An IC manufacturing yield model considering intra-die variations

In deep submicron, feature sizes continue to shrink aggressively beyond the natural capabilities of the 193 nm lithography used to produce those features thanks to all the innovations in the field of resolution enhancement techniques (RET). With reduced feature sizes and tighter pitches die level variations become an increasingly dominant factor in determining manufacturing yield. Thus a prediction of design-specific features that impact intra-die variability and correspondingly its yield is extremely valuable as it allows for altering such features in a manner that reduces intra-die variability and improves yield. In this paper, a manufacturing yield model which takes into account both physical layout features and manufacturing fluctuations is proposed. The intra-die systematic variations are evaluated using a physics-based model as a function of a design's physical layout. The random variations and their across-die spatial correlations are obtained from data harvested from manufactured test structures. An efficient algorithm is proposed to reduce the order of the numerical integration in the yield model. The model can be used to (i) predict manufacturing yields at the design stage and (ii) enhance the layout of a design for higher manufacturing yield.