01-09-2016, 10:41 AM
PREDICTION OF SURFACE ROUGHNESS BASED ON MACHINING CONDITION AND CONDITION OF CARBIDE TIP INSERT IN BORING STAINLESS STEEL USING DECISION TREE MODEL
1451983931-Vijayabstract.docx (Size: 12.28 KB / Downloads: 7)
ABSTRACT
The prediction of surface roughness is the main objective of all manufacturing industries. In this paper, the prediction of surface roughness model was developed in boring operation under the cutting parameters such as speed, feed rate depth of cut and tool condition as flank wear. Stainless steel 304 was chosen as a work piece because it has multiple applications. Due to the high hardness and chemical stability with work piece. The tool used for machining purpose is a carbide tipped tool [Insert]. The machining was done by CNC Lathe machine and the vibration signals were recorded by data acquisition card. Finally, the prediction model was developed in the decision tree method.