scholarly journals Optimization of Cutting Speed and Feed Rate on Surface Roughness and Vibration using Taguchi Method: A Review

2020 ◽  
Vol 1 (2) ◽  
pp. 43
Author(s):  
Mohammad Ilham ◽  
Suparjon Suparjon ◽  
Yudistira Sanjiwani
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Feed Rate ◽  
Machine Tools ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Dominant Factor ◽  
Workpiece Surface ◽  
Material Hardness ◽  
Machining Operations

<span lang="EN-ID">The result of a turning process is strongly influenced by the process parameters that could result in the product to be unacceptable. The cutting parameters may be determined according to the material hardness and roughness of the workpiece surface. The purpose of this paper is to investigate the effects of cutting speed and feed rate on surface roughness and vibration. In Taguchi method, the number of experiments is reduced by orthogonal arrays while  the effects of uncontrollable factors are also also reduced. The Taguchi method is used to reduce track, experimental time and production cost. Simple and precise are the most benefits of this method. Unstable vibrations in machining operations, known as chats, can cause damage to tools, workpieces, and machine tools. Cutting force is found to be the most dominant factor affecting surface roughness.</span>

scholarly journals Experimental Investigation on Surface Roughness and Tool Wear in Dry Machining of TiC Reinforced Aluminium LM6 Composite

2013 ◽  
Vol 773-774 ◽  
pp. 339-347 ◽  
Author(s):  
Muhammad Yusuf ◽  
M.K.A. Ariffin ◽  
N. Ismail ◽  
S. Sulaiman
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Carbide Tool ◽  
Dry Machining ◽  
Workpiece Surface ◽  
High Cutting Speed

With increasing quantities of applications of Metal Matrix Composites (MMCs), the machinablity of these materials has become important for investigation. This paper presents an investigation of surface roughness and tool wear in dry machining of aluminium LM6-TiC composite using uncoated carbide tool. The experiments carried out consisted of different cutting models based on combination of cutting speed, feed rate and depth of cut as the parameters of cutting process. The cutting models designed based on the Design of Experiment Response Surface Methodology. The objective of this research is finding the optimum cutting parameters based on workpiece surface roughness and cutting tool wear. The results indicated that the optimum workpiece surface roughness was found at high cutting speed of 250 m min-1 with various feed rate within range of 0.05 to 0.2 mm rev-1, and depth of cut within range of 0.5 to 1.5 mm. Turning operation at high cutting speed of 250 m min-1 produced faster tool wear as compared to low cutting speed of 175 m min-1 and 100 m min-1. The wear minimum (VB = 42 μm ) was found at cutting speed of 100 m min-1, feet rate of 0.2 mm rev-1, and depth of cut of 1.0 mm until the length of cut reached 4050 mm. Based on the results of the workpiece surface roughness and the tool flank wear, recommended that turning of LM6 aluminium with 2 wt % TiC composite using uncoated carbide tool should be carried out at cutting speed higher than 175 m min-1 but at feed rate of less than 0.05 mm rev-1 and depth of cut less than 1.0 mm.

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.

scholarly journals Modeling and optimization of face milling process parameters for AISI 4140 steel

2018 ◽  
Vol 12 (1) ◽  
pp. 5-10 ◽  
Author(s):  
Gokhan Basar ◽  
Funda Kahraman
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Performance Characteristics ◽  
Depth Of Cut ◽  
Aisi 4140 Steel ◽  
Control Factors ◽  
Aisi 4140

In this study, the effect of cutting parameters such as the depth of cut, feed rate, cutting speed and the number of inserts on surface roughness were investigated in the milling of the AISI 4140 steel. The optimal control factors for surface quality were detected by using the Taguchi technique. Experimental trials were designed according to the Taguchi L18 (21x33) orthogonal array. The statistical effects of control factors on surface roughness have been established by using the analysis of variance (ANOVA). Optimal cutting parameters were obtained by using the S/N ratio values. The ANOVA results showed that the effective factors were the number of inserts and the feed rate on surface roughness. However, the depth of cut and the cutting speed showed an insignificant effect. Additionally, the First-order and Second-order regression analysis were conducted to estimate the performance characteristics of the experiment. The acquired regression equation results matched with the surface roughness measurement results. The optimal performance characteristics were obtained as a 0.5 mm depth of cut, 0.08 mm/rev feed rate, 325 m/min cutting speed and 1 number of inserts by using the Taguchi method. Additionally, the confirmation test results indicated that the Taguchi method was very prosperous in the optimization of the machining parameters to obtain the minimum surface roughness in the milling of the AISI 4140 steel.

