Eliminating the Ouija(R) board: automatic thresholds and probabilistic IDDQ diagnosis

I_DDQ diagnosis is an important part of the Failure Analysis toy box, but it often requires substantial guesswork and intuition, especially when trying to divine the proper pass-fail threshold for the correct diagnostic result. This paper describes clustering and probability assignment algorithms designed to eliminate this guesswork by automatically determining diagnostic pass-fail thresholds, while using probabilistic techniques to allow for reasonable noise and error. We report the result of using these techniques on some of the failing chips from the Sematech experiment. The system describe first identifies appropriate thresholds and then pinpoints the correct diagnosis without requiring manual intervention and without requiring that the observed I_DDQ behavior perfectly matches the predicted I_DDQ behavior. The paper also discusses the use of information produced by inductive fault analysis and specialized fault simulation as part of the diagnosis process