The Effects of Cutting Speed and Depth of Cut on Machinability Characteristics of Austempered Ductile Iron

2012 ◽  
Vol 134 (2) ◽  
Author(s):  
Ahmet Akdemir ◽  
Şakir Yazman ◽  
Hacı Saglam ◽  
Mesut Uyaner
Keyword(s):  
Surface Roughness ◽  
Ductile Iron ◽  
Flank Wear ◽  
Tangential Force ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Salt Bath ◽  
Austempered Ductile Iron ◽  
Dominant Factor ◽  
Depth Of Cut

Ductile iron can acquire enhanced thermal and mechanical properties from austempering heat treatment. The present study aims to identify the function of different cutting parameters affecting machinability and to quantify its effects. Turning was performed to test machinability according to the ISO3685-1993 (E) standard. After austenitizing at 900 °C for 90 min, austempered ductile iron (ADI) specimens were quenched in a salt bath at 380 °C for 90 min. The cutting force signals along three directions were measured in real time, whereas flank wear and surface roughness were measured offline. For the cutting parameters, the cutting speed and depth of cut were varied, but the feed rate was kept constant. In the flank wear tests, machining length was corresponded to tool life. In addition, in order to find out the effect of cutting parameters on surface roughness (Ra), tangential force (Ft), and flank wear (VB) during turning, response surface methodology (RSM) was utilized by using experimental data. The effect of the depth of cut on the surface roughness was negligible but considerable in the cutting forces. The increased cutting speed produced a positive effect on surface roughness. It is found that the cutting speed was the dominant factor on the surface roughness, tangential force, and flank wear.

Evaluation of the Performance of CBN Tools When Turning Austempered Ductile Iron Material

2008 ◽  
Vol 130 (5) ◽  
Author(s):  
K. Aslantas ◽  
İ. Ucun ◽  
K. Gök
Keyword(s):  
Surface Roughness ◽  
Ductile Iron ◽  
Cubic Boron Nitride ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Salt Bath ◽  
Austempered Ductile Iron ◽  
Depth Of Cut ◽  
Tool Performance ◽  
Austempering Temperature

The study deals with the machinability properties of austempered ductile iron using cubic boron nitride cutting tools. To emphasize the role of the austempering process, ductile iron specimens were first austenitized in salt bath at 900°C for 60min, after which they were quenched in a salt bath at 250°C and 325°C for 60min. Machining tests were carried out at various cutting speeds under the constant depth of cut and the feed rate. Tool performance was evaluated based on the workpiece surface roughness and flank wear. The influence of the austempering temperature and cutting speed on the chip form was also studied. The results point out that the lower austempering temperature results in the increase in the cutting forces, while better surface roughness is attained.

scholarly journals Pengaruh Parameter Proses Milling pada Austempered Ductile Iron (ADI) Terhadap Kekasaran Permukaan Benda Kerja dan Chip Thickness Ratio

2021 ◽  
Vol 16 (2) ◽  
pp. 200
Author(s):  
Rusnaldy Rusnaldy ◽  
Yusuf Umardani ◽  
Diva Tsamara Putra ◽  
Jovian Bernard
Keyword(s):  
Surface Roughness ◽  
Ductile Iron ◽  
Cutting Speed ◽  
Chip Thickness ◽  
Weight Ratio ◽  
Salt Bath ◽  
Thickness Ratio ◽  
Austempered Ductile Iron ◽  
Depth Of Cut ◽  
Dynamic Wear

<p><em>Austempered ductile iron (ADI) is a difficult material for machining, </em><em>even though ADI is believed to have several advantages such as strength, ductility, high toughness, fatigue resistance, good dynamic wear resistance, has a good strength-to-weight ratio, easy to manufacture  and easy to cast that causes it to be widely used in various applications.  </em><em>This study investigates the effect of milling parameters on surface rougness and chip thickness ratio on milling of ADI. To produce ADI, ductile irons  were first austenitized in furnace at 900<sup>o</sup>C for 1 hour and then they were quenched in salt bath at 375<sup>o</sup>C for 1 hour. The work material was machined with uncoated carbide tool. The tool was 20 mm in diameter. The cutting experiments were carried out in the dry mode. The feed was varied from 0.05 to 0.1 mm/tooth for cutting speed ranging from 15 m/min to 25 mm/min and depth of cut ranging from 0.1 mm to 0.3 mm. The surface roughness was measured using the Mitutoyo SJ-201, surface roughness machine. The chip thickness was measured using software Image J from the photograph produced by digital microscope endoscope. The results show that connected and loose chips were produced. Long and continuous chips were not found in this study. The effects of cutting speeds, feeds and depth of cut on surface roughness and chip thickness ratio  are reported in this paper</em><em></em></p>

