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Reseach Article

A Survey of Data Mining Techniques for Quality Improvement in Process Industries

Published on May 2012 by V. Sharmila, M. Shanmugasundaram
National Conference on Advances in Computer Science and Applications (NCACSA 2012)
Foundation of Computer Science USA
NCACSA - Number 4
May 2012
Authors: V. Sharmila, M. Shanmugasundaram
9260fd5d-5c33-4456-9f27-7abdef22f05d

V. Sharmila, M. Shanmugasundaram . A Survey of Data Mining Techniques for Quality Improvement in Process Industries. National Conference on Advances in Computer Science and Applications (NCACSA 2012). NCACSA, 4 (May 2012), 20-22.

@article{
author = { V. Sharmila, M. Shanmugasundaram },
title = { A Survey of Data Mining Techniques for Quality Improvement in Process Industries },
journal = { National Conference on Advances in Computer Science and Applications (NCACSA 2012) },
issue_date = { May 2012 },
volume = { NCACSA },
number = { 4 },
month = { May },
year = { 2012 },
issn = 0975-8887,
pages = { 20-22 },
numpages = 3,
url = { /proceedings/ncacsa/number4/6502-1027/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Advances in Computer Science and Applications (NCACSA 2012)
%A V. Sharmila
%A M. Shanmugasundaram
%T A Survey of Data Mining Techniques for Quality Improvement in Process Industries
%J National Conference on Advances in Computer Science and Applications (NCACSA 2012)
%@ 0975-8887
%V NCACSA
%N 4
%P 20-22
%D 2012
%I International Journal of Computer Applications
Abstract

This paper presents a survey of quality improvement of various products in process industries and present how data mining can be used in manufacturing for improving the quality, maintenance, control and production of a product.

References
  1. Giess, M. D. , Culley, S. J. , and Shepherd, A. , 2002, "Informing Design Using Data Mining Methods," ASME DETC, Montreal, Canada, pp. 98–106
  2. Giess, M. D. , and Culley, S. J. , 2003, "Investigating Manufacturing Data for Use Within Design," ICED 03, Stockholm, Sweden, pp. 1408–1413
  3. Perzyk, M. , Kochanski, A. , and Kozlowsk. J, 2008, "Data mining in manufacturing: significance analysis of process parameters" Proc. IMechE Vol. 222 Part B: J. Engineering Manufacture pp 1503 – 1516.
  4. Chen-Fu Chien, Wen-Chih Wang, Jen-Chieh Cheng, Data mining for yield enhancement in semiconductor manufacturing and an empirical study" Expert Systems with Applications 33 (2007) 192–198
  5. Bashar Al-Salim, Mansour Abdoli, "Data mining for decision support of the quality improvement process" Proceedings of the Eleventh Americas Conference on Information Systems, Omaha, NE, USA August 11th-14th 200 . pp 1462-1469
  6. Shu-guang He1, Zhen He, G. Alan Wang and Li Li, "Data Mining and Knowledge Discovery in Real Life Application", Book edited by: Julio Ponce and Adem Karahoca, pp. 438, February 2009, I-Tech, Vienna, Austria
  7. Gulser Koksa, Inci Batmaz, Murat Caner Testik, "A review of data mining applications for quality improvement in manufacturing industry" Expert Systems with Applications 38 (2011) 13448–13467
  8. Jayanthi Ranjan "Applications of data mining techniques in pharmaceutical Industry "Journal of Theoretical and Applied Information Technology (2005-2007). ,pp(61-67)
  9. Dan Braha and Armin Shmilovici, "Data Mining for Improving a Cleaning Process in the Semiconductor industry" IEEE transactions on semiconductor manufacturing, VOL. 15, NO. 1, FEBRUARY 2002 pp (91-101)
Index Terms

Computer Science
Information Sciences

Keywords

Quality Improvement Data Mining Manufacturing Process Industries Product