Investigation study of electrical discharge machining parameters on material removal rate for AISI M2 material
Volume 16, Issue 1, Winter 2023, Pages 42-46
https://doi.org/10.30772/qjes.v16i1.832
Shukry H. Aghdeab, Ahmed Basil Abdulwahhab, Zainab H. Mohsein
Abstract EDM (Electrical Discharge Machining) is a common non-traditional machining technique for manufacture geometry parts made of intricate or extremely rigid metals that are challenging to manufacture using conventional manufacturing techniques. Electrical discharge machining by utilizing electrical discharge erosion, classify the meaning of material removal (MR). This paper's main objective is to discuss the ideal EDM parameters in order to use high-speed steel as workpiece AISI M2 and with using brass & copper as electrodes. Pulse on-time are (100, 150, and 200 µs), Current (10, 24 and 42 A) and Pulse off-time (4, 12 and 25 µs) are the input parameters effect on the material removal rate (MRR) used in the experimental work. The present study's findings shown that the highest MRR with using copper & brass as electrodes with pulse on-time 200 µs, pulse off-time 12 µs and current 42 A, at (0.31284 g/min and 0.18769) respectively, and the lowest average value of the removed material was when evaluating current 10 A, Ton is 100 µs, Toff is 4 µs, at (0.05451g/min and 0.01898 g/min) respectively.
Еxpeгimental investigаtion of сutting cоnditions рarameters on surfаce roughness in aluminum alloys (AL-2024)
Volume 15, Issue 3, Summer 2022, Pages 141-146
https://doi.org/10.30772/qjes.v15i3.826
Abdullah Faraj Huayier
Abstract The purpose of this search is to study the main factors on the surface roughness in (AL-2024) using a CNC milling machine for an HSS tool with flat end milling. And by using the Taguchi experience design method to conserve time and costs. To determine the optimal values of surface roughness using Taguchi optimization. We then performed an analysis of variance and regression. Confirmation tests were performed to verify work. The cutting process consists of two stages; the first stage is the cutting process in the upper direction of the cutting, using a coolant and dry cutting. The second stage is the cutting process in the lower direction of the cut, using a coolant and dry cutting the results show the best operating condition to obtain the best surface roughness of the product by using the bottom grinding, measuring the surface process surface roughness using the cutting conditions of the cutter (feeding) = 15 mm/min), (cutting depth = 1 mm) and (cutting speed = 37.68 (m/min) surface roughness (Ra = 0.17 µm) compared with the other value obtained.
INFLUENCES AND OPTIMIZATION OF CNC TURNING MACHINING PARAMETERS
Volume 9, Issue 2, Spring 2016, Pages 200-210
Shukry H. Aghdeab, Baqer Ayad Ahmed, Mohammed Sattar Jabbar, Asaad Ali Abbas
Abstract In this study, the objective is to obtain optimal values of CNC turning parameters (cutting speed, depth of cut and feed rate) which result in an optimal value of surface roughness by machining aluminum shaft. In this work, Taguchi method was carried out on machining of aluminum ENAC-43400 material in dry cutting using CNC turning machine type StarChip 450 equip with carbide cutting tool type DNMG 332. Surface roughness was measured using the POCKET SURF EMD-1500 tester. The results obtained of the surface roughness (Ra) are about (1.14-1.91) μm, and the best was at cutting speed 250 m/min, feed rate 0.05 mm/rev and depth of cut 0.5 mm which is refers to the optimum machining parameters.
PREDICTION OF SURFACE ROUGHNESS IN TURNING MACHINE Using TAGUCHI METHOD
Volume 8, Issue 3, Summer 2015, Pages 326-334
Abbas Fadhil Ibrahim
Abstract This paper investigates the effect of process parameters (approach angle, nose radius, cutting speed and feed rate) on surface roughness in turning machine. The experiments was conducted based on Taguchi’s L8 orthogonal array and assessed with analysis of variance and signal to noise ratio. According to this, it was observed that surface roughness correlates negatively with nose radius and positively with approach angle. The ability of the independent values to predict the dependent values was 95.1% for mean. Minimum surface roughness was predicted as 4.207 μm with approach angle 5°, nose radius 1.5mm, cutting speed of 455 rpm and feed rate of 0.19 mm/rev. From analysis of variance ANOVA, the feed rate was the most significant parameter for minimum surface roughness, cutting speed was next significant parameter for minimum surface roughness, then nose radius, while approach angle was the last.
