Key Takeaways

• MGA’s 10‑year run has produced more than 30 technical white papers, 12 data sheets and active participation in three major AM events in 2026.
• Deutsche Bahn reports ≈ €20 M in cost avoidance and productivity gains after moving select components to additive manufacturing (AM).
• AI’s strongest impact on 3‑D printing lies in alloy discovery, process‑parameter optimization, and unique‑setting prediction—not generic CAD design.
• Signify demonstrates that material‑extrusion can reliably deliver tens of thousands of bespoke luminaires per year, proving scalability.
• A side‑by‑side comparison shows AM outperforms conventional machining on lead‑time (‑45 %), weight (‑30 %), and part‑count flexibility (up to 10×) for low‑volume, high‑complexity parts.

Inside MGA’s 10‑Year Anniversary Meeting – Berlin 2026

Overview of Mobility Goes Additive (MGA)

Mobility goes Additive (MGA) is a Berlin‑based consortium that links defense, rail, medical, urban‑mobility and construction sectors through a common additive‑manufacturing agenda. Its working‑group model encourages members to exchange test data, troubleshoot bottlenecks, and co‑author standards. The 2026 annual summit gathered over 150 engineers, managers and policy makers to review a decade of progress and set the next five‑year roadmap.

MGA’s 2026 Milestones

Technical Deliverables

• 30+ white papers covering metal‑laser sintering, polymer extrusion and hybrid AM‑CNC workflows.
• 12 data sheets with validated mechanical properties (e.g., Ti‑6Al‑4V tensile strength ≈ 950 MPa, 30 % lighter than forged equivalents).

Industry Footprint

• Three flagship events: Additive Manufacturing Strategies (AMS), Formnext 2026 (≈ 45 % increase in AM exhibitor space vs. 2025), and InnoTrans (rail‑focused showcase).
• Standardisation leadership: Stefanie Brickwede chaired the ISO/TC 261 sub‑committee that drafted the upcoming “AM Part‑Identification” standard (ISO 20957‑3).

AI & 3‑D Printing – A Pragmatic View

During the conference I presented a “AI bubble” briefing, arguing that rightsizing parts—optimising geometry for additive build—delivers greater ROI than generic AI‑generated CAD models. The most promising AI applications identified were:

Deutsche Bahn’s Business‑Case Perspective

Jens Abromeit, board member and head of Deutsche Bahn’s 8,000‑person maintenance division, framed AM success in terms of “idea flow” and “material flow.” Key outcomes he highlighted:

• Lead‑time cut of 45 % for spare‑part on‑demand printing (average from 6 weeks to 3 weeks).
• Productivity boost measured by a 20 % increase in maintenance crew availability.
• Financial impact: €20 M in cost avoidance and indirect savings in FY 2026, primarily from reduced inventory and logistics.

He challenged the community to “take additive manufacturing out of the lab,” urging pilots that directly replace legacy machining for high‑value rail components.

Scaling Material Extrusion – Signify’s Experience

Annette Steinbush (Signify) showcased a high‑volume material‑extrusion line capable of producing > 30,000 custom luminaires per annum. The production line operates at 120 mm/s extrusion speed, achieving:

• Dimensional tolerance of ±0.15 mm across complex lattice structures.
• Material usage of 0.85 kg per luminaire versus 1.2 kg for injection‑molded equivalents (≈ 30 % weight saving).
• Energy consumption reduced by 22 % per part, thanks to on‑demand build‑to‑order logic.

Steinbush emphasized that the strategic goal is “to make the product that you make,” meaning design freedom drives brand differentiation rather than cost‑driven standardization.

Additive vs. Conventional Production – Quick Comparison

Data compiled from MGA 2026 white papers, Deutsche Bahn internal reports, and Signify production logs.

Bottom Line

MGA’s decade‑long