This research integrates sampling hypothesis testing and decision models to enhance quality control, suggesting significant cost reduction and defect rate improvement.
Key Points
Significant improvements include 15-20% cost reduction and 25-30% deficit rate improvement through a novel approach.
The model achieves 95% confidence for rejection and 90% for acceptance using a sampling inspection scheme.
Dynamic programming principles are applied to optimize supplier selection and production decisions under complex conditions.
Monte Carlo simulation confirms the model's effectiveness under uncertain defect rates, offering practical insights for manufacturing.