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Optimization Methodology Integrated Data Mining and Statistical Method  

Song, Suh-Ill (Dept. of Industrial & Management Systems Engineering, Dong-A University)
Shin, Sang-Mun (Department of Systems Management & Engineering, Inje University)
Jung, Hey-Jin (Dept. of Industrial & Management Systems Engineering, Dong-A University)
Publication Information
Journal of Korean Society for Quality Management / v.34, no.4, 2006 , pp. 33-39 More about this Journal
Abstract
These days manufacture technology and manufacture environment are changing rapidly. By development of computer and enlargement of technique, most of manufacture field are computerized. In order to win international competition, it is important for companies how fast get the useful information from vast data. Statistical process control(SPC) techniques have been used as a problem solution tool at manufacturing process until present. However, these statistical methods are not applied more extensively because it has much restrictions in realistic problems. These statistical techniques have lots of problems when much data and factors are analyzed. In this paper, we proposed more practical and efficient a new statistical design technique which integrated data mining (DM) and statistical methods as alternative of problems. First step is selecting significant factor using DM feature selection algorithm from data of manufacturing process including many factors. Second step is finding optimum of process after estimating response function through response surface methodology(RSM) that is a statistical techniques
Keywords
Data MininG; CBFS; SPC; RSM; Optimization;
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