Optimal design of experiments for semiconductor lifetime data

Performing experiments is necessary to find influences of different factors on the measured output. In semiconductor industry experiments are mainly performed following predefined specifications and guidelines, given by experts for the device under test (DUT). The statistical method design of experiments (DoE) provides an objective solution to the question: which experiments have to be performed to get the most information concerning main influencing factors and interaction between factors. In practical usage classical DoE often reach their limits, especially when resources for experiments are meagre. A remedy is given by optimal DoEs. They are more flexible and offer the possibility to optimize e.g. the prediction accuracy on a pre-defined area, where performing measurements is difficult. For this purpose the IV-optimality criterion is used in this paper. On the basis of already performed experiments, an exchange algorithm proposed by Spoöck and Pilz [2] was used to select 3 further desired experiments. After their performance they were evaluated and, as expected, an improvement in the mean squared error of prediction (MSEP) was observed.