scholarly journals Optimal Cutting Condition of Rough Cutting Using Trochoidal Motion

2017 ◽  
Vol 26 (1) ◽  
pp. 13-19
Author(s):  
Ha Yoon Bong ◽  
Moon Ki Kim
Keyword(s):  
Cutting Condition ◽  
Optimal Cutting Condition

scholarly journals Development of the mathematical model for the choice of the optimal cutting condition with combined axial tool

2015 ◽  
Vol 4 (1(24)) ◽  
pp. 69
Author(s):  
Михаил Сергеевич Степанов ◽  
Марина Сергеевна Иванова
Keyword(s):  
Mathematical Model ◽  
Cutting Condition ◽  
Optimal Cutting Condition ◽  
The Mathematical Model

Optimization of Surface Roughness in Dry Turning of Brass

2013 ◽  
Vol 395-396 ◽  
pp. 1035-1039
Author(s):  
On Uma Lasunon
Keyword(s):  
Surface Roughness ◽  
Cutting Tool ◽  
Cutting Speed ◽  
Arithmetic Mean ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Average Surface Roughness ◽  
Dry Turning ◽  
Carbide Cutting Tool ◽  
Optimal Cutting Condition

This study aimed to investigate the effect of cutting speed, feed and depth of cut on the arithmetic mean surface roughness (Ra). The optimal cutting condition in dry turning brass with carbide cutting tool was also recommended. The experimentation was designed by using Taguchi Method (L9). Three investigated factors with 3-level each were cutting speed (42, 68 and 110 m/min), feed (0.05, 0.1 and 0.15 mm/rev), and depth of cut (0.15, 0.25 and 0.5 mm). The results indicated that speed and feed were significantly affected at average surface roughness. The optimal cutting conditions were cutting speed at 68 m/min, feed at 0.05 mm/rev and depth of cut at 0.15 mm.

scholarly journals Selection of Optimal Cutting Condition for Wear, Friction and Lubricant using Hybrid Intelligent System (Dept.M)

2020 ◽  
Vol 33 (1) ◽  
pp. 61-67
Author(s):  
Tawfik El-Midany ◽  
Ibrahim Mohamed Amar ◽  
A. Gad El-Mawla ◽  
N. El-Hamshary ◽  
Ossama Badie Abouelatta
Keyword(s):  
Intelligent System ◽  
Cutting Condition ◽  
Optimal Cutting Condition ◽  
Hybrid Intelligent System ◽  
Wear Friction ◽  
Selection Of

Optimal cutting condition determination for milling thin-walled details

2018 ◽  
Vol 6 (3) ◽  
pp. 280-290 ◽  
Author(s):  
Anton Germashev ◽  
Viktor Logominov ◽  
Dmitri Anpilogov ◽  
Yuri Vnukov ◽  
Vladimir Khristal
Keyword(s):  
Cutting Condition ◽  
Optimal Cutting Condition ◽  
Thin Walled

Effects of Process Parameters on Surface Roughness and MRR in the hard turning of EN 36 steel

2018 ◽  
pp. 102-110
Author(s):  
Amritpal Singh ◽  
Rakesh Kumar
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Hard Turning ◽  
Control Parameter ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Dry Cutting

In the present study, Experimental investigation of the effects of various cutting parameters on the response parameters in the hard turning of EN36 steel under the dry cutting condition is done. The input control parameters selected for the present work was the cutting speed, feed and depth of cut. The objective of the present work is to minimize the surface roughness to obtain better surface finish and maximization of material removal rate for better productivity. The design of experiments was done with the help of Taguchi L9 orthogonal array. Analysis of variance (ANOVA) was used to find out the significance of the input parameters on the response parameters. Percentage contribution for each control parameter was calculated using ANOVA with 95 % confidence value. From results, it was observed that feed is the most significant factor for surface roughness and the depth of cut is the most significant control parameter for Material removal rate.

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