Research on Production Process Optimization Based on Multi stage Decision Model

Abstract

This study developed a multi-stage decision model to optimize detection and disassembly strategies for minimizing costs and maximizing profits in the production of a popular electronic product. The product, assembled from two key components, is deemed defective if either component is faulty, though other factors may also cause defects. For defective products, the company can choose to either scrap them directly or disassemble them to recover parts, which incurs additional costs. Using sampling inspection methods, the study estimated the defect rate in production and optimized inspection plans for components and finished products. The model simulated various strategy combinations, calculating and comparing the total cost and profit of each to identify the optimal solution. Additionally, the study examined the impact of sampling errors on defect rate estimation and made dynamic adjustments to detection and disassembly strategies to enhance production efficiency and quality management. The findings provide important theoretical and practical guidance for quality control in enterprise production decision-making.