A Multi-stage Decision Planning Model for Optimizing Production Inspection Strategy with Defect Rate Reduction

This paper proposes a multi-stage decision planning model for optimizing inspection strategies in production processes with progressive defect rate reduction. We establish statistical methods for determining minimal sample sizes at different confidence levels (95% vs. 90%) and develop a cost optimization model that dynamically balances inspection costs against defect-related losses. Experimental results demonstrate that prioritizing final product inspection while minimizing component-level testing yields the lowest overall costs. Our findings reveal that component-level inspection is rarely cost-effective in most scenarios, and inspection strategies should be dynamically adjusted as defect rates decrease. Additionally, lowering confidence levels from 95% to 90% moderately reduces quality control costs without significantly compromising quality assurance. The model provides manufacturers with a quantitative framework for optimizing inspection decisions across multiple production stages.