15.1.1 The Role of Data Analysis in Test and Product Engineering

Data analysis is the process by which we examine test results and draw conclusions from them. Using data analysis, we can evaluate DUT design weaknesses, identify DIB and tester repeatability and correlation problems, improve test efficiency, and expose test program bugs. As mentioned in Chapter 2, debugging is one of the main activities associated with mixed-signal test and product engineering. Debugging activities account for about 20% of the average workweek. Consequently, data analysis plays a very large part in the overall test and product engineering task.

In addition to supporting the silicon and test program debugging task, many data analysis tools are designed to help improve the silicon fabrication process itself. The fabrication process can be improved through statistical data analysis of production test results. A methodology called statistical process control (SPC) formalizes the steps by which this improvement is achieved. In this chapter we will examine various data visualization tools, study the statistics that describe repeatability and process variations, and introduce the topic of statistical process control. Although our treatment of SPC is very brief and incomplete, we do not mean to treat it as an unimportant subject. SPC is a powerful tool for continuous improvement that helps reduce defects and lower testing costs.

15.1.2 Visualizing Test Results

Many types of data visualization tools have been developed to help us make sense of the reams of test data that are generated by...