Defect cause modeling with decision tree and regression analysis : a case study in casting industry

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2007

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Bakır, Berna

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In this thesis, we study improvement of product quality in manufacturing industry by identifying and optimizing influential process variables that cause defects on the items produced. Real data provided by a manufacturing company from the metal casting industry were studied. Two well-known approaches, logistic regression and decision trees, were used to model the relationship between process variables and defect types. The approaches used were compared.

Subject Keywords

Information Technology.

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http://etd.lib.metu.edu.tr/upload/12608427/index.pdf
https://hdl.handle.net/11511/16800

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Graduate School of Informatics, Thesis

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Citation Formats

B. Bakır, “Defect cause modeling with decision tree and regression analysis : a case study in casting industry ,” M.S. - Master of Science, Middle East Technical University, 2007.