Spoke 6

Additive Manufacturing as disruptive enabler of the Twin Transition

Spoke 6

Additive Manufacturing as disruptive enabler of the Twin Transition

Ambition: Additive Manufacturing (AM) in principle represents the only viable solution to realize a new generation of green and circular products (lightweight, energy efficient, extended-lifetime products), adopting green and sustainable materials with a new generation of zero-waste processes. Spoke 6 ambition is to revolutionize AM as a disrupting enabling technology of the twin transition!

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Objectives

  • Highly customized, sustainable, and smart products to support the future of AM through the development of new design approaches that can design complexity for green.
  • Low-impact products throughout their lifecycle through the development of innovative materials specifically designed for AM.
  • Zero-waste smart AM through the development of innovative manufacturing platforms highly-sensorised and augmented with AI and big data mining to achieve in-situ, in-line monitoring, adaptive control, and self-healing capabilities for first-time-right manufacturing.

Main activities

01

Integration of all stages in the AM process chain to speed up the scientific and industrial takeoff of Italy as a leading country in the international panorama of AM.​

02

Development of novel solutions to design for AM.

Development of new alloys and novel materials with reduced environmental impact during lifecycle.

03

Introduction of a new generation of sustainable AM technologies, processes, and systems.

Other Spokes

Digital Advanced Design: technologies, processes, and tools
Eco-Design strategies: from materials to Product Service Systems – PSS
Green and sustainable products & materials from non-critical & secondary raw sources
Smart and sustainable materials for circular and augmented industrial products and processes
Closed-loop, sustainable, inclusive factories and processes
New and consumer-driven business models for resilient and circular supply chains
Digitally-oriented factory design and management through AI and data driven approaches