Research on the Optimization of Multi-process Production Quality Inspection Strategy Based on Decision Tree and Comprehensive Index Scoring

This study aims to address the optimization of quality inspection strategies in multi-process production, with the goal of providing enterprises with a scientific decision-making method for quality management. This paper focuses on the complex manufacturing environment with multiple spare parts and multiple processes, and studies how to balance costs and benefits in quality inspection. Firstly, a comprehensive decision-making model including spare part inspection, semi-finished product inspection, finished product inspection, and disassembly decision is established, and cost and revenue functions are constructed. Secondly, the decision tree model is used to analyze the impact of different inspection strategies on costs and benefits, and the optimal strategy is screened through the comprehensive index score. The research results show that the strategy optimization based on the comprehensive index score function can effectively balance costs and benefits. Among the 8192 inspection strategies, the comprehensive score of the selected optimal strategy is 0.246, which significantly improves the revenue and reduces the defective rate. Finally, the feasibility and effectiveness of the model are verified through numerical experiments, and the robustness of the model under different defective rate conditions is analyzed. The model proposed in this paper provides theoretical guidance and practical reference for enterprises to optimize quality inspection strategies and achieve revenue maximization.