Unlock the Power of Data in Additive Manufacturing

In today’s fast-evolving manufacturing landscape, additive manufacturing (AM) stands out as one of the most promising technologies. Instead of subtracting material from a larger whole, AM builds physical parts layer by layer from a digital design. This shift not only opens the door to complex, custom-made components, but it also creates a wealth of valuable data along the entire production chain.

From the initial design to the final quality check, every step of the additive manufacturing process generates information: machine configurations, sensor readings, process settings, material usage, and quality outcomes. This data holds immense potential—for improving quality, enabling traceability, and building a "digital passport" for every produced item.

And yet, most of this data goes unused. It may contain confidential information hence be siloed, lost, or only partially available for analysis. This makes it difficult to trace defects, optimize processes, or share reliable information with partners and customers. A solution exists: The knowledge graph allows to put structure into the data and reveal relationships. Combined with a secure platform, this enables smooth data sharing and interpretation for process improvement and decision-making.

The Knowledge Graph for additive manufacturing

A knowledge graph is a way to structure and connect data in a meaningful way. Think of it as a map that links different parts of your production process - machines, materials, parameters, and people - so you can see not just the data itself, but the relationships between them.

We use a technology called RDF (Resource Description Framework) to build these graphs. RDF expresses data in triples: subject, predicate, object. For example: "Part456 is manufactured by SLM Process." and "Part456 uses material Ti6Al4V." 

These simple links allow us to build a rich, flexible, and searchable web of information. Combined with query languages like SPARQL, the knowledge graph becomes a powerful tool to:

• Monitor process configurations
• Track experiment details and quality results
• Compare runs and test outcomes
• Ensure full traceability across the production cycle

This kind of structure helps manufacturers make data-driven decisions faster and more confidently.

In the additive manufacturing setup comprehensive records are logged in the Knowledge Graph that support traceability and analysis:

• Machine settings and sensor configurations for each build
• Experiment parameters and conditions

Additionally, quality results derived from sensor data and AI algorithms are added to the graph. This way, all quality-related information for every individual experiment can be linked directly to the conditions under which it was produced.

All of this is integrated in one cohesive system, making it easy to compare experiments, spot issues, and optimize processes.

Secure and energy-efficient data sharing through TANGO

The knowledge graph facilitates in-depth analysis and decision-making, relevant to both internal and external customers. But how do we go about sharing this data with customers, partners, or regulatory bodies? Security and guaranteeing data integrity is of crucial importance.

This is why we’ve assisted in TANGO - funded by the European Union - for the development an innovative platform for secure and energy-efficient data sharing.

The Tango Platform ensures companies can:

• Share data while protecting confidentiality
• Keep control over who sees what
• Use AI tools like explainable models and federated learning without compromising trust

The platform includes smart building blocks like Self-Sovereign Identity (SSI) and Policy Enforcement Points (PEP), all working together using data space technology to ensure smooth, secure, and trustworthy interactions.

We’re proud to be a pilot provider in the TANGO project, testing and validating these technologies with a focus on: advanced AI methods, efficient encryption techniques and the seamless onboarding and usability for manufacturers.

TANGO driving innovation

Additive manufacturing offers much more than design freedom—it opens up new ways of thinking about data, quality, and collaboration. With the help of knowledge graphs and a secure platform like TANGO, manufacturers can unlock this potential: improving traceability, enabling smarter AI applications, and ensuring safe, structured data sharing across the value chain.

Technologies

Manufacturing, Mechanical Components and Systems

Optimising mechanical components and systems, their performance, sustainability and manufacturing process.