scholarly journals Machining Parameter optimization by using Taguchi Technique for CNC turning of Grade T6 Aluminium alloy

2019 ◽  
Vol 9 (2) ◽  
pp. 2458-2461
Keyword(s):  
Surface Roughness ◽  
Aluminium Alloy ◽  
Parameter Optimization ◽  
Surface Finish ◽  
Cutting Speed ◽  
Process Parameter ◽  
Depth Of Cut ◽  
Taguchi Technique ◽  
Cnc Turning ◽  
Machining Parameter

With the increase in demand for producing products with good surface finish within reduced time. Selection of suitable parameters for machining in CNC lathe is much required from the operator’s point of view. To attain the desired parameters this study deals taguchi technique as a tool in process parameter optimization using carbon insert CNMG tool in turning of AA6063 alloy. L9 orthogonal array is selected for conducting the experiments and for this Feed, Cutting Speed, Depth of Cut are the process parameters. The ANOVA and S-N ratio is used to analyse the characteristic performance of the turning operation performed. From the results of ANOVA the most influential parameter in reducing the surface roughness is found as depth of cut. Finally for various process parameter combinations the surface roughness is calculated and the optimum parameter for machining is attained by using Taguchi. For authentication of the optimum output attained in optimization experiments have been conducted to get maximum surface finish when machining the aluminium alloy in CNC turning

scholarly journals Optimization of process parameters in turning of nuclear graded steel alloy (AISI-410) for sustainable manufacture

2021 ◽  
Vol 9 ◽  
Author(s):  
Anis Fatima ◽  
◽  
Muhammad Wasif ◽  
Muhammad Omer Mumtaz ◽  
◽  
...  
Keyword(s):  
Surface Roughness ◽  
Statistical Model ◽  
Surface Finish ◽  
Metal Cutting ◽  
Functional Performance ◽  
Cutting Speed ◽  
Dimensional Accuracy ◽  
Process Parameter ◽  
Depth Of Cut ◽  
Work Piece

Metal cutting operations involve intense heat generation owing to plastic deformation of the work piece and due to friction at the tool-work piece and tool-chip interface. The heat generated in metal cutting unfavourably affects the quality and thus the functional performance of the product. It is known that quality and functional performance is the function of roughness and dimensional accuracy. To maintain a longer component life, along with the robust material choice, a component should have good surface finish and dimensional accuracy. While, for the organization to monitor and control their environmental issues in a holistic manner, emphasis in adopting eco-friendly practices and protecting environment has been growing continuously across all the business sectors. In this study, an attempt is made to optimize the process parameter of stainless steel AISI-410 alloy, a nuclear graded material, for better surface finish. For this, Taguchi L9 orthogonal array was utilise to identify the process parameter and cutting environment. Analysis of variance (ANOVA) was also conducted to highlight the significant parameter that affects the surface finish most. A statistical model to forecast the surface roughness was also developed and was validated by an experiment with a maximum error of 12%. Results indicates that feed rate is the most critical factor that effects the surface roughness with the contribution of 91.5%, followed by environment with 5.22% contribution, cutting speed and depth of cut with 2.7 % and 0.4 % respectively. The correlation coefficient of 0.9213 and conformation tests reveals that developed statistical model predicts surface roughness with the statistical error limit.

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.

OPTIMISING CUTTING PARAMETERS FOR HOT TURNING ON EN31 MATERIAL

2021 ◽  
Vol 5 (10) ◽  
Author(s):  
Prof. Hemant k. Baitule ◽  
Satish Rahangdale ◽  
Vaibhav Kamane ◽  
Saurabh Yende
Keyword(s):  
Surface Roughness ◽  
Surface Finish ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Machining Process ◽  
Depth Of Cut ◽  
Multiple Time ◽  
Turning Process ◽  
Workpiece Material ◽  
Hot Turning

In any type of machining process the surface roughness plays an important role. In these the product is judge on the basis of their (surface roughness) surface finish. In machining process there are four main cutting parameter i.e. cutting speed, feed rate, depth of cut, spindle speed. For obtaining good surface finish, we can use the hot turning process. In hot turning process we heat the workpiece material and perform turning process multiple time and obtain the reading. The taguchi method is design to perform an experiment and L18 experiment were performed. The result is analyzed by using the analysis of variance (ANOVA) method. The result Obtain by this method may be useful for many other researchers.

