1 research outputs found
Defect Cause Modeling with Decision Tree and Regression Analysis
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 trees are 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