Optimization of Production Quality Control Strategies Based on Sequential Probability Ratio Test

In modern manufacturing industry, for the limitations of traditional fixed sampling inspection methods, sequential probability ratio test (SPRT) achieves efficient and flexible quality control optimization by dynamically adjusting the sampling size, which is especially suitable for complex inspection scenarios in multi-stage production processes. In this study, a mathematical model is constructed from the perspective of enterprise production decision-making, combined with key parameters such as defective rate, with the aim of exploring the optimal decision-making in each stage of the production process. By applying the SPRT method, the inspection strategy is optimized, the sampling number is reduced, and the relationship between the actual defective rate and the average sampling number is analyzed through simulation experiments, which provides a scientific basis for the sampling decision of the enterprise. In addition, this paper also establishes the total profit calculation model and solves the optimal decision in six cases by simulated annealing algorithm.