Smart Data Drives 3D Printing Innovation in 2022

3D printing is reshaping factory floors, enabling large‑scale production across multiple sites. Historically isolated from traditional manufacturing, additive processes are now converging with conventional workflows, creating a unified, digitally‑centric production ecosystem.

This integrated environment delivers greater efficiency, repeatability, scale and control, but it hinges on a single resource: data. As additive manufacturing (AM) evolves, the importance of data will only grow.

In a recent round‑table, leading experts from Materialise examined how smart data is reshaping AM and the evolving role of human expertise.

The increasing relevance of smart data will play a crucial role in additive manufacturing in 2022.

How relevant is data in AM?

We refer to 3D printing as "smart manufacturing", a term that originates from conventional production. AM is inherently more complex because material and product are created simultaneously, making data even more critical.

Smart data is the linchpin for scaling industrial 3D printing. By reducing scrap, predicting failures before they occur, and meeting stringent quality standards, manufacturers can unlock true production potential. – Tim Van den Bogaert, Sr. Market Director, Materialise Software

Collecting data is only the first step. Turning it into actionable insights is what transforms a plant into a smart factory, enabling continuous improvement, scalability and superior products.

A customer recently said, "We believe in a world where the next part we print is always a better version of the previous part." This vision requires a software platform that connects every system and dataset across the production environment.

Pieter Slagmolen, Innovation Manager for Medical, Materialise, notes that medical AM must differentiate between "smart data" for scaling complex devices and "patient data" that enhances treatment but raises privacy concerns.

Kristel Van den Bergh, Director of Innovation, Materialise Mindware, adds that distributed, cloud‑based manufacturing amplifies concerns about protecting proprietary designs and prototypes.

Who owns the data in AM?

The question "Who owns the data?" is old, but Peter Leys, Executive Chairman, argues the real issue is ownership of designs and processes. These assets give manufacturers the power to innovate.

Most manufacturers claim and control their designs and processes, sharing insights selectively to empower the industry while safeguarding competitive advantage. – Peter Leys, Materialise

Bart Van der Schueren, CTO, suggests anonymizing data to build confidence, fostering collaboration without exposing trade secrets.

In industrial settings, data ownership comes with responsibility. As production shifts from centralized to distributed, new conversations around liability and legal frameworks are emerging.

For medical AM, hospitals and device manufacturers control process data for quality assurance, while patient data ownership remains debated. Optimal care demands access to patient data, regardless of ownership.

Experts from Materialise discuss smart data ownership and its impact on human expertise in AM.

Will human expertise still be important in AM?

Smart data optimizes workflows, potentially reducing manual intervention. Yet, creating better processes still requires human expertise.

Kristel Van den Bergh notes that in predictable, data‑rich contexts, machines dominate and humans supervise. In contrast, innovation demands creativity, imagination and intuition—human traits that automation cannot replicate.

Even with abundant data, domain knowledge is essential before automation can be justified; otherwise, automation may lock in a flawed process.

Peter Leys sees new opportunities: "Smart manufacturing based on data also creates an opportunity for smart people to make a difference." He cites medical surgeons using experience to add intelligence to patient treatment, and AM firms adding personal insight for competitive advantage.

The third ingredient

Van den Bergh emphasizes that breakthrough innovation arises from connecting seemingly unrelated ideas—something humans excel at. While computers process connections faster, the human brain creates novel associations that data alone cannot reveal.

To answer the central question: will more smart data replace human expertise? No. Companies must invest in both machine intelligence and human expertise, and develop processes that integrate the two effectively.

Conclusion

Smart data is poised to become a cornerstone of 3D printing. Success hinges on data ownership, control, and the ability to translate data into actionable insights.

As data drives smarter, automated manufacturing, human engineers will focus on defining and fine‑tuning unique processes. The future challenge lies in establishing workflows where machine intelligence and human expertise amplify one another throughout the 3D printing journey.