A new via chain design method considering confidence level and estimation precision
For accurate prediction of via yield, via chains are usually fabricated on test chips to investigate issues about vias. To minimize the randomness of experiments and make the testing results more convincing, the confidence level and estimation precision of the via failure rate are investigated in this paper. Based on the Poisson yield model, the method of determining an adequate number of total vias is obtained using the law of large numbers and the de Moivre-Laplace theorem. Moreover, for a specific confidence level and estimation precision, the method of determining a suitable via chain length is proposed. For area minimization, an optimal combination of total vias and via chain length is further determined. Monte Carlo simulation results show that the method is in good accordance with theoretical analyses. Results of via failure rates measured on test chips also reveal that via chains designed using the proposed method has a better performance. In addition, the proposed methodology can be extended to investigate statistical significance for other failure modes.
via chain confidence level estimation precision via failure rate poisson yield model