Risk Assessment in Signature Analysis

Abstract

Abstract Hie failure analysis lab has analyzed 'n' devices that all have the same failure signature (a failure mode plus other observable characteristics), and found that they all failed from the same mechanism. We wish to identify this mechanism with the failure signature so that future parts with the same signature may be assigned a mechanism without analysis, but by inference from historical data, thus saving lab time and resources. What is the risk of error? A probability model is presented that allows the analyst to calculate a confidence interval for the proportion of future devices with the same signature failing from the same mechanism. An X/Y criterion is defined: one is X% confident that greater than Y% of future devices with this signature will also have this mechanism. The model is presented for an 'on-going process' application and for a 'finite-population' application. Easy calculation methods are presented, and charts are given to illustrate and shortcut the calculations.