Applying Data Mining Methods to Predict Defects on Steel Surface

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Provided by: Journal of Theoretical and Applied Information Technology
Topic: Data Management
Format: PDF
In the steel industry, especially alloy steel, creating different defected product can impose a high cost for steel producers. One common defect in producing low carbon steel grades is Pits & Blister defect. To eliminate this drawback, the authors need to grind the surface of the product. In some cases, the severity of defects may lead to scrap part of the product. Grinding cause waste of time and cost of production will be increased. Incidence of defects is related to several factors including material analysis and production processes.
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