scholarly journals Experimental Investigation into Influence of Lathe Cutting Parameters on Surface Roughness for Ferrous and Non- Ferrous Alloys

2017 ◽  
Vol 3 (4) ◽  
pp. 11
Author(s):  
Asim M Saddique ◽  
Murali R V ◽  
Salim R.K
Keyword(s):  
Surface Roughness ◽  
Experimental Investigation ◽  
Stainless Steel ◽  
Feed Rate ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Cnc Turning ◽  
Stainless Steel 304 ◽  
Turning Center

Optimization of lathe cutting parameters is very important as they form the best suitable conditions for the machining operations. For the efficient use of a CNC Lathe, a set of optimum cutting parameters (speed, feed and depth of cut) is an essential requirement. Surface Roughness, which heavily depends on these cutting parameters, is one of the most frequently used standards to define the quality of turned components. In this work, a correlative study of cutting parameters and the surface roughness for ferrous (stainless steel 304) and non–ferrous alloy (aluminum) material is carried out and presented. Response Surface Methodology (RSM) and Analysis of Variance (ANOVA) techniques are employed to investigate the influence of cutting parameters on surface roughness values. Results from contour plots are obtained to investigate the patterns of factors and the responses. The combination of optimum experimental parameters can be found by machining these ferrous and non-ferrous materials in CNC turning center and finding the least surface roughness parameters. ANOVA analysis, integrated with Design Expert© software, is used to determine effective ratios of the parameters and subsequently the relationships between input parameters and their responses relationship are established. The minimum surface roughness results in reference to spindle rpm, feed rate, and depth of cut are determined and estimation of the optimal surface roughness values (Ra) for least surface roughness are the results obtained in the study. This study presents the findings of an experimental investigation into the effect of turning parameters like cutting speed. Feed rate and depth of cut by turning ferrous (stainless steel 304) and non-ferrous material (Aluminium) in the CNC turning center and then checked the surface roughness values with Mitutoyo SJ-301 instrument. The effects of parameters and their correlation with the surface roughness and the optimal values have been analysed. These results establish a firm relationship and correlation between cutting parameters and surface roughness and in doing so, results also achieve an optimal set of machining parameters for select ferrous and non-ferrous materials.

Effects of Insert Nose Radius and Processing Cutting Parameter on the Surface Roughness of Aisi 316 Stainless Steel

2010 ◽  
Vol 447-448 ◽  
pp. 51-54
Author(s):  
Mohd Fazuri Abdullah ◽  
Muhammad Ilman Hakimi Chua Abdullah ◽  
Abu Bakar Sulong ◽  
Jaharah A. Ghani
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Surface Finish ◽  
Feed Rate ◽  
Cutting Speed ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Aisi 316

The effects of different cutting parameters, insert nose radius, cutting speed and feed rates on the surface quality of the stainless steel to be use in medical application. Stainless steel AISI 316 had been machined with three different nose radiuses (0.4 mm 0.8 mm, and 1.2mm), three different cutting speeds (100, 130, 170 m/min) and feed rates (0.1, 0.125, 0.16 mm/rev) while depth of cut keep constant at (0.4 mm). It is seen that the insert nose radius, feed rates, and cutting speed have different effect on the surface roughness. The minimum average surface roughness (0.225µm) has been measured using the nose radius insert (1.2 mm) at lowest feed rate (0.1 mm/rev). The highest surface roughness (1.838µm) has been measured with nose radius insert (0.4 mm) at highest feed rate (0.16 mm/rev). The analysis of ANOVA showed the cutting speed is not dominant in processing for the fine surface finish compared with feed rate and nose radius. Conclusion, surface roughness is decreasing with decreasing of the feed rate. High nose radius produce better surface finish than small nose radius because of the maximum uncut chip thickness decreases with increase of nose radius.

scholarly journals Green machining for the dry milling process of stainless steel 304

2019 ◽  
Vol 234 (5) ◽  
pp. 881-899 ◽  
Author(s):  
Trung-Thanh Nguyen ◽  
Mozammel Mia ◽  
Xuan-Phuong Dang ◽  
Chi-Hieu Le ◽  
Michael S Packianather
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Energy Consumption ◽  
Power Factor ◽  
Feed Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Dry Machining ◽  
Dry Milling ◽  
Stainless Steel 304

Dry machining represents an eco-friendly method that reduces the environmental impacts, saves energy costs, and protects operator health. This article presents a multi-response optimization which aims to enhance the power factor and decrease the energy consumption as well as the surface roughness for the dry machining of a stainless steel 304. The cutting speed ( V), depth of cut ( a), feed rate ( f), and nose radius ( r) were the processing conditions. The outputs of the optimization are the power factor, energy consumption, and surface roughness. The relationships between inputs and outputs were established using the radial basis function models. The experimental data were normalized, with the use of the Grey relational analysis. The principal component analysis is applied to calculate the weight values of technical responses. The desirability approach is used to observe the optimal values. The results showed that the technical outputs are primarily influenced by the feed rate and cutting speed. The reductions of energy consumption and surface roughness are approximately 34.85% and 57.65%, respectively, and the power factor improves around 28.83%, compared to the initial process parameter settings. The outcomes and findings of the investigated work can be used for further research in sustainable design and manufacturing as well as directly used in the knowledge-based and expert systems for dry milling applications in industrial practices.

