At advanced technology nodes (sub-22 nm), design rules become very complicated as interactions between multiple layers become more complex, while the number of design elements within the optical radius increases. As a result, one may possibly encounter novel yield limiters in the 2D/3D design space with every new product taping out to the fab. Key to fast yield ramp is identifying novel constructs that may become yield detractors, and to address the challenge in the DFM space before actual Silicon is run. A comprehensive methodology to find such geometric constructs is proposed.
Proc. SPIE. 9427, Design-Process-Technology Co-optimization for Manufacturability IX
KEYWORDS: Statistical analysis, Data modeling, Metals, Manufacturing, Design for manufacturing, Image classification, Raster graphics, Optimization (mathematics), Current controlled current source, Design for manufacturability
During the yield ramp of semi-conductor manufacturing, data is gathered on specific design-related process window limiters, or yield detractors, through a combination of test structures, failure analysis, and model-based printability simulations. Case-by-case, this data is translated into design for manufacturability (DFM) checks to restrict design usage of problematic constructs. This case-by-case approach is inherently reactive: DFM solutions are created in response to known manufacturing marginalities as they are identified. In this paper, we propose an alternative, yet complementary approach. Using design-only topological pattern analysis, all possible layout constructs of a particular type appearing in a design are categorized. For example, all possible ways via forms a connection with the metal above it may be categorized. The frequency of occurrence of each category indicates the importance of that category for yield. Categories may be split into sub-categories to align to specific manufacturing defect mechanisms. Frequency of categories can be compared from product to product, and unexpectedly high frequencies can be highlighted for further monitoring. Each category can be weighted for yield impact, once manufacturing data is available. This methodology is demonstrated on representative layout designs from the 28 nm node. We fully analyze all possible categories and sub-categories of via enclosure such that 100% of all vias are covered. The frequency of specific categories is compared across multiple designs. The 10 most frequent via enclosure categories cover ≥90% of all the vias in all designs. KL divergence is used to compare the frequency distribution of categories between products. Outlier categories with unexpected high frequency are found in some designs, indicating the need to monitor such categories for potential impact on yield.