Development of an SPC Platform for High-Precision Aerospace Components Through Automated Collection of 3D Measurement Data and Report Automation.

As the Fourth Industrial Revolution continues to expand across various industries, many companies are accelerating efforts to establish smart factory-based industrial environments. A smart factory refers to an intelligent production system that maximizes efficiency and productivity by integrating digital automation into every stage of production, including design, manufacturing, quality control, and logistics. This innovative system is particularly significant in the high-precision aerospace component manufacturing industry, where the importance of meeting stringent quality standards is paramount. The high-precision aerospace component industry demands extremely high-quality standards, and to meet these requirements, precise measurements using three-dimensional (3D) measurement machines have become an essential part of the production process. Accurate data collection through 3D measurement machines plays a crucial role in ensuring product quality. However, traditional methods of data collection and management have heavily relied on manual processes, which are time-consuming, labor-intensive, and prone to human error, leading to limitations in productivity and quality control. To address these challenges, this paper proposes the design and methodology for developing a Statistical Process Control (SPC) system platform specifically tailored for the real-time automatic collection and analysis of 3D measurement data in high-precision aerospace manufacturing processes. The agent developed in this research enables the real-time automatic collection of raw data, offering significant advantages in terms of labor and time savings compared to traditional manual methods. This agent automatically compiles and analyzes data, facilitating optimized quality verification processes for high-precision aerospace component manufacturing. The collected quality data are analyzed using statistical quality control techniques specialized for 3D measurement data, allowing for continuous monitoring of product quality. Additionally, the system supports the establishment of a quality monitoring system capable of real-time response to any quality issues that may arise, significantly enhancing the efficiency of quality management. Therefore, the system proposed in this paper provides the essential technological foundation for implementing smart factories in the high-precision aerospace component manufacturing industry, with the potential to greatly improve overall productivity and quality management efficiency. This research is expected to make significant contributions to quality management in smart manufacturing environments for high-precision components. [ABSTRACT FROM AUTHOR]