Optimization of Cutting Parameters for Turning Operation of Titanium Alloy Ti-6Al-4V Material Workpiece Using the Taguchi Method

2013 ◽  
Vol 685 ◽  
pp. 57-62
Author(s):  
Seyyed Pedram Shahebrahimi ◽  
Abdolrahman Dadvand
Keyword(s):  
Surface Roughness ◽  
Titanium Alloy ◽  
Taguchi Method ◽  
Surface Finish ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Material Tool

One of the most important issues in turning operations is to choose suitable parameters in order to achieve a desired surface finish. The surface finish in machining operation depends on many parameters such as workpiece material, tool material, tool coating, machining parameters, etc. The purpose of this research is to focus on the analysis of optimum cutting parameters to get the lowest surface roughness in turning Titanium alloy Ti-6Al-4V with the insert with the standard code DNMG 110404 under dry cutting condition, by the Taguchi method. The turning parameters are evaluated as cutting speed of 14, 20 and 28 m/min, feed rate of 0.12, 0.14 and 0.16 mm/rev, depth of cut of 0.3, 0.6 and 1 mm, each at three levels. The Experiment was designed using the Taguchi method and 9 experiments were conducted by this process. The results are analyzed using analysis of variance method (ANOVA). The results of analysis show that the depth of cut has a significant role to play in producing lower surface roughness that is about 63.33% followed by feed rate about 30.25%, and cutting speed has less contribution on the surface roughness. Also it was realized that with the use of the confirmation test, the surface roughness improved by 227% from its initial state.

Optimization of Surface Roughness in Turning Operation Using Firefly Algorithm

2015 ◽  
Vol 815 ◽  
pp. 268-272 ◽  
Author(s):  
Nur Farahlina Johari ◽  
Azlan Mohd Zain ◽  
Noorfa Haszlinna Mustaffa ◽  
Amirmudin Udin
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Firefly Algorithm ◽  
Volume Fraction ◽  
Optimization Problems ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Machining Time

Recently, Firefly Algorithm (FA) has become an important technique to solve optimization problems. Various FA variants have been developed to suit various applications. In this paper, FA is used to optimize machining parameters such as % Volume fraction of SiC (V), cutting speed (S), feed rate (F), depth of cut (D) and machining time (T). The optimal machining cutting parameters estimated by FA that lead to a minimum surface roughness are validated using ANOVA test.

Surface Roughness Optimization of some Machining Parameters in Turning Operations Using Taguchi Method

2009 ◽  
Vol 62-64 ◽  
pp. 613-620 ◽  
Author(s):  
Ishaya Musa Dagwa
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Signal To Noise Ratio ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Confirmatory Test ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Turning Operations ◽  
Factors Affecting

In this study, an attempt has been made to optimize cutting parameters (cutting speed, depth of cut, and feed rate) in conventional turning operations. A Taguchi orthogonal array (L933) was used in surface roughness optimization of a solid round bar of mild steel material. The experimental runs were randomized; two skilled machinists were involved in the turning operation using the same machining parameters. ANOVA analysis was performed to identify the percentage contribution of the factors affecting surface roughness during machining. The optimal cutting combination was determined by using the signal-to-noise ratio and the following results were obtained; speed (level 2) = 55.m/min, depth of cut (level 3) = 0.08mm, and feed rate (levels 3) = at 0.08mm/rev. A prediction of surface roughness was carried out using the optimal setting followed by a confirmatory test on the lathe. The result shows that the confirmatory runs compared favourably (96.44%) with the predicted surface roughness.

Effect of Machining Parameters on Surface Integrity in Dry Turning of Inconel 718

2013 ◽  
Vol 634-638 ◽  
pp. 2831-2834
Author(s):  
Xiao Li Zhu ◽  
Jin Fa Zhang ◽  
Wu Jun Chen ◽  
Ji Wen Deng
Keyword(s):  
Surface Roughness ◽  
Residual Stresses ◽  
Surface Integrity ◽  
Feed Rate ◽  
Inconel 718 ◽  
Cutting Speed ◽  
Diffraction Method ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Machining Parameters

Surface quality including residual stresses and surface roughness due to turning operations in Inconel 718 were studied as a function of cutting speed, feed rate and depth of cut. By means of X-ray radiation diffraction method, the influence of cutting parameters on residual stress was investigated. The results show that dry cutting of Inconel 718 resulted in predominantly tensile residual stresses at the machined surface and the surface roughness increased with the increase of cutting parameters.The effects of the cutting parameters on surface integrity are investigated while employing the range analysis. From these results it was possible to select a combination of cutting speed, feed rate and depth of cut that generate favorable surface characteristics.

