A DFT approach for diagnosis and process variation-aware structural test of thermometer coded current steering DACs

A design for test (DFT) hardware is proposed to increase the controllability of a thermometer coded current steering digital to analog converter. A procedure is introduced to reduce the diagnosis and structural test time from quadratic to linear using the proposed DFT hardware. To evaluate the applicability of the proposed technique, principal component analysis is used to create virtual process variations to simulate in lieu of semiconductor fabrication data. An architecture specific soft fault model is suggested for the diagnosis problem. Random errors according to the fault model are introduced in the virtual test environment on top of the process variations and it is shown that diagnosis of a fault is possible with high accuracy with the proposed method. The same technique employing principal component analysis is furthermore used to provide process variation-aware reference test comparison values for a structural test of the DAC. The structural test provides a mechanism to test for even unmodeled manufacturing faults. The process variation-aware test values help detect defects even under process variations. The proposed DFT hardware and method are low cost and quite suitable for a built-in self diagnosis and test implementation.