Chapter 20: Data Mining Experiences in Steel Industry
- Ordieres-Meré, J. 1
- González-Marcos, A. 2
- Castejón-Limas, M. 3
- Martínez-de-Pisón, F.J. 2
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1
Universidad Politécnica de Madrid
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2
Universidad de La Rioja
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3
Universidad de León
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Argitaletxea: information science reference
ISBN: 978-1-60566-766-9
Argitalpen urtea: 2010
Orrialdeak: 427-439
Mota: Liburuko kapitulua
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Laburpena
This chapter reports five experiences in successfully applying different data mining techniques in a hotdip galvanizing line. Engineers working in steelmaking have traditionally built mathematical models either for their processes or products using classical techniques. Their need to continuously cut costs down while increasing productivity and product quality is now pushing the industry into using data mining techniques so as to gain deeper insights into their manufacturing processes. The authors' work was aimed at extracting hidden knowledge from massive data bases in order to improve the existing control systems. The results obtained, though small at first glance, lead to huge savings at such high volume production environment. The effective solutions provided by the use of data mining techniques along these projects encourages the authors to continue applying this data driven approach to frequent hard-to-solve problems in the steel industry. © 2010, IGI Global.