Daniel Hutzschenreuter, Clifford Brown, Wafa El Jaoua, Moritz Gafert, David Urban
Digital Metrological Expert – design of a software for automated key comparison data analysis in a digital world

Key and supplementary comparisons are a core component of the Mutual Recognition Arrangement. Digitalisation of data processing steps has the potential to reduce workloads of metrologists and to improve consistency of outcomes. The Digital Metrological Expert is an open-source software tool for automating the comparison data analysis and report creation. It is designed for use by metrology experts and for an integration into end-to-end digital workflows for machines. Automation is supported by applying FAIR principles for machine-actionable data and APIs that are based on the SI. The tool can also utilise digital standards from the quality infrastructure such as Digital Calibration Certificates and Smart Standards to fulfil its work.

Fatemeh Khalesi, Ioan Tudosa, Francesco Picariello, Arman Neyestani, Sergio Rapuano
Quantum Channel Characterization in QKD: A Metrological Perspective

Quantum Key Distribution (QKD) offers secure communication by leveraging core principles of quantum mechanics. Characterization of QKD system is fundamental for comparing the experimental results provided by researchers. Unfortunately, there is no standardized or unified approach; therefore, different researchers present results that provide heterogeneous information, making comparisons difficult. A systematic analysis of the literature is necessary to identify common approaches from a metrological perspective. This paper provides an overview of measurements used to characterize quantum channels, with a focus on parameters such as attenuation, polarization effects, and timing stability. To support this analysis, real-world case studies are examined.

Anamaria Hariton, Cristian Zet, Cristian Foşalău
Automatic Method of Assessment and Grading of Students in a Measurement Laboratory

High activity levels in measurement laboratories can often exceed the time allocated for individual laboratory sessions. These laboratories involve a wide range of measurement tasks—from simple to complex—while students operate under strict time constraints. Consequently, the manual evaluation of student performance by instructors becomes labor-intensive and time-consuming. The digitization of the assessment process offers an effective solution. This paper presents a method that integrates LabVIEW with an SQL database to automatically record, verify, and grade student performance in laboratory sessions. The proposed method includes automated data saving for each student, validation of measurement accuracy, and objective grading mechanisms. Various tools are employed for real-time data acquisition, verification, and automatic evaluation of student activities.

Dong-Hun Ryu, Chae-Wook Lim
Development and Application Study of a Calibration Certificate Anomaly Detection System

This study focuses on the development of a system to effectively extract and utilize data from approximately 3,000 types of unstructured calibration certificates (e.g., paper, PDFs) widely used in the calibration industry. To process document-based data that are difficult for machines to recognize, the Korea Testing Laboratory (KTL) has developed a calibration certificate anomaly detection system called K-Argos, which applies object detection AI technology based on Convolutional Neural Networks (CNNs). The core function of the system is to extract data from unstructured documents, convert them into structured data, and standardize and store the results. Using the converted structured data, K-Argos provides statistical data management features such as performance analysis of calibrated equipment and anomaly detection in calibration data. Additionally, the system can be used to correct inaccurate identification information (e.g., manufacturer, model, serial number) and to analyze errors within the calibration data. In the future, the K-Argos system will be expanded to include an online technical supervisor service that automatically determines anomalies in data during the certificate approval stage and provides relevant information to the approver (technical supervisor). This is expected to significantly improve the efficiency and reliability of calibration tasks and contribute to the digital transformation of the calibration industry through the implementation of Digital Calibration Certificates (DCCs).

Tuukka Mustapää
Transition to DCC-based calibration management: findings from proof-of-concept investigations

The introduction of standardized data formats for measurement and calibration data such as the digital calibration certificate (DCC) will enable further automation of calibration-related processes. This will open new possibilities for optimization of calibration processes in industrial applications. This paper describes some of the challenges and possibilities related to the transition to DCC-based calibration processes and management in the process industry. The findings presented are based on case examples and proof-of-concept projects from the process industry, in which automation of a calibration process is pursued using a combination of systems from multiple providers. The investigations and findings also suggest that parts of the DCC data structure could potentially be beneficial also for other applications, in which exchanging of calibration data is needed, but system integration is otherwise challenging due to lack of a suitable harmonized data structure.