Title :
Acceptance sampling: an efficient, accurate method for estimating and optimizing parametric yield [IC manufacture]
Author :
Elias, Norman J.
Author_Institution :
Philips Lab., Briarcliff Manor, NY, USA
fDate :
3/1/1994 12:00:00 AM
Abstract :
Acceptance sampling is a new yield estimation and optimization method which combines the accuracy of Monte Carlo analysis with the computational efficiency of response surface methods. Response surface approximations are used to guide selection of simulation samples. Formulas based on established statistical methods (viz., confidence intervals, stratified sampling) estimate yield and predict accuracy. Yield optimization procedures employ conventional search algorithms. Examples using 50 to 100 simulations demonstrate accuracy matching 1000 to 10000 Monte Carlo samples
Keywords :
Monte Carlo methods; estimation theory; integrated circuit manufacture; optimisation; production; statistical analysis; IC manufacture; Monte Carlo analysis; acceptance sampling; confidence intervals; parametric yield; response surface approximations; search algorithms; statistical methods; stratified sampling; yield estimation; yield optimization; Approximation error; Circuit simulation; Computational modeling; Monte Carlo methods; Optimization methods; Response surface methodology; Sampling methods; Scattering; Surface fitting; Yield estimation;
Journal_Title :
Solid-State Circuits, IEEE Journal of
