In this talk, we present a novel design-to-production workflow that leverages generative AI to enable mass customization without compromising efficiency. Using the example of custom pendant lamps for interior spaces, we show how users can define product parameters such as geometry, texture, and surface finish through intuitive AI interfaces. Design concepts are generated in real time and automatically translated into manufacturable 3D models suitable for advanced AM processes like DED or PBF-LB/M.
We outline the technical architecture behind the pipeline—including AI-powered image analysis, geometry parametrization, and design automation—and demonstrate how robust manufacturability constraints are integrated early in the design loop. The result is a fully automated system capable of delivering unique, production-ready metal parts with high aesthetic and functional quality.
By combining the flexibility of AM with the creativity and speed of AI, we aim to shift the paradigm from ""design for the masses"" to ""design for the individual""—scalable, sustainable, and smart.
Speakers:
Maximilian Voshage, Chief Engineer, ACAM GmbH
Florian Fischer, Research Associate, RWTH Aachen Univ. - Digital Additive Production
Johannes Wilkomm, Research Associate, RWTH Aachen Univ. - Digital Additive Production