Development of a data mining methodology using robust design

초록

The data mining (DM) method is far more effective than any other method when a large number of input factors are considered on a process design procedure. This DM approach to a robust design problem has not been adequately addressed in the literature nor properly applied to industries. As a result, the primary objective of this paper is two-fold. First, we show how DM techniques can be effectively applied into a process design by proposing a correlation-based factor selection (CBFS) method. Second, we then show how DM results can be integrated into a robust design (RD) paradigm based on the selected significant factors.

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