SASO Uncertainty Machine - Advanced Pythonic ML Algorithm for Estimating Uncertainty in General Calibration Services at Saudi Standards, Metrology, and Quality Organization-SASO-KSA |
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| Saad A. Bin Qoud, Fahad A. AlMuhlaki, Rayan A. AlYousefi, I. AlFaleh, N. Qahtani, Lama M. AlBugami, Rawan A. AlMutairi, Khaled G. AlGhizzi, Raed H. AlShabatat, A. El-Matarawey |
- Abstract:
- The missions of the National Metrology Calibration Centre (NMCC) at the Saudi Standards, Metrology, and Quality Organization (SASO), as a national metrology institute, are to maintain, disseminate, develop, and realize the International SI units. Among the services offered by the laboratories is routine calibration, covering nearly all fields and sectors such as industrial, medical, and environmental applications. This work aims to digitize a web-based software application to evaluate the measurement uncertainty associated with a measured quantity for all types of model functions (linear, non-linear, polynomial, logarithmic, etc.) relevant to calibration, testing, accreditation, verification, and validation services. A Python-based machine learning algorithm was developed in accordance with the requirements of JGCM-100 to provide the user with a comprehensive report on the experiment and measurement uncertainty in three main steps. The validation of the automated algorithm was carried out on five examples from the JGCM standard, showing complete numerical agreement. This article provides an open-source, step-by-step algorithm as part of the global digital transformation trend in metrology.
- Download:
- IMEKO-TC6-2025-049.pdf
- DOI:
- 10.21014/tc6-2025.049
- Event details
- IMEKO TC:
- TC6
- Event name:
- TC6 M4Dconf2025
- Title:
2025 IMEKO TC-6 International Conference on Metrology and Digital Transformation
- Place:
- Benevento, ITALY
- Time:
- 03 September 2025 - 05 September 2025