The methodology of selective quality control of rebar products

Introduction. The quality of rolled reinforcement is a key factor in the reliability of reinforced concrete structures in conditions of increasing number of floors and complexity of construction projects. Modern Russian standards (State Standard 34028-2016, State Standard R 52544-2006) require strict statistical control of the mechanical properties of rolled products, including temporary resistance, yield strength and relative elongation. The relevance of the study is due to the need to improve the accuracy of sampling methods in order to minimize the risks of an unreliable quality assessment. Aim. Development of a methodology for selective quality control of rebar products based on statistical analysis, including verification of the normality of data distribution, elimination of outliers and assessment of compliance with the requirements of standards. Materials and methods. The study is based on the analysis of test data for rebar rolled products of class A600 (State Standard 34028-2016). The Shapiro–Wilk, Pearson (χ2), and Kolmogorov–Smirnov criteria were applied to verify the normality of the distribution. Outliers were identified by the Charlier method (α = 0.05). Software tools were used to calculate statistical indicators (mean, RMSD, skewness, excess) and visualization (histograms, Q–Q graphs). Results. It was found that the presence of outliers distorts the distribution of key parameters. For the ratio of temporary resistance to yield strength, the exclusion of emissions allowed the normality of the distribution to be restored (p > 0.05 according to two criteria), whereas for the relative elongation δmax, their effect turned out to be insignificant. Automated analysis has confirmed that the use of confidence intervals (95 %) and State Standard 34028-2016 methods increases the reliability of quality assessment. Conclusions. Eliminating of outliers is a critical step to ensure the normality of data distribution. The combined use of agreement criteria increases the reliability of statistical conclusions. Automation of the methodology based on specialized software reduces the monitoring time and minimizes the human factor. Regular sampling is necessary to ensure that products meet the requirements of the standards and reduce risks in construction.