Reliability improvement in Al metallization: A combination of statistical prediction and failure analytical methodology

Failure mechanism identification in metal interconnect is an important step to appropriately improve the interconnect reliability characteristics. However, analysis of all the failed units from accelerated testing is too time consuming and impractical in industry. In this work, a statistical prediction combined with advanced failure analytical techniques is developed that can classify all the failed units into different failure categories simply based on their time to failure. Thereafter, detail failure analysis on only one or two failures within each category will be sufficient to identify the failure mechanisms of different categories. An industrial case is given to illustrate this analysis procedure. This approach also suggests that the early failure could be different under stress and normal use condition, and hence, care have to be taken when prioritize improvement action for field reliability improvement.