Development of a data mining methodology using robust design

Authors:
Sangmun Shin;Myeonggil Choi;Youngsun Choi;Guo Yi
Affiliations:
Department of System Management Engineering, Inje University, Gimhae, South Korea;Department of System Management Engineering, Inje University, Gimhae, South Korea;Department of System Management Engineering, Inje University, Gimhae, South Korea;Department of System Management Engineering, Inje University, Gimhae, South Korea
Venue:
ACOS'06 Proceedings of the 5th WSEAS international conference on Applied computer science
Year:
2006

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Abstract

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.