scholarly journals Optimization with Taguchi Method of Influences on Surface Roughness of Cutting Parameters in CNC Turning Processing

Mechanika ◽  
2019 ◽  
Vol 25 (5) ◽  
pp. 397-405
Author(s):  
Mustafa özdemir
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Cnc Machine ◽  
Control Factors ◽  
Steel Material ◽  
Validation Tests

In this study, the effect of cutting speed, feed rate, and depth of cut on surface roughness was experimentally examined in the processing of AISI 409 (ferritic chromium stainless steel) material. As cutting parameters, three cutting speeds (200, 300, and 400 m/min), three feed rates (0.1, 0.2, and 0.3 mm/rev), and three depths of cut (1, 2 and 3 mm) were selected. Turning tests in CNC machine were made according to Taguchi L27 orthogonal array and the signal/noise (S/N) ratios were used in the evaluation of the experimental results. By using Taguchi method, cutting parameters giving the optimum surface roughness (Ra and Rz) values were determined. The effect of control factors on the results was found with the help of Analysis of Variance (ANOVA). According to ANOVA results, the most important parameters affecting the surface roughness were determined as feed rate, depth of cut, and cutting speed, respectively. By conducting validation tests, the optimization was observed to be applied successfully.

OPTIMIZATION OF THE MACHINING PARAMETERS IN TURNING OF HARDENED HOT WORK TOOL STEEL USING CRYOGENICALLY TREATED TOOLS

2019 ◽  
Vol 27 (05) ◽  
pp. 1950177 ◽  
Author(s):  
ENGIN NAS ◽  
NURSEL ALTAN ÖZBEK
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Tool Steel ◽  
Feed Rate ◽  
Flank Wear ◽  
Cutting Speed ◽  
Gray Relational Analysis ◽  
Dominant Factor ◽  
Relational Analysis ◽  
Hot Work Tool Steel

This paper addresses an approach based on the Taguchi method with gray relational analysis for optimizing the turning parameters of hardened DIN 1.2344 hot work tool steel (54 HRC) with multiple performance characteristics. A gray relational grade obtained from the gray relational analysis was used for the performance characteristic in the Taguchi method L[Formula: see text] (2[Formula: see text]. The optimal turning parameters for surface roughness and tool wear were determined using the parameter design proposed by the Taguchi method. Dry turning tests were carried out using cryogenically treated and untreated uncoated carbide cutting tools. The cutting tool (Untreated and Deep Cryogenic Treated), cutting speed (200, 250 and 300[Formula: see text]m/min) and feed rate (0.09, 0.12 and 0.15[Formula: see text]mm/rev) were selected as experiment parameters. The analysis results revealed that the feed rate (72.84%) was the dominant factor affecting surface roughness and the cutting speed (93.93%) was the dominant factor affecting flank wear. The optimum turning parameters for the lowest Ra values were A2B1C2 and for the lowest Vb values were A1B3C2. According to the results of gray relational analysis, the optimum parameters for minimum average surface roughness and minimum flank wear were A1B2C2.

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.

Statistical Study and Multi-Response Optimization of Cutting Parameters for Dry Turning Stainless Steel AISI 316L Using Cermet Tool

2020 ◽  
Vol 36 ◽  
pp. 28-46
Author(s):  
Youssef Touggui ◽  
Salim Belhadi ◽  
Salah Eddine Mechraoui ◽  
Mohamed Athmane Yallese ◽  
Mustapha Temmar
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Aisi 316L ◽  
Cutting Power ◽  
Dry Turning ◽  
Optimization Of Cutting Parameters

Stainless steels have gained much attention to be an alternative solution for many manufacturing industries due to their high mechanical properties and corrosion resistance. However, owing to their high ductility, their low thermal conductivity and high tendency to work hardening, these materials are classed as materials difficult to machine. Therefore, the main aim of the study was to examine the effect of cutting parameters such as cutting speed, feed rate and depth of cut on the response parameters including surface roughness (Ra), tangential cutting force (Fz) and cutting power (Pc) during dry turning of AISI 316L using TiCN-TiN PVD cermet tool. As a methodology, the Taguchi L27 orthogonal array parameter design and response surface methodology (RSM)) have been used. Statistical analysis revealed feed rate affected for surface roughness (79.61%) and depth of cut impacted for tangential cutting force and cutting power (62.12% and 35.68%), respectively. According to optimization analysis based on desirability function (DF), cutting speed of 212.837 m/min, 0.08 mm/rev feed rate and 0.1 mm depth of cut were determined to acquire high machined part quality

scholarly journals Investigations on Surface Roughness and Tool Wear Characteristics in Micro-Turning of Ti-6Al-4V Alloy

