Production Process Decision Based on 0-1 Integer Programming and Sequential Probability Ratio Test

In modern manufacturing systems, large-scale production lines face complex component and finished product processing tasks. It is of great significance to establish a data-driven, precise decision-making system to ensure the scientificity and process stability of the production process. This article focuses on the quality control method based on sequential sampling, optimizing the manufacturing process through in-depth analysis of the core process parameter of defect rate. A 0-1 programming model is adopted to optimize the design of the component synthesis strategy, and a dynamically adjusted quality control scheme is proposed. Under the condition of a preset defect rate of 0.1, this study achieved a statistical confidence level of 95% and was able to adaptively adjust the control strategy based on dynamic changes in the number of components, with a rejection threshold set at 15%. In response to the actual engineering situation where the defect rate fluctuates between 0.1 and 0.15, this method significantly reduces the number of sampling iterations and only requires an average of 245 iterations to complete quality assessment.