A general defect modelling and simulation-assisted approach for fault isolation in failure analysis

Over the years, defect modelling has demonstrated its effectiveness in intracell defect or root cause estimation via scan test and scan diagnosis methods. This paper describes a novel application of defect modelling in fault isolation and defect estimation in failure analysis (FA). In this article, basic defect models are first created based on failure phenomena and principles of fault isolation tools. Then, considering the corresponding failure phenomena, defect models are inserted into targeted circuits to demonstrate defect impacts via analogue simulation tools. Through this method, unreasonable defect estimations are eliminated, while the remaining estimations can cause failure; thus, defect estimations become more accurate, and further analysis becomes more targeted. To facilitate methodology execution, the analysis flow is optimized and validated in real cases. As such, visible defects are rapidly identified in three real cases, which are suitable examples to reflect the effectiveness of this method in regard to fault isolation. Moreover, further investigation of the three cases proves that how defect modelling and simulation is one powerful approach able to significantly reduce the number of defect candidates and the size of the area of interest (AOI) compared to regular approaches. In addition, via defect modelling and with the assistance of analogue simulation tools, we have an opportunity to continue to isolate defects and enhance the defect estimation accuracy through the validation of each original defect candidate under the condition of insufficient fault isolation data, or we can even meet the resolution limitation of fault isolation tools. • Deeper understanding on various fault isolation data with defect simulation • Accelerating fault isolation process with defect modelling and simulation assisted • Providing the opportunity to validate defect estimations before physical analysis • General approach for reducing defect estimation redundancy and enhancing accuracy • Enabling more targeted physical analysis with defect simulation assisted