Optimization of Sampling Inspection and Disassembly Production Decisions Considering Defect Rate Random Disturbances

With the increasing complexity of electronic product manufacturing, the uncertainty of component quality has a significant impact on the finished product pass rate and production costs. Traditional full inspection methods are costly, while sampling inspection reduces detection costs but introduces randomness in defect rate estimation, increasing the difficulty of production decision-making. This paper proposes an optimization model for quality management under sampling inspection conditions, which comprehensively considers component inspection, semi-finished product inspection, and finished product disassembly strategies. The model simulates defect rate fluctuations by introducing random disturbances, and based on a comparison between inspection costs and potential losses, it formulates dynamic inspection and disassembly strategies to balance defect rate control and cost optimization. The research results indicate that reasonable design of inspection and processing decisions can effectively reduce overall production costs and improve finished product quality in multi-stage production processes. The proposed model has good generality and scalability, making it applicable to various complex production scenarios and providing systematic decision support for manufacturing enterprises.