Demystifying Unexpected Silicon Responses through User-Defined Fault Models (UDFM) and Failure Analysis

Abstract

Failure Analysis (FA) plays an important role during silicon development and yield ramp up, helping identify critical test, design marginality and process issues in a timely and efficient manner. FA techniques typically rely on diagnosis callouts as a starting point for debug. Diagnostic algorithms rely on the error logs collected on production patterns which are generated to detect Stuck-at Faults (SAF) and Transition Delay Faults (TDF). Typically, SAF patterns screen out the static defects and TDF patterns test for transient fails. But often, we see cases where a SAF pattern shmoo is clean but the TDF pattern shmoo is a gross failure indicating a cell-internal static defect missed by the traditional SAF patterns. In this work, we will present our own developed User-Defined Fault Model, which targets cell-internal faults to explain unexpected silicon observations. An added advantage of the work can be seen in improving diagnosis results on the error logs collected using these targeted UDFM patterns. Since UDFM utilizes targeted fault excitation, the diagnosis algorithm results in better callouts. In this paper, we will also propose a custom diagnosis flow using our in-house UDFM to achieve better resolution. Three FA case studies will be presented to showcase the usefulness and effectivity of the proposed methods.