O. M. Ikumapayi

Data showing the effects of temperature and time variances on nano-additives treatment of mild steel during machining

The effects of temperature and time variances on nano-additives treatment of mild steel during machining was presented in this study. Mild steel of 150u202fkg mass containing 0.56% carbon was charged into the furnace at melting and pouring temperature of 1539 and 1545u202f°C respectively. Also charged into the furnace with the mild steel were 0.05% max phosphorous and a bit of sulphur. Thereafter, the sample was cooled and annealed at a temperature of 900u202f°C for 9u202fh and then cooled to 300u202f°C of hardening, normalizing and tempering respectively. The treated samples were then soaked with pulverized in palm kernel shell and barium carbonate (20%) energizer at respective temperatures (800, 850, 900 and 950u202f°C) and time variances (60, 90 and 120u202fmin) in a muffle furnace. The developed tool was tested on a lathe machine to evaluate its performance. The surface and core hardness, wear resistance and toughness were carried out using the hardness tester, Rotopol–V and impact tester respectively. This is essential for predicting the useful life of the tool in service.

Experimental and Mathematical Modeling for Prediction of Tool Wear on the Machining of Aluminium 6061 Alloy by High Speed Steel Tools

Abstract In recent machining operation, tool life is one of the most demanding tasks in production process, especially in the automotive industry. The aim of this paper is to study tool wear on HSS in end milling of aluminium 6061 alloy. The experiments were carried out to investigate tool wear with the machined parameters and to developed mathematical model using response surface methodology. The various machining parameters selected for the experiment are spindle speed (N), feed rate (f), axial depth of cut (a) and radial depth of cut (r). The experiment was designed using central composite design (CCD) in which 31 samples were run on SIEG 3/10/0010 CNC end milling machine. After each experiment the cutting tool was measured using scanning electron microscope (SEM). The obtained optimum machining parameter combination are spindle speed of 2500 rpm, feed rate of 200 mm/min, axial depth of cut of 20 mm, and radial depth of cut 1.0mm was found out to achieved the minimum tool wear as 0.213 mm. The mathematical model developed predicted the tool wear with 99.7% which is within the acceptable accuracy range for tool wear prediction.