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

Bakır, Berna
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.


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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.