Design Guidelines for In-line X-ray Inspection in Advanced Packaging Technology: A CoWoS Case Study

The shift towards advanced packaging technologies, including 2.5D and 3D integration, addresses the limitations of traditional methods while meeting increasing demands for performance, miniaturization, and efficiency. These methods enhance functionality and support heterogeneous integration but also introduce metrology challenges due to complex, three-dimensional structures. X-ray imaging, crucial for non-destructive inspection, faces compatibility issues such as material density similarities and noise scattering. To address these challenges, we propose a framework based on AI-integrated Design of Experiment (DoE) to develop design guidelines to optimize X-ray compatibility during the design stage. This framework, demonstrated through a case study on Chip-on-Wafer-on-Substrate (CoWoS) packaging, systematically analyzes design parameters and material properties to develop guidelines for improved inspection accuracy. Our method integrates AI to predict outcomes and optimize processes, ensuring high-quality X-ray images and enhancing defect detection. Implementing these guidelines can significantly improve inspection accuracy and reliability, reducing production costs and supporting the efficiency and scalability of advanced semiconductor technologies.