Quality Control and Structural Reliability -- A Unified Framework for Integrating Conformity Assessment and Partial Safety Factors

Abstract

Ensuring structural reliability remains a core concern in civil engineering, yet the quantitative effects of quality control measures on material variability and safety margins are not fully understood, especially for materials other than reinforced concrete. This study addresses this gap by presenting a probabilistic framework that integrates Bayesian updating, acceptance sampling, and operating characteristic (OC) curves to model conformity assessment as a probabilistic filter. In doing so, it refines prior distributions of key material and execution parameters based on quality control outcomes, linking reductions in the coefficient of variation directly to adjustments in partial safety factors. Applying the framework to a masonry wall example demonstrates how systematic quality control efforts, particularly those targeting parameters with higher importance such as masonry unit strength and execution quality-produce substantial gains in structural reliability. The analysis shows that combined quality control measures can lower the partial safety factor from a baseline of 1.5 to about 1.38, corresponding to an improvement factor of roughly 1.09 and material savings of approximately 8%. Conversely, controlling parameters with negligible influence, such as mortar properties, provides limited benefit. These findings encourage focusing quality control resources on the most influential parameters and integrating results into semi-probabilistic design methods. By offering a transparent, standards-compatible approach, the framework supports the refinement of design guidelines, promotes more efficient resource allocation, and enhances overall structural safety in the built environment.