الفهرس | Only 14 pages are availabe for public view |
Abstract The aim of this study is to the effect of the cutting variables in the numerical control devices by controlling the cutting parameter that are causing resulting in a poor surface finish, high-pitch noise and accelerated tool wear which in turn reduces machine tool life, reliability and safety of the machining operation. A face milling process was applied to Aluminum alloy (AA5083) material which used in many different Engineering application such as, the main factor affecting chatter are (surface cutting speed N, feed rate f, depth of cut a) five values for each cutting parameter were selected the different levels of the surface cutting speed are (19, 21, 23, 25and 27 m/ruin), the feed rate values are (150, 200, 250,300 and 350 mm/min) and the depth of cut values are (0.7, 1, 1.5, 2 and 2.3 mm). The experiments were carried out and vibration measurement was done using the Sensor Accelerometer and installed in surface cutting speed, the readings were recorded directly on the Mat lab program and then the surface roughness of the device was measured, Experiments were for fifteen test specimens. Chatter can be reduced by the control of surface cutting speed, feed rate and machining depth of cut, the tests were conducted to determine the effect of vibration on the surface roughness; the results showed that the depth of cut and surface cutting speed were the most important in measuring the Chatter vibrations. The Lower the depth of cut, the higher the surface cutting speed and the lower the vibrations, lower surface roughness was obtained at a surface cutting speed of 23 m/min, feed rate of 200 mm/ruin and depth of cut of 1.5 mm. Similarly, high surface roughness was obtained at surface cutting speed of 23 m/min. feed rate of 350 mm/min and depth of cut of 1.5 mm. The tests were conducted in the case of coolant to determine the ratio of the effect of the coolant on both the vibration and the roughness of the surface. An artificial neural network (ANN) model was used to predict the vibration chatter of Aluminum alloy (AA5083) material. The grid is based on an experimental cIata set of the vibration chatter and surface roughness measured during operation. (Surface cutting speed N, feed rate f and depth of cut a) are taken input data in the ANN model, while surface roughness and vibration are taken output data. |