REAL-TIME EMPIRICAL BAYES MANUFACTURING PROCESS MONITORING FOR CENSORED-DATA

Because of the current work in manufacturing electronics which links high-speed test sets to host computers, it is now possible to collect and analyse measurements seconds after a product is tested. However, some of the actual measurements may often not be collected. This paper describes a technique to monitor right-censored, left-censored or both right- and left-censored manufacturing data. Also, the technique is applicable to 'interval' censored data; data that is censored when it occurs in an interval, with uncensored observations above and below the interval. This'interval' censoring can occur when automatic test equipment cannot transmit data and test at the same time. To increase production volume through the test area, measurements are often collected only when a test fails. The method described is designed to monitor a manufacturing process in real-time with the goal of identifying process changes as they occur. An empirical Bayes model of the process response parameters is developed for the situation when censoring is present. Estimates for the model are developed, a strategy for implementing the model is given and an example is presented which illustrates its use to monitor a process.