Surface Roughness and Chip Formation of AlSi/AIN Metal Matrix Composite by End Milling Machining using the Taguchi Method

2014 ◽  
Vol 68 (4) ◽  
Author(s):  
M. S. Said ◽  
J. A. Ghani ◽  
R. Othman ◽  
M. A. Selamat ◽  
N. N. Wan ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Matrix Composite ◽  
Surface Finish ◽  
Chip Formation ◽  
End Milling ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Taguchi Optimization ◽  
Cutting Speeds

The purpose of this research is to demonstrate surface roughness and chip formation by the machining of Aluminium silicon alloy (AlSic) matrix composite, reinforced with aluminium nitride (AlN), with three types of carbide inserts present. Experiments were conducted at various cutting speeds, feed rates, and depths of cut, according to the Taguchi method, using a standard orthogonal array L9 (34). The effects of cutting speeds, feed rates, depths of cut, and types of tool on surface roughness during the milling operation were evaluated using Taguchi optimization methodology, using the signal-to-noise (S/N) ratio. The surface finish produced is very important in determining whether the quality of the machined part is within specification and permissible tolerance limits. It is understood that chip formation is a fundamental element that influences tool performance. The analysis of chip formation was done using a Sometech SV-35 video microscope. The analysis of results, using the S/N ratio, concluded that a combination of low feed rate, low depth of cut, medium cutting speed, and an uncoated tool, gave a remarkable surface finish. The chips formed from the experiment varied from semi–continuous to discontinuous. 

Effect of machining parameters on the surface finish of a metal matrix composite under dry cutting conditions

2015 ◽  
Vol 231 (6) ◽  
pp. 913-923 ◽  
Author(s):  
Brian Boswell ◽  
Mohammad Nazrul Islam ◽  
Ian J Davies ◽  
Alokesh Pramanik
Keyword(s):  
Surface Roughness ◽  
Metal Matrix Composite ◽  
Tool Life ◽  
Surface Finish ◽  
Feed Rate ◽  
Metal Matrix ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Dry Cutting

The machining of aerospace materials, such as metal matrix composites, introduces an additional challenge compared with traditional machining operations because of the presence of a reinforcement phase (e.g. ceramic particles or whiskers). This reinforcement phase decreases the thermal conductivity of the workpiece, thus, increasing the tool interface temperature and, consequently, reducing the tool life. Determining the optimum machining parameters is vital to maximising tool life and producing parts with the desired quality. By measuring the surface finish, the authors investigated the influence that the three major cutting parameters (cutting speed (50–150 m/min), feed rate (0.10–0.30 mm/rev) and depth of cut (1.0–2.0 mm)) have on tool life. End milling of a boron carbide particle-reinforced aluminium alloy was conducted under dry cutting conditions. The main result showed that contrary to the expectations for traditional machined alloys, the surface finish of the metal matrix composite examined in this work generally improved with increasing feed rate. The resulting surface roughness (arithmetic average) varied between 1.15 and 5.64 μm, with the minimum surface roughness achieved with the machining conditions of a cutting speed of 100 m/min, feed rate of 0.30 mm/rev and depth of cut of 1.0 mm. Another important result was the presence of surface microcracks in all specimens examined by electron microscopy irrespective of the machining condition or surface roughness.

scholarly journals Optimization of machining parameters in face milling using multi-objective Taguchi technique

2018 ◽  
Vol 12 (2) ◽  
pp. 104-108 ◽  
Author(s):  
Yusuf Fedai ◽  
Hediye Kirli Akin
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Taguchi Technique ◽  
Average Roughness ◽  
Multi Objective ◽  
Control Factors ◽  
Average Maximum

