대한안전경영과학회지 (Journal of the Korea Safety Management & Science)

  • 제9권3호
  • /
  • Pages.135-142
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  • 2007
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  • 1229-6783(pISSN)
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  • 2288-1484(eISSN)
대한안전경영과학회 (Korea Safety Management & Science)
권호 표지

데이터마이닝을 이용한 설계변경의 효율향상 - B전자의 사례를 중심으로 -

Raise the efficiency of engineering changes using Data mining - B Electronics Case -

  • 발행 : 2007.06.30
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초록

The authors used association rules and patterns in sequential of data mining in order to raise the efficiency of engineering changes. The association rule can reduce the number of engineering changes since it can estimate the parts to be changed. The patterns in sequential can perform engineering changes effectively by estimating the parts to be changed from sequence estimation. According to this result, unnecessary engineering changes are eliminated and the number of engineering changes decrease. This method can be used for improving design quality and productivity in company managing engineering changes and related information.

키워드

참고문헌

  1. 강창완, 강현철, 데이터마이닝, 사이플러스, (2007)
  2. 고재문, 정길상, 황달준, 데이터마이닝의 이해와 활용, 울산대학교출판부, (2005)
  3. 석정재, 김재근, 이철우, 홍순구, 유춘번, '설계변경의 경향 및 원인분석을 통한 설계 품질향상 방안', 품질혁신, 제 1권 제 1호 (2000): 108-123
  4. 허명회, 이용구, 데이터마이닝 모델링과 사례, 데이터솔루션, (2003)
  5. 허준, 정규상, 허수희, 최희경, Clementine 7 매뉴얼, 데이터 솔루션, (2003)
  6. Agrawal R., Imielinski T. and A. Swami, Database mining: A performance perspective, IEEE Transaction on knowledge and data engineering, 5 (1993): 914-925 https://doi.org/10.1109/69.250074
  7. Chen M. S., Han J. and Yu P. S., Data mining: An overview from a database perspective, IEEE Transaction on knowledge and data engineering, 8 (1996): 866-883 https://doi.org/10.1109/69.553155
  8. George Q.Huang, K.L.Mak, Internet Applications in Production Design and Manufacturing, Springer, (2003)
  9. Hegde, G.G., Kekre, S.H., Su, H., Engineering changes and time delays: A field investigation, Production economics 28 (1992): 341-352 https://doi.org/10.1016/0925-5273(92)90021-X
  10. Ho GTS, Lau HCW, Lee CKM, An intelligent production workflow mining system for continual quality enhancement, Advanced Manufacturing Technology 28 (2006): 792-809 https://doi.org/10.1007/s00170-004-2416-9
  11. Lior Rokach, Oded Maimon, Data mining for improving the quality of manufacturing, Intelligent Manufacturing, 17 (2006): 285-299 https://doi.org/10.1007/s10845-005-0005-x
  12. SPSS, Clementine 8.0 user's guide, SPSS, (2003)
  13. Srikant R. and R. Agrawal, Mining generalized association rules, Proceedings of the 21th International Conference on Very Large Databases, (1995): 407-419