Abstract
With the fast development trend of highly integrated electronic
products, as the key technology of three-dimensional(3D) interconnect
circuits, the research on Monolithic Inter-tier Via(MIV) testing
technology is particularly critical. Therefore,this paper proposes a
machine-learning-based MIV open fault localization method. This method
adopts the EXtreme Gradient Boosting (XGBoost) prediction model
optimized based on the Grid Search (GS) algorithm, and takes the
S-parameters as the training dataset. The S-parameters are used as the
training data set to train and evaluate the prediction model. This
method can effectively solve the problem that the traditional MIV test
method is difficult to accurately locate the MIV open faults. Simulation
results show that the prediction model proposed in this paper can
accurately predict the location of open faults.