Yield improvement using data mining system
Fumitake Mieno, Toshinori Sato, Yukinori Shibuya, Kazuya Odagiri, Hiroshi Tsuda, Riichiro Take · 2003
It is ideal to prevent all failures. However, when a failure occurs, it is important to quickly specify the cause stage and take countermeasures. There are various types of failures, ranging from the failures due to simple mis-operation to the failures whose cause analysis takes many highly skilled engineers a long time. If the failure cause in the latter case can be specified simply by anyone, the yield enhancement will be accelerated. We are developing a method that enables us to specify a failure cause, without depending on the experience and skills of engineers. Data mining is a method for extracting buried information and rules from data of enormous quantity, by using a statistical method. Some examples have been reported in various fields but only a few in the semiconductor field. This time, we have applied a regression tree analysis system, which is one of data mining tool's codeveloped by Fujitsu Laboratories Ltd. and FLT, to failure analysis in LSI manufacturing. As a result, a failure cause which has been difficult to be detected even in the in-process monitoring was specified automatically only in six hours. Then, through the verification process, we ascertained that the failure cause was correct. We could specify the cause and take countermeasures at a speed six times faster than by the conventional method.