Improved SRAM failure diagnosis for process monitoring via current signature analysis

SRAM's are frequently used as monitor circuits for defect related yield, due to the ease of testing and the good correlation to the yield characteristics of logic circuitry. For the identification of the failure/fault type and the nature of the defect causing the failure, measured failbitmaps are mapped onto a failbitmap catalog obtained from defect-fault simulation. Often this mapping is not unique. A given failbitmap can be caused by several faults or defects. In this contribution, the application of current signature analysis is demonstrated for a stand-alone 16kx1 SRAM monitor circuit. It is found that the resolution of the failbitmap-fault-defect catalog can be improved considerably by additional current signature measurements. The interpretation of current measurements is based on simulation of the possible faults contained in the failbitmap catalog under the operating conditions in the current test. There was good agreement between the simulated and measured current values. With the aid of current measurements, more yield learning information is obtained from the process monitoring vehicle. In some cases, the shorted nodes inside a SRAM cell can be determined exactly. This eases the localization of the failure and is of practical importance for the sample preparation in physical failure analysis.