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Optimization of Robust Design Model using Data Mining  

Jung, Hey-Jin (Department of Industrial & Management Systems Engineering, Dong-A University)
Koo, Bon-Cheol (Department of Mechanical Engineering, Tongmyong University)
Publication Information
Journal of Korean Society of Industrial and Systems Engineering / v.30, no.2, 2007 , pp. 99-105 More about this Journal
Abstract
According to the automated manufacturing processes followed by the development of computer manufacturing technologies, products or quality characteristics produced on the processes have measured and recorded automatically. Much amount of data daily produced on the processes may not be efficiently analyzed by current statistical methodologies (i.e., statistical quality control and statistical process control methodologies) because of the dimensionality associated with many input and response variables. Although a number of statistical methods to handle this situation, there is room for improvement. In order to overcome this limitation, we integrated data mining and robust design approach in this research. We find efficiently the significant input variables that connected with the interesting response variables by using the data mining technique. And we find the optimum operating condition of process by using RSM and robust design approach.
Keywords
Data Mining; CBFS; BFS; RSM; Robust Design;
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