Logic Diagnosis Based on Deep Learning for Multiple Faults

Diagnosis of faults in logic circuit is essential to improve the yield of semiconductor circuit production. However, accurate diagnosis of adjacent multiple faults is difficult. In this paper, an idea for diagnosis of logic circuit faults using deep learning is proposed. In the proposed diagnosis idea, two adjacent faults can be accurately diagnosed using three deep learning modules. Once the modules are trained with data processed from fault simulation, the number of faults and the location of the faults are predicted by the modules from test responses of logic circuit. Experimental results of the proposed fault diagnosis idea show more than 96.4% diagnostic accuracy.