Riichiro Take

Yield improvement using data mining system

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 tools 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.

Event analyzer: a tool for sequential data processing

In this paper we present a tool called Event Analyzer that processes events that compose a sequence. We present the data model in which Event Analyzer is based, as well as its query language that allows the expression of complex patterns to be searched over the sequence of events. The Event Analyzer has been developed and it now integrates the Fujitsu Symfoware e-Business Intelligence Suite Premium.