The application of innovative joint control strategies in the synergistic optimization of enterprise procurement, production, rework and quality control

Abstract

This study proposes an innovative joint control strategy for enterprise collaborative optimization in procurement, production, rework, and quality control in mechanical component manufacturing enterprises. A comprehensive model unifies supplier selection, rework decisions, and quality sampling is developed, thereby addressing the fragmentation of single-stage optimization in existing studies. In procurement, a confidence-interval-based model screens suppliers, with sample size determined by binomial distribution, factoring in two types of error risks to optimize costs. A cost-benefit model for production evaluates rework feasibility. For quality control, a fraction-f sampling plan balances inspection costs and product quality. The model is solved and simulated using MATLAB, and sensitivity analysis is conducted. The analysis reveals that the spare-part defect rate significantly impacts total profit, stressing procurement quality control. The defect rate of semi-finished products has minimal impact, indicating effective controls. An increase in the finished-product defect rate raises costs and reduces profits. These results demonstrate the effectiveness of the proposed joint control strategy in optimizing the cost-quality balance.