원문정보
Quality Imporovement of Auto-Parts Using Data Mining
초록
영어
Data mining is the process of finding and analyzing data from a big database and summarizing it into useful information for a decision-making. A variety of data mining techniques have been being used for wide range of industries. One application of those is especially so for gathering meaningful information from process data in manufacturing factories for quality improvement. The purpose of this paper is to provide a methodology to improve manufacturing quality of fuel tanks which are auto-parts. The methodology is to analyse influential attributes and establish a model for optimal manufacturing condition of fuel tanks to improve the quality using decision tree, association rule, and feature selection.
목차
1. 서론
2. 관련문헌 연구
3. 알루미늄 연료탱크 제조공정
4. 품질데이터 분석
4.1 속성선정(Feature Selection)
4.2 분류모델 분석
4.3 연관분석(Association Model)
4.4 공정변수 패턴 파악
5. 결론 및 향후과제
6. 참고문헌