scholarly journals Effect of Cutting Insert Type on Surface Roughness of Hardened AISI 420 Stainless Steel

2021 ◽  
Vol 4 (1) ◽  
pp. 171-185
Author(s):  
Anıl Berk Dalkıran ◽  
Furkan Yılmaz ◽  
Samet Emre Bilim
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Feed Rate ◽  
Cutting Speed ◽  
High Strength ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Aisi 420 ◽  
Cutting Insert ◽  
Coated Carbide

AISI 420 stainless steel is one of the alloys that can be used in various applications due to its malleability, high strength, and weldability. In this study, the effects of cutting parameters (feed rate, depth of cut, and cutting speed) on the surface roughness were investigated during the turning of AISI 420 under dry test conditions using coated carbide and ceramic cutting inserts. Response surface methodology, analysis of variance, and statistical methods of the main effect plot were applied to investigate the effects of input parameters on response values. The results of this study showed that feed rate followed by the depth of cut had the most significant effect on output parameters. According to the experimental data, as the feed rate and depth of cut increase, the surface roughness increases.

scholarly journals Analysis of Surface Roughness and Cutting Forces in Hard Turning of 42CrMo4 Steel using Taguchi and RSM Method

Mechanika ◽  
2020 ◽  
Vol 26 (3) ◽  
pp. 231-241 ◽  
Author(s):  
Mustafa ÖZDEMİR ◽  
Mehmet Tuncay KAYA ◽  
Hamza Kemal AKYILDIZ
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Forces ◽  
Tangential Force ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Radial Force ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Feed Force

In this study, effects of cutting speed (V), feed rate (f), depth of cut (a) and tool tip radius (R) on  surface roughness (Ra, Rz, and Rt) and cutting forces (radial force (Fx), tangential force (Fy), and feed force (Fz)) in hard finish turning processes of hardened 42CrMo4 (52 HRC) material was investigated experimentally. Taguchi’s mixed level parameter design (L18) is used for the experimental design (2x1,3x3). The signal-to-noise ratio (S/N) was used in the evaluation of test results.  By using Taguchi method, cutting parameters giving optimum surface roughness and cutting forces were determined. Regression analyses are applied to predict surface roughness and cutting forces. Analysis of variance (ANOVA) is used to determine the effects of the machining parameters on surface roughness and cutting forces. According to ANOVA analysis, the most important cutting parameters were found to be feed rate for surface roughness and depth of cut among cutting forces.  By conducting validation experiments, optimization was seen to be applied successfully.

scholarly journals Effect of Cutting Parameters on Machinability of Hardened AISI 52100 Bearing Steel

2020 ◽  
Vol 3 (1) ◽  
pp. 474-481
Author(s):  
Mohammad Rafighi
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Bearing Steel ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Manufacturing Cost ◽  
Machining Parameters ◽  
Aisi 52100

In this study, the effects of machining parameters, namely feed rate, cutting speed and depth of cut on the surface roughness was investigated experimentally in hard turning of AISI 52100 bearing steel using cubic boron nitride insert under dry cutting condition. Taguchi method was utilized to reduce the number of trials to 9 for saving the time and manufacturing cost. The significant factor on the surface roughness was determined using analysis of variance. Furthermore, the optimum cutting parameter for reducing the surface roughness was obtained. The findings showed that the feed rate has the highest impact on surface roughness among any other cutting parameters, with 88.32% contribution.

Studying The Effect of a New Mixed Cutting Fluid on Surface Roughness

2020 ◽  
Vol 38 (11A) ◽  
pp. 1593-1601
Author(s):  
Mohammed H. Shaker ◽  
Salah K. Jawad ◽  
Maan A. Tawfiq
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Cutting Parameters ◽  
Machining Process ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Cutting Fluids ◽  
Machining Processes ◽  
Dry Cutting ◽  
Cutting Speeds

This research studied the influence of cutting fluids and cutting parameters on the surface roughness for stainless steel worked by turning machine in dry and wet cutting cases. The work was done with different cutting speeds, and feed rates with a fixed depth of cutting. During the machining process, heat was generated and effects of higher surface roughness of work material. In this study, the effects of some cutting fluids, and dry cutting on surface roughness have been examined in turning of AISI316 stainless steel material. Sodium Lauryl Ether Sulfate (SLES) instead of other soluble oils has been used and compared to dry machining processes. Experiments have been performed at four cutting speeds (60, 95, 155, 240) m/min, feed rates (0.065, 0.08, 0.096, 0.114) mm/rev. and constant depth of cut (0.5) mm. The amount of decrease in Ra after the used suggested mixture arrived at (0.21µm), while Ra exceeded (1µm) in case of soluble oils This means the suggested mixture gave the best results of lubricating properties than other cases.

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