Acceptance sampling: An efficient, accurate method for estimating and optimizing parametric yield

Author

Elias, Norman Jay

Author_Institution

Philips Lab., Briarcliff Manor, NY, USA

fYear

1993

fDate

9-12 May 1993

Abstract

Acceptance sampling, a yield estimation and optimization method which combines the accuracy of Monte Carlo analysis with the computational efficiency of response surface methods, is described. Response surface approximations are used to guide selection of simulation samples. Formulas based on established statistical methods (confidence intervals, stratified sampling, etc.) estimate yield and predict accuracy. Yield optimization procedures employ conventional search algorithms. Examples using 50 to 100 simulations demonstrate accuracy matching 1,000 to 10,000 Monte Carlo samples

Keywords

circuit optimisation; Monte Carlo analysis; acceptance sampling; accurate method; confidence intervals; parametric yield; response surface approximations; search algorithms; selection of simulation samples; stratified sampling; yield estimation; yield optimisation; Approximation error; Circuit simulation; Computational modeling; Computer simulation; Least squares approximation; Monte Carlo methods; Optimization methods; Response surface methodology; Sampling methods; Yield estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Custom Integrated Circuits Conference, 1993., Proceedings of the IEEE 1993

Conference_Location

San Diego, CA

Print_ISBN

0-7803-0826-3

Type

conf

DOI

10.1109/CICC.1993.590588

Filename

590588