Implementation of a versatile and efficient monitoring system in semiconductor high-volume manufacturing

Statistical Process Control (SPC) plays a critical role in semiconductor manufacturing, ensuring product quality and yield by monitoring key performance indicators (KPIs) of processes and equipment. As semiconductor nodes continue to shrink, the challenges of process control increases, often requiring the combination of traditional KPIs or the creation of new ones to identify root causes effectively. However, existing SPC systems - both commercially available and those developed in-house - may lack the necessary flexibility and functionality to manage complex data volumes. In our study, we propose a flexible and efficient KPI monitoring system based on KLA visual flow editor software applied specifically to photolithography process control and addresses these critical aspects: <strong>Scanner Performance Stability:</strong> Monitoring the stability of scanners used in photolithography processes is essential for consistent results. Any deviations can impact product quality and yield. <strong>Overlay Fingerprint Changes:</strong> Overlay refers to the alignment accuracy of multiple layers during semiconductor manufacturing. Detecting changes in overlay fingerprints helps maintain precise alignment, which is crucial for successful chip fabrication. <strong>Metrology Health:</strong> Metrology tools measure critical dimensions and other parameters during the manufacturing process. Ensuring the health and accuracy of these tools is vital for reliable data. Our proposed monitoring system leverages powerful data processing capabilities, allowing for customized KPI monitoring tailored to specific user needs. By reducing engineering time and costs, it enhances efficiency in high-volume manufacturing environments.