Integration of Quality Management and Metrological Assurance Systems in Food Manufacturing Enterprises: A Methodological Framework
Keywords:
Quality Management, Metrological Assurance, Measurement Uncertainty, Food Safety, ISO 22000, ISO 10012, Conformity AssessmentAbstract
This study aims to develop and demonstrate a methodological framework that integrates quality management systems (QMS) and food safety management systems with metrological assurance in food manufacturing enterprises. It addresses the weak link between measurement quality and the decisions on product conformity and process control that rely on it. The framework was built through a structured analysis of international standards (ISO 9001, ISO 22000, ISO 10012, ISO/IEC 17025) and the relevant literature. It was operationalised through a process-based mapping of requirements, a Measurement Criticality Index (MCI) for risk-ranking measurement processes, and Monte Carlo simulation in accordance with JCGM 101 to quantify conformity-decision errors. The framework was demonstrated on a representative dairy production scenario with three critical measurands: pasteurization temperature, fill mass and yogurt pH. In the simulated scenario, reducing measurement uncertainty through risk-based metrological assurance lowered the MCI of the three measurands by 62.5–70.0%. False rejection of conforming product fell by 81.2–94.3%, and false acceptance of nonconforming product fell by 34.4–40.1%. The study links measurement uncertainty directly to QMS risk-based thinking through a quantitative, decision-oriented indicator, and it combines process mapping, risk ranking and uncertainty-based simulation in one reproducible framework. Food enterprises can use the framework to prioritise calibration resources, set calibration intervals and define decision rules. Regulators can use it as a basis for proportionate metrological requirements in food safety oversight. The results rely on simulated data and assumed severity scores. Validation through multi-plant empirical studies, including drift-based calibration-interval optimisation, is needed.
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