Manufacturers of digital circuits test their products to find defective parts so they are not sold to customers. Despite extensive testing, some of their products that are defective pass the testing process. To combat this problem, manufacturers have developed a metric called defective part level. This metric measures the percentage of parts that passed the testing that are actually defective. While this is useful for the manufacturer, the customer would like to know how long it will take for a manufacturing defect to affect circuit operation. In order for a defect to be detected during circuit operation, it must be excited and observed at the same time. This research shows the correlation between defect detection during automatic test pattern generation (ATPG) testing and normal operation for both combinational and sequential circuits. This information is then used to formulate a mathematical model to predict the expected latency to failure due to manufacturing defects.

Manufacturers of digital circuits test their products to find defective parts so they are not sold to customers. Despite extensive testing, some of their products that are defective pass the testing process. To combat this problem, manufacturers have developed a metric called defective part level. This metric measures the percentage of parts that passed the testing that are actually defective. While this is useful for the manufacturer, the customer would like to know how long it will take for a manufacturing defect to affect circuit operation. In order for a defect to be detected during circuit operation, it must be excited and observed at the same time. This research shows the correlation between defect detection during automatic test pattern generation (ATPG) testing and normal operation for both combinational and sequential circuits. This information is then used to formulate a mathematical model to predict the expected latency to failure due to manufacturing defects.