Enhancing Robotic Steel Prefabrication with Semantic Digital Twins

This technical report focuses on the enhancement of robotic steel prefabrication through the development of a semantic digital twin (DT) driven by established industry standards. The objective is to increase automation in steel construction by addressing the challenges posed by manufacturing tolerances. The paper outlines the creation of an ontology based on the DSTV-NC standard, which facilitates the integration of process data, tolerances, and deviations. A case study is presented to demonstrate the feasibility of this approach, showcasing how the semantic DT can link robot control, feedback data, and measured tolerances specifically for robotic plasma cutting. The results indicate that the proposed data model enables the realization of a semantic DT that provides valuable information for downstream manufacturing, assembly, and construction processes. The report highlights the need for adaptive information models in steel construction to improve the robustness and efficiency of robotic applications.