Abstract:During the integration of complex equipment, a key issue is the difficulty in quantifying, controlling, and optimizing the quality of the integration system, which impacts the equipment's performance and delivery. To address this, we first conduct an in-depth analysis of the quality of the complex equipment integration system. Based on customer, result, and process orientation, a quality control model is established, forming a Quality Composite Index (QCI) algorithm to reflect the system's dynamic quality trends. Next, focusing on the key elements of personnel, machinery, materials, methods, environment, and measurement, we optimize quality control based on process, responsibility, and data. Finally, taking an aeronautical complex equipment integration system as an example, empirical research confirms the feasibility of the model and algorithm, as well as the effectiveness of QCI-driven quality improvement measures. Our findings show that, in the digital and intelligent context, the QCI algorithm and quality control model for complex equipment integration systems actively contribute to quality enhancement.