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For advanced technology nodes, the ability to improve the yield of a product in a short time dictates the success for both fabless and foundry. Identification of failure mechanisms in digital logic is frequently done using scan diagnosis driven yield analysis (DDYA) [1][2][3]. Recent works on root cause deconvolution (RCD) [4][5] discussed a Bayes net model based diagnosis data learning algorithm...
This investigation employs an optimized method to alleviate defects occurring at BF2+ implanted source/drain areas, some white spots defects found at scribes lines after BPSG (boron and phosphorus doped silicon glass) anneal. The results of physical failure analysis indicate the white spot defects are relative to outgassed fluorine that can't be released out during BPSG thermal annealing. Various...
The need for faster and more reliable yield ramp-up when introducing new CMOS technologies is driving the effort to acquire and analyze valuable information from production test, for the process of identification of yield detractors. This paper addresses a key step in the phase of "industrialization" of these processes: standardization. The objective of standardization is to enable a seamless...
Diagnosis of scan test fail data plays a crucial role in enhancing ramp up of new CMOS technology generations. To enable faster feedback it is preferable to establish a monitoring diagnosis methodology on the production test floor. This paper reports result of a study on using test time optimized compressed scan technology and associated new algorithms for fault diagnosis. Data is based on a system-on-a-chip...
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