🤖 AI Summary
This study addresses the growing challenges traditional failure analysis methods face in the era of advanced packaging technologies—such as chiplets, hybrid bonding, and 3D stacking—by conducting an anonymous global survey of over 100 semiconductor design, packaging, and failure analysis organizations. The findings reveal that 69% of respondents prioritize heterogeneous integration products (mean importance score: 7.92/10), while 54% identify hybrid bonding as the most analytically challenging technique. A strong consensus emerges around the need for standardized data formats, with 83% of participants advocating for unified protocols, and high-resolution non-destructive imaging garners substantial support (mean score: 8.18/10). The research systematically identifies critical pain points in sample preparation and 3D structural inspection, offering empirical insights to guide industry standardization and technological innovation.
📝 Abstract
Failure analysis is being reshaped by heterogeneous integration, chiplet-based architectures, hybrid bonding, backside technologies, & increasingly buried package structures. To examine how practitioners view this transition, an anonymous survey was distributed across a broad set of organizations involved in semiconductor design, packaging, systems, tools, & failure analysis. The survey collected approximately one hundred responses & probed organizational background, supported product domains, future priorities in failure analysis, critical bottlenecks, sample preparation challenges, emerging architecture specific pain points, & perceived needs for workflow acceleration & data standardization. The results show that heterogeneous integration, chiplet, and three-dimensional products dominate the respondent base at 69%, while package & heterogeneous integration failure analysis received the highest importance rating at 7.92 out of 10. Hybrid bonding emerged as the most difficult new architecture to analyze at 54%, higher-resolution non-destructive imaging ranked as the most important future accelerator at 8.18 out of 10, and 83% of respondents supported formalized data standardization frameworks. The complete survey data are provided in Appendix A (Table II) to improve transparency & support future benchmarking.