorf, September 17, 2025. The Fraunhofer IAPT is researching the industrial application of additive manufacturing. The perspective across the entire additive process chain considers both the economic viability and the quality of components. The virtualization of all production phases provides a particularly effective lever. It connects previously fragmented data, addresses scaling challenges, and automates manual processes.

Online Session on the Application and Economics of AI in Quality Assurance

On October 16, 2025, experts from the Fraunhofer IAPT will showcase research findings from the field of virtualization in an online session. The session will illustrate the benefits of digital twins, artificial intelligence (AI), and learning systems for additive manufacturing through selected application areas. Specific use cases will demonstrate how AI paves the way for new approaches to quality assurance.

The focus is on accelerating and automating quality management, for example through shop-floor solutions for production and operations managers, as well as QA and inspection teams. A case study from the industry will also highlight the cost-effectiveness of AI solutions in additive manufacturing.

Key Data and Participation

The online session titled »How Does AI Fuel New Approaches to QA for Additive Manufacturing?« will start on October 16, 2025, at 2 PM. It will be conducted in English and is aimed at executives from production, AM, and quality management, as well as engineers, data scientists, experts in digitalization in manufacturing, or development teams.

Interested participants can find more information about the webinar and registration on the website for the online session. Participation is free of charge.

Fraunhofer IAPT Deep Dive The_Impact_of_AI-tools_on_AM_Design

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