Intervalos de recalibración para equipos de medición con dos o más certificados de calibración
Recalibration Intervals for Measuring Equipment with Two or More Calibration Certificates
Abstract (en)
The calibration of measuring equipment is crucial to ensure accuracy and reliability in test laboratory results. This study describes a systematic approach to establish recalibration intervals in the laboratories of the Aquatic Resources Research Center (CIRA) at UNAN-Managua, based on drift decision analysis to improve measurement quality. Lack of accuracy in measurement systems can affect data quality and lead to incorrect decisions.
To address this research, the ILAC-G24/OIML D10:2022 Guide was used, which provides guidelines for the calibration and recalibration of equipment, complemented by an Excel spreadsheet to facilitate data entry and statistical analysis, allowing the estimation of equipment drifts. Measurement error data from calibration certificates were employed, ensuring traceability to the International System of Units (SI). This approach safeguards the integrity and validity of measurements, strengthening the capacity of laboratories to carry out accurate and reliable testing.
The study includes the identification of procedures and the development of equations to implement the calibration system. The proposed approach seeks for laboratories not only to comply with international quality standards, but also to enhance the quality of testing and their role in research, thereby contributing to continuous improvement in the management of measurement data.
Abstract (es)
La calibración de equipos de medición es crucial para asegurar la precisión y confiabilidad de los resultados en los laboratorios de ensayo. Este estudio describe una sistemática para establecer intervalos de recalibración en los laboratorios del Centro de Investigación de Recursos Acuáticos (CIRA) de la UNAN-Managua, basada en el análisis de decisión por deriva, con el fin de mejorar la calidad de las mediciones. La falta de precisión en los sistemas de medición puede afectar la calidad de los datos y conducir a decisiones incorrectas.
Para abordar esta investigación se utilizó la Guía ILAC-G24/OIML D10:2022, que ofrece directrices para la calibración y recalibración de equipos, complementada con una hoja de cálculo en Excel para facilitar el ingreso de datos y el análisis estadístico, permitiendo estimar las derivas de los equipos calibrados. Se emplearon datos de errores de medición obtenidos de certificados de calibración, asegurando la trazabilidad al Sistema Internacional de Unidades (SI). Este enfoque protege la integridad y validez de las mediciones, fortaleciendo la capacidad de los laboratorios para realizar ensayos precisos y confiables.
El estudio incluye la identificación de procedimientos y el desarrollo de ecuaciones para implementar el sistema de calibración. La sistemática propuesta busca que los laboratorios no solo cumplan con normas internacionales de calidad, sino que también eleven la calidad de los ensayos y fortalezcan su rol en la investigación, contribuyendo así a la mejora continua en el manejo de datos de medición.
References
Corning Mexicana, S. A. de C. V. (2020, noviembre). Quality management report. Miguel Flores.
Ellison, S. L. R. y Williams, A. (Eds.). (2019). Metrological traceability in analytical measurement (2nd ed.). Eurachem/CITAC.
EURAMET. (2015). Guidelines on the calibration of non-automatic weighing instruments (EURAMET/cg18/v02). European Association of National Metrology Institutes (EURAMET).
ILAC y OIML. (2022). Guidelines for the determination of calibration intervals of measuring instruments (ILAC-G24:2022/OIML D 10:2022). International Laboratory Accreditation Cooperation (ILAC) & International Organization of Legal Metrology (OIML).
National Institute of Standards and Technology. (2019). Good measurement practice for assignment and adjustment of calibration intervals for laboratory standards (GMP 11:2019). NIST.
Organismo Nacional de Acreditación. (2024). Política sobre incertidumbre de la calibración (DOC-ONA-17-020). ONA.
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