Materials ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 2998 ◽  
Author(s):  
Kubilay Aslantas ◽  
Mohd Danish ◽  
Ahmet Hasçelik ◽  
Mozammel Mia ◽  
Munish Gupta ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Removal Rate ◽  
Cutting Speed ◽  
Small Diameter ◽  
Cutting Parameters ◽  
Ti6al4v Alloy ◽  
Depth Of Cut ◽  
Turning Process ◽  
Micro Turning

Micro-turning is a micro-mechanical cutting method used to produce small diameter cylindrical parts. Since the diameter of the part is usually small, it may be a little difficult to improve the surface quality by a second operation, such as grinding. Therefore, it is important to obtain the good surface finish in micro turning process using the ideal cutting parameters. Here, the multi-objective optimization of micro-turning process parameters such as cutting speed, feed rate and depth of cut were performed by response surface method (RSM). Two important machining indices, such as surface roughness and material removal rate, were simultaneously optimized in the micro-turning of a Ti6Al4V alloy. Further, the scanning electron microscope (SEM) analysis was done on the cutting tools. The overall results depict that the feed rate is the prominent factor that significantly affects the responses in micro-turning operation. Moreover, the SEM results confirmed that abrasion and crater wear mechanism were observed during the micro-turning of a Ti6Al4V alloy.

A Prediction Model of Surface Roughness in Micro End Milling

2015 ◽  
Vol 727-728 ◽  
pp. 354-357
Author(s):  
Mei Xia Yuan ◽  
Xi Bin Wang ◽  
Li Jiao ◽  
Yan Li
Keyword(s):  
Surface Roughness ◽  
Prediction Model ◽  
Feed Rate ◽  
End Milling ◽  
Orthogonal Experiment ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Micro Milling ◽  
Cutting Depth ◽  
Micro End Milling

Micro-milling orthogonal experiment of micro plane was done in mesoscale. Probability statistics and multiple regression principle were used to establish the surface roughness prediction model about cutting speed, feed rate and cutting depth, and the significant test of regression equation was done. On the basis of successfully building the prediction model of surface roughness, the diagram of surface roughness and cutting parameters was intuitively built, and then the effect of the cutting speed, feed rate and cutting depth on the small structure surface roughness was obtained.

Estimation of fractal dimension and surface roughness based on material characteristics and cutting conditions in the end milling of carbon steels

2015 ◽  
Vol 231 (8) ◽  
pp. 1423-1437 ◽  
Author(s):  
Xue Zuo ◽  
Hua Zhu ◽  
Yuankai Zhou ◽  
Jianhua Yang
Keyword(s):  
Surface Roughness ◽  
Fractal Dimension ◽  
Feed Rate ◽  
End Milling ◽  
Cutting Parameters ◽  
Carbon Steels ◽  
Spindle Speed ◽  
Numerical Control ◽  
Material Hardness ◽  
Milled Surface

Cutting parameters and material properties have important effects on the quality of milled surface, which can be characterized by fractal dimension and surface roughness. The relationships between two surface parameters (surface roughness and fractal dimension) and material hardness, elongation, spindle speed and feed rate were investigated, respectively, in this study. Four carbon steels, that is, AISI 1020, Gr 50, 1045 and 1566, were milled with five spindle speeds and four feed rates on a computer numerical control machine. The surface topographies were measured with a three-dimensional profiler. The surface profiles were obtained by re-sampling the data points on the surface topography in the measurement direction. The surface roughness and fractal dimension were calculated from the two-dimensional profiles, where the fractal dimension was obtained by the root-mean-square method. The results showed that for specific spindle speed and feed rate, the roughness of the milled surface decreased with the workpiece hardness, whereas the elongation and fractal dimension increased with the hardness. Based on the material hardness and elongation, spindle speed and feed rate, empirical formulae were established to quantitatively estimate the surface roughness and fractal dimension. Moreover, the spindle speed and feed rate can be easily calculated from the empirical formulae to achieve a surface with the desired surface roughness and fractal dimension. The empirical formulae have been demonstrated with the experiments and were shown to be applicable in estimating the surface roughness and fractal dimension for all carbon steels in end milling. The results are instructive for the fractal dimension estimation of the machined surfaces of carbon steel, which has not been previously studied.

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