Advancing Digital Metrology with EURAMET:
SE “Ukrmetrteststandart” Develops AI-Assisted Approaches to Metrological Documentation
As part of its digital transformation programme, SE “Ukrmetrteststandart” is advancing an internal research initiative focused on the structured processing and AI-assisted translation of normative and scientific metrological documentation. The aim is to support reliable digital workflows while preserving the integrity of metrological information.
A central challenge in this field is that AI-assisted translation, while improving access and efficiency, may introduce subtle structural inconsistencies in formulas, measurement units, uncertainty expressions, and metrological traceability requirements - all of which are critical to technical reliability.
In a proof-of-concept study, domain-specific structural constraints were shown to improve translation consistency under low-data conditions. These constraints were implemented through carefully designed corpora and controlled fine-tuning protocols intended to preserve essential technical invariants.
A subsequent experimental phase introduced a structured diagnostic corpus to examine how models respond to technically complex and potentially conflicting information under different training configurations. The results suggest that model behaviour is sensitive to corpus structure and fine-tuning parameters, producing measurable differences in representation-level stability while largely preserving core structural invariants.
“Digitalisation in metrology must reinforce, rather than compromise, the principles of traceability and technical accuracy. Our work focuses on developing structured validation mechanisms that increase confidence in AI-assisted processes within precision measurement science.”
PhD Yurii KUZMENKO, Deputy Director General for Metrology, CIML Member for Ukraine
This initiative contributes to the robustness of Ukraine’s national metrology infrastructure and aligns with broader European efforts to promote trustworthy and reliable digital technologies in high-stakes technical domains.