In this research, the effect of machining parameters on the various surface roughness characteristics (arithmetic average roughness (Ra), root mean square average roughness (Rq) and average maximum height of the profile (Rz)) in the milling of AISI 4140 steel were experimentally investigated. Depth of cut, feed rate, cutting speed and the number of insert were considered as control factors; Ra, Rz and Rq were considered as response factors. Experiments were designed considering Taguchi L9 orthogonal array. Multi signal-to-noise ratio was calculated for the response variables simultaneously. Analysis of variance was conducted to detect the significance of control factors on responses. Moreover, the percent contributions of the control factors on the surface roughness were obtained to be the number of insert (71.89 %), feed (19.74 %), cutting speed (5.08%) and depth of cut (3.29 %). Minimum surface roughness values for Ra, Rz and Rq were obtained at 325 m/min cutting speed, 0.08 mm/rev feed rate, 1 number of insert and 1 mm depth of cut by using multi-objective Taguchi technique.

Technological Investigation of Effect of Machining Parameter on Tool Life

2020 ◽  
Vol 22 (4) ◽  
pp. 41-53
Author(s):  
Manojkumar Sheladiya ◽  
◽  
Shailee Acharya ◽  
Ghanshyam Acharya ◽  
◽  
...  
Keyword(s):  
Surface Roughness ◽  
Mild Steel ◽  
Tool Life ◽  
Flank Wear ◽  
Cutting Speed ◽  
Numerical Control ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Machining Time ◽  
Machining Parameter

Introduction. The machinability is typical criteria to be investigated and different authors suggested different parameters describing its quantification. Different parameters i. e. speed, feed, depth of cut, tool work-piece combination, machine types and its condition, cutting fluid, machinist expertise, etc. are contributing directly to the tool life. The selection of the tool for the machining impacts greatly on the economic viability of the machining in terms of energy usage and tooling costs. The method of investigation. The current research emphasis mainly on tool life investigation when machining the mild steel specimens ISRO 50, BIS 1732:1989 at constant cutting speed i.e. 200 m / min. In the industries the mild steel material is commonly used for various products manufacturing. Considering the high demands on productivity and surface finish, machining at 200 m / min is the preferred. The computerized numerical control machine (CNC DX-150) is used for the turning. The four corner insert (TNMG 120408) is used for different machining times i.e. 10, 15, 20 and 25 minutes respectively. The flank wear of the tool is measured with calibrated optical microscope. The temperature of the tool corner during machining is continuously measured for possible impact of temperature on bonding properties of the tool insert and impact on red hardness. Results and discussion. The plot of flank wear vs. machining time will give the value of tool life. The other quality output parameter, such as surface roughness, is measured after machining, indicating surface irregularities in root means square value. Efforts have been made to identify the relationship of tool life, machining time, the quantity of metal removed, surface roughness, and tool bit temperature.

scholarly journals The Experimental Investigation of Surface Roughness After Dry Turning of Steel S235

2019 ◽  
Vol 26 (4) ◽  
pp. 179-184
Author(s):  
Justyna Molenda
Keyword(s):  
Surface Roughness ◽  
Surface Finish ◽  
Cutting Speed ◽  
Scientific Work ◽  
Machining Process ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Workpiece Material ◽  
Important Indicator

AbstractNowadays lot of scientific work inspired by industry companies was done with the aim to avoid the use of cutting fluids in machining operations. The reasons were ecological and human health problems caused by the cutting fluid. The most logical solution, which can be taken to eliminate all of the problems associated with the use of cooling lubricant, is dry machining. In most cases, however, a machining operation without lubricant finds acceptance only when it is possible to guarantee that the part quality and machining times achieved in wet machining are equalled or surpassed. Surface finish has become an important indicator of quality and precision in manufacturing processes and it is considered as one of the most important parameter in industry. Today the quality of surface finish is a significant requirement for many workpieces. Thus, the choice of optimized cutting parameters is very important for controlling the required surface quality. In the present study, the influence of different machining parameters on surface roughness has been analysed. Experiments were conducted for turning, as it is the most frequently used machining process in machine industry. All these parameters have been studied in terms of depth of cut (ap), feed rate (f) and cutting speed (vc). As workpiece, material steel S235 has been selected. This work presents results of research done during turning realised on conventional lathe CDS 6250 BX-1000 with severe parameters. These demonstrate the necessity of further, more detailed research on turning process results.

