Improved methods for IC yield and quality optimization using surface integrals

A novel formulation of the parametric yield as a surface integral on the boundary of the disturbance space acceptability region is introduced. This formulation allows the accurate and efficient estimation of yield via a Monte Carlo method which can also produce yield gradients with minimal overhead. Under mild assumptions, the surface integral based yield estimate is continuous and practically twice differentiable almost everywhere; therefore it is ideally suited for use with powerful gradient-based optimization algorithms. A general IC quality optimization method, significantly more efficient than Taguchi´s method, is also introduced. This method can handle multiple performances and handles yield maximization as a special case.<>