Research on the Surface Roughness Predictive Model of Austempered Ductile Iron Based on Genetic Algorithm

2012 ◽  
Vol 497 ◽  
pp. 61-67
Author(s):  
Ting Ting Chen ◽  
Xu Hong Guo ◽  
Hao Jin Yang
Keyword(s):  
Genetic Algorithm ◽  
Surface Roughness ◽  
Ductile Iron ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Austempered Ductile Iron ◽  
Dry Cutting ◽  
Quenching Temperature

As a search algorithm for optimization based on the mechanics of natural selection and genetics, Genetic Algorithm (GA) has been widely used for solving optimization problems in various fields. According to the present manufacture situation of Austempered Ductile Iron (ADI), three samples with different quenching temperature were prepared and their mechanical properties were tested. The ceramic cutter CC6050 were used in the precise dry cutting experiment and 2205 profilometer was used to measure the surface roughness of the workpieces. The predictive models of the surface roughness during the dry finishing process were established based on Genetic Algorithm, then the results were compared with those gotten by multiple regressions, and the relationship between the surface roughness and the quenching temperature was analyzed. the cutting speed and the feed rate has greater impact on the surface roughness among the three cutting parameters, and the obtained surface roughness was larger as the quenching temperature increased.

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.

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.

Evaluation of Process Parameters in Machining of AA6063 Alloy

2018 ◽  
Vol 1148 ◽  
pp. 109-114
Author(s):  
M. Balaji ◽  
C.H. Nagaraju ◽  
V.U.S. Vara Prasad ◽  
R. Kalyani ◽  
B. Avinash
Keyword(s):  
Surface Roughness ◽  
Regression Analysis ◽  
Process Parameters ◽  
Single Channel ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Roughness Parameters ◽  
Surface Roughness Parameters ◽  
Aa6063 Alloy

The main aim of this work is to analyse the significance of cutting parameters on surface roughness and spindle vibrations while machining the AA6063 alloy. The turning experiments were carried out on a CNC lathe with a constant spindle speed of 1000rpm using carbide tool inserts coated with Tic. The cutting speed, feed rate and depth of cut are chosen as process parameters whose values are varied in between 73.51m/min to 94.24m/min, 0.02 to 0.04 mm/rev and 0.25 to 0.45 mm respectively. For each experiment, the surface roughness parameters and the amplitude plots have been noted for analysis. The output data include surface roughness parameters (Ra,Rq,Rz) measured using Talysurf and vibration parameter as vibration amplitude (mm/sec) at the front end of the spindle in transverse direction using single channel spectrum analyzer (FFT).With the collected data Regression analysis is also performed for finding the optimum parameters. The results show that significant variation of surface irregularities and vibration amplitudes were observed with cutting speed and feed. The optimum cutting speed and feed from the regression analysis were 77.0697m/min and 0.0253mm/rev. for the minimum output parameters. No significant effect of depth of cut on output parameters is identified.

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

Improvement of Surface Roughness in End Milling of Ti6Al4V by Coupling RSM with Genetic Algorithm

2011 ◽  
Vol 264-265 ◽  
pp. 1154-1159
Author(s):  
Anayet Ullah Patwari ◽  
A.K.M. Nurul Amin ◽  
S. Alam
Keyword(s):  
Genetic Algorithm ◽  
Surface Roughness ◽  
Titanium Alloys ◽  
End Milling ◽  
Fitness Function ◽  
Cutting Speed ◽  
Weight Ratio ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Resistance Surface

Titanium alloys are being widely used in the aerospace, biomedical and automotive industries because of their good strength-to-weight ratio and superior corrosion resistance. Surface roughness is one of the most important requirements in machining of Titanium alloys. This paper describes mathematically the effect of cutting parameters on Surface roughness in end milling of Ti6Al4V. The mathematical model for the surface roughness has been developed in terms of cutting speed, feed rate, and axial depth of cut using design of experiments and the response surface methodology (RSM). Central composite design was employed in developing the surface roughness models in relation to primary cutting parameters. The experimental results indicate that the proposed mathematical models suggested could adequately describe the performance indicators within the limits of the factors that are being investigated. The developed RSM is coupled as a fitness function with genetic algorithm to predict the optimum cutting conditions leading to the least surface roughness value. MATLAB 7.0 toolbox for GA is used to develop GA program. The predicted results are in good agreement with the experimental one and hence the model can be efficiently used to achieve the minimum surface roughness value.

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