Early-life reliability prediction methodology for integrated circuits

Abstract

A methodology for predicting early failures due to random process flaws in integrated circuits is proposed. Early failures are not intrinsic failures, and therefore the current practice of extrapolating intrinsic life-test distributions to estimate early-life reliability is incorrect and yields optimistic results. Early failure mechanisms are classified into three categories based on the physical understanding and statistical data available for the mechanism. Subpopulations with defect-related failure distributions are characterized by a knowledge of the effects of defects in category one and using past field return data in category two. The third category, associated with failures due to applied overstress or misuse, iis characterized by field return, technology and design data. Modeling early failures at the ‘micro’ level (subsystem level) is an improvement over the existing practice of characterizing infant mortality based on field returns at the ‘macro’ level (chip level). Using the proposed methodology, process and design improvements can be incorporated in the early failure predictions. Examples showing the application of this methodology are included.