scholarly journals Optimization of CNC Turning Parameters in Machining EN19 using Face Centered Central Composite Design Based RSM

2020 ◽  
Vol 9 (2) ◽  
pp. 889-896
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Removal Rate ◽  
Cutting Speed ◽  
Vital Role ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Cnc Turning ◽  
Software Analysis ◽  
Central Composite

Manufacturing a defect free (quality) product is playing a vital role in today’s globally competitive, customer oriented era. Meeting the demand of the market by producing sufficient quantity is another challenge. Achieving greater production rates without compromising on quality, increases the complexity of the task. Adopting modern manufacturing methods like CNC turning are essential to meet the above requirements. EN19 is an important member in the family of alloy steels, which has a wide variety of applications in automobile and machine tool industries. Optimization of machining parameters is crucial in obtaining the required outputs such as quality and productivity. In this work, optimization of CNC turning parameters for machining EN19 alloy steel is performed. The number of experiments was designed using face centred central composite based response surface methodology with varied independent process parameters namely cutting speed, feed and depth of cut. After designing the experiments, the performance measures such as surface roughness of the test samples and Material Removal Rate (MRR) is calculated using the existing formulae. The influence of parameters on MRR and surface roughness are determined by analysis of variance (ANOVA) and for significance interactions of the process parameters are also considered. Using MINITAB 17 software analysis is performed. Further, regression analysis has been done and second order mathematical model is obtained. Using desirability approach, optimization is carried out.

EFFECT OF MACHINING PARAMETERS ON SURFACE ROUGHNESS FOR ALUMINIUM MATRIX COMPOSITE BY USING TAGUCHI METHOD WITH DECISION TREE ALGORITHM

2021 ◽  
pp. 2150021
Author(s):  
P. RAVEENDRAN ◽  
S. V. ALAGARSAMY ◽  
M. RAVICHANDRAN ◽  
M. MEIGNANAMOORTHY
Keyword(s):  
Surface Roughness ◽  
Decision Tree ◽  
Taguchi Method ◽  
Cutting Speed ◽  
Experimental Result ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Cnc Turning ◽  
Cnc Turning Process ◽  
Taguchi’S Design Of Experiments

The intend of this research work is to explore the effect of various parameters in a CNC turning process like cutting speed ([Formula: see text]), feed ([Formula: see text]), and depth of cut ([Formula: see text]) on surface roughness (Ra) of turning AA7075 filled with 10[Formula: see text]wt.% of TiO2 composite fabricated through stir casting method. Taguchi method and decision tree (DT) algorithm were utilized to foresee the surface roughness (Ra) of the proposed composite. The microstructure of composite was ensured with the presence of TiO2 particles dispersed in a homogeneous manner within the matrix material. The machining of composite was carried out by using the CNC turning center and tungsten carbide insert as tool material. This experimental work was designed on L27 (33) orthogonal array using Taguchi’s design of experiments. From its signal-to-noise (S/N) ratio study, the minimum surface roughness (Ra) was obtained at the optimum level of parameters with the cutting speed at 1500[Formula: see text]rpm, feed at 0.15[Formula: see text]mm/rev and depth of cut at 0.3[Formula: see text]mm. Analysis of variance (ANOVA) and decision tree (DT) algorithm were used to identify the significant effect of parameters. The experimental result shows that depth of cut was the major significant parameter on surface roughness (Ra) when compared to cutting speed and feed.

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