Interspectral to Lead Swedish Research Project Into AI-Powered Quality Assurance for Additive Manufacturing

Why It Matters

Embedding real‑time, secure AI quality checks into additive manufacturing will accelerate adoption in high‑risk industries, reducing scrap, improving safety and protecting intellectual property. The consortium’s federated‑learning approach offers a scalable blueprint for cross‑site collaboration without compromising data confidentiality.

Key Takeaways

• Interspectral leads AI model development for AM quality assurance.
• TRUSTAM uses federated learning to keep data on‑site.
• Consortium includes Saab, AMEXCI, Scaleout Systems, funded by Vinnova.
• Project runs to early 2028, delivering aerospace demonstrators.
• Integration will enhance Interspectral’s AM Explorer platform.

Pulse Analysis

The TRUSTAM initiative marks a pivotal step toward mainstreaming additive manufacturing (AM) in sectors where failure is not an option. By leveraging federated learning, the consortium sidesteps the traditional bottleneck of data centralization, allowing each production site to train AI models locally while sharing only anonymized updates. This architecture preserves proprietary designs and sensitive process parameters, addressing a core barrier that has slowed AM adoption in aerospace and defence. Industry observers note that such privacy‑preserving AI could become a de‑facto standard for high‑value manufacturing ecosystems.

Interspectral’s role as the technical lead focuses on embedding the federated AI engine directly into its AM Explorer platform. The platform already aggregates sensor streams from metal printers, lasers and post‑processing equipment, but the new on‑premise models will provide real‑time defect detection and process drift alerts tailored to each machine’s unique characteristics. By keeping raw data behind the firewall, manufacturers retain full IP ownership while still benefiting from collective intelligence across the consortium’s partners, including Saab’s aerospace expertise and Scaleout’s edge‑computing infrastructure.

The project’s timeline—culminating in early 2028 with live demonstrators—offers a clear runway for commercial rollout. Successful pilots in defense‑grade facilities will generate validated case studies, encouraging broader industry uptake and potentially influencing regulatory standards for AM part certification. As the consortium disseminates its findings, the broader AM community can expect open‑source frameworks and best‑practice guidelines that accelerate secure, AI‑enabled quality assurance across the global supply chain.