9. Product quality analysis using methods of statistical study of repair results

Annotation: The quality analysis of products is a crucial component of production management and reliability enhancement for manufactured or repaired items. Today, the growing complexity of technological processes and the expanding range of products necessitate eff ective quality control methods that ensure reliable assessment with minimal time and resource expenditure. One of the most eff ective tools for achieving this is statistical quality control. It enables informed decisions about product quality based on sample inspection results. This paper examines two approaches for evaluating the quality of repaired products: the single sampling method and the sequential analysis method. The single sampling method helps determine whether the entire batch meets the specifi ed quality criteria using a representative sample. This method involves calculating the optimal sample size and the acceptable number of defective items, taking into account the admissible risk levels for both the supplier and the customer. The principal advantage of this method lies in the simplicity of calculations and the ability to predict the probability of batch acceptance or rejection. The sequential analysis method developed by Wald off ers a more fl exible approach for large batches of products. It allows devising a control plan in the form of a graph divided into three regions: acceptance, rejection, and an intermediate zone where additional testing is required. This method reduces the number of necessary tests, saves resources, and ensures quality assessment with specifi ed reliability and risk levels. To accurately classify batches in the intermediate region, the truncation method is applied, allowing a fi nal decision on batch quality based on additional data. This paper presents calculation examples based on real repair data, demonstrating the practical eff ectiveness of both methods. The results show that statistical quality control enhances the reliability of decisions made, optimizes the product inspection process, and ensures a high level of product reliability under given economic and technical conditions. The fi ndings are practical for quality control and reliability assurance engineers, as well as for managers at production facilities, seeking to introduce statistical control into product repair and modernization processes.