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Defect Cause Modeling with Decision Tree and Regression Analysis
Abstract:The main aim of this study is to identify the most influential variables that cause defects on the items produced by a casting company located in Turkey. To this end, one of the items produced by the company with high defective percentage rates is selected. Two approaches-the regression analysis and decision treesare used to model the relationship between process parameters and defect types. Although logistic regression models failed, decision tree model gives meaningful results. Based on these results, it can be claimed that the decision tree approach is a promising technique for determining the most important process variables.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1072351Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2287
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