Semantic modeling of additive manufacturing processes of metal structures

Subproject to the joint research project "ODE_AM" ("Ontologies for decentralized capturing multi-scale static and cyclic parameters of additively manufactured steel structures from experiment and simulation")


Processes and techniques in additive manufacturing become increasingly heterogeneous and the material parameters more and more complex. Providing a solid foundation for additive manufacturing requires a sustainable transformation of today's materials science into an Industry 4.0-driven, digital and multidisciplinary field of research and development. The joint research project “ODE_AM” aims to support additive manufacturing of metal structures (Figure 1) through innovative digital methods, concepts, and processes.

Project goals and scientific approach

The goal of this subproject is to develop a cross-scale and cross-domain ontology as a vehicle introduced to render additive manufacturing techniques and processes of metal structures more robust and efficient (Figure 2). Emphasis will be put on conceptual modeling of information related to the manufacturing process, such as process control parameters, material information, and geometric information, entailing an "information model for additive manufacturing". The information model will be designed according to the standards of the MaterialDigital digitalization platform to ensure smooth integration into the platform. In addition, the information model will reflect the variance of parameters known from additive manufacturing practice, enabling a direct integration of probabilistic methods, such as Bayesian updating. As compared to traditional modeling strategies, a distinct advantage is expected in the robust mathematical representation of the underlying information, thus the formal optimizability and systematization of the manufacturing processes and techniques. Finally, this subproject, integrating data and information stemming from the other subprojects, provides an interface to the MaterialDigital digitalization platform, which will be accessed via a client-server architecture to be developed in this subproject.

Project partners

  • Material Research and Testing Institute, Weimar, Germany
  • Ilmenau University of Technology, Ilmenau, Germany
  • Fraunhofer Institute for Casting, Composite and Processing Technology (IGCV), Augsburg, Germany


Professor Dr. Kay Smarsly
Hamburg University of Technology
Institute of Digital and Autonomous Construction
Blohmstraße 15
21079 Hamburg
Email: kay.smarsly(at)tuhh(dot)de