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Defect Cause Modeling With Decision Tree And Regression Analysis: A Case Study In Casting Industry

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.

Identiferoai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12608427/index.pdf
Date01 May 2007
CreatorsBakir, Berna
ContributorsBaykal, Nazife
PublisherMETU
Source SetsMiddle East Technical Univ.
LanguageEnglish
Detected LanguageEnglish
TypeM.S. Thesis
Formattext/pdf
RightsTo liberate the content for public access

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