Quality Assurance in the Calibration of Platinum Resistance Thermometers (Pt-100) at NIS

Abstract Ensuring the quality and accuracy of measurements is a critical aspect of the calibration process. One of the major challenges that calibration laboratories face is limited participation in international or bilateral comparisons and proficiency testing. This research aims to identify potential deviations or weaknesses in the measurement and calibration processes by implementing both scientific and practical methods to enhance measurement quality. A Python-based automation program was developed to detect deviations from acceptable tolerance limits in real-time during calibration. The proposed methodology was applied to the calibration of a platinum resistance thermometer (Pt-100) at the Thermal Measurements Laboratory of the National Institute for Standards (NIS), Egypt. The experiment demonstrated successful implementation: when measurements exceeded predefined tolerance limits, the Python program triggered an alert to halt the calibration and initiate error diagnostics. Calibration was conducted at 70 °C, 150 °C, and 200 °C, with quality assurance procedures specifically applied to the 70 °C point as a case study. This methodology provides a replicable model for laboratories aiming to integrate conventional quality control (QC) with automated monitoring. The integration of statistical process control (SPC) and automation enhances reliability, minimizes human error, and offers a replicable framework for strengthening quality assurance in calibration laboratories.