TY - JFULL AU - S. Ghorbani and N. I. Polushin PY - 2017/5/ TI - An Alternative Approach for Assessing the Impact of Cutting Conditions on Surface Roughness Using Single Decision Tree T2 - International Journal of Mechanical and Mechatronics Engineering SP - 824 EP - 830 VL - 11 SN - 1307-6892 UR - https://publications.waset.org/pdf/10007017 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 124, 2017 N2 - In this study, an approach to identify factors affecting on surface roughness in a machining process is presented. This study is based on 81 data about surface roughness over a wide range of cutting tools (conventional, cutting tool with holes, cutting tool with composite material), workpiece materials (AISI 1045 Steel, AA2024 aluminum alloy, A48-class30 gray cast iron), spindle speed (630-1000 rpm), feed rate (0.05-0.075 mm/rev), depth of cut (0.05-0.15 mm) and tool overhang (41-65 mm). A single decision tree (SDT) analysis was done to identify factors for predicting a model of surface roughness, and the CART algorithm was employed for building and evaluating regression tree. Results show that a single decision tree is better than traditional regression models with higher rate and forecast accuracy and strong value. ER -