Studies Regarding the Influence on the Surface Roughness Material of the Cutting Regime during the Milling Processing

2015 ◽  
Vol 1128 ◽  
pp. 271-281 ◽  
Author(s):  
Mihai Demian ◽  
Luminita Grecu ◽  
Gabriela Demian
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Optimal Parameter ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Error Variance ◽  
Milling Process ◽  
Depth Of Cut ◽  
Low Level ◽  
First Case

The aim of the present paper is to establish the optimal parameter values of the cutting regime of a milling process. The paper presents a study regarding the influence of the cutting parameters on the surface roughness of the material and also on the vibration generated by their combinations, during a processing by milling. The studies are made on samples made from S355 JR steel with a metal milling machine FUS 25, which is used also for the experiments. The samples dimensions are 210x150x16mm. For the experiments there was used a cylindrical - frontal milling tool, with 32mm diameter and 10 tooth. Basic parameters of milling processing of materials we have considered in this paper are: feed rate [mm/min]; cutting speed RPM [rot/min]; depth of cut [mm]. For each of this parameters three levels were envisaged. For a 100% accurate experiment results at least 27 experiments must be done. Using an L9 orthogonal array, the number of experiments is reduced to nine and the accurate of the method is around 99.96%. The optimal process parameters values are obtained using Taguchi method considering three situations. In the first case the goal is to get only a fine roughness for the sample. The second studied case is focused on finding a low level for the vibration generated during the milling process. The aim of the last study is to find a fine roughness and also a low level of vibration for the process. The analysis of variance (ANOVA) is applied, in all cases, in order to estimate the error variance and to rank the process parameters according to their importance.

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.

scholarly journals A Study on Surface Roughness when Milling C45 Steel

2021 ◽  
pp. 188-194
Author(s):  
Do Thi Kim Lien ◽  
Phung Tran Dinh
Keyword(s):  
Surface Roughness ◽  
Regression Models ◽  
Process Analysis ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Milling Process ◽  
Experimental Results ◽  
Depth Of Cut ◽  
Experimental Process ◽  
Cut Surface

In this paper, a study is presented on the milling process of C45 steel by face milling cutters. An experimental process was performed according to an experimental matrix constructed by the Box-Behnken method. At each experiment, three cutting parameters were changed, namely cutting speed, feed rate, and depth of cut. Surface roughness has been selected as a parameter to evaluate the milling process. Analysis of experimental results has determined the influence of cutting parameters as well as their interactions on surface roughness. Two regression models for surface roughness have been proposed. In which one model uses the Johnson transformation. These two models were used to predict the surface roughness and then compared with the experimental results. The results show that the model using the Johnson transformation has higher accuracy than the model not using the data transformation.

Application of Taguchi’s Method for Study of Machining Parameters on Surface Roughness of 7136 Aluminum Alloy in End Milling

2015 ◽  
Vol 809-810 ◽  
pp. 123-128 ◽  
Author(s):  
Alina Bianca Bonţiu Pop
Keyword(s):  
Surface Roughness ◽  
Aluminum Alloy ◽  
Process Parameters ◽  
End Milling ◽  
Signal To Noise Ratio ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Future Research ◽  
Depth Of Cut ◽  
Machining Parameters

Starting with the necessity to identify the optimum values of the cutting parameters which are affecting the surface quality, it is appropriate to use the design of experiment techniques to conduct the experiments. Previous researches [1] focused on the investigation of the effects of machining parameters on surface roughness. In this paper, the experiments were conducted based on the established Taguchi’s technique, L8 orthogonal array using Minitab-17 statistical software. Three machining parameters are chosen as process parameters: Cutting Speed, Feed per tooth and Depth of cut. The orthogonal matrix includes these three factors set for analysis, each with 2 levels associated. The level of influence that the process parameters exert on the surface roughness is analyzed by Taguchi method data analysis. In this case the signal to noise ratio was tacked into account. Also, the recommended configuration regarding the optimum values of these parameters was determined as well as the interactions between them, in order to obtain better surface roughness for 7136 aluminum alloy machining. The final results will be used as data for future research.

scholarly journals Investigation on the Surface Quality Obtained during Trochoidal Milling of 6082 Aluminum Alloy

Machines ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 75
Author(s):  
Nikolaos E. Karkalos ◽  
Panagiotis Karmiris-Obratański ◽  
Szymon Kurpiel ◽  
Krzysztof Zagórski ◽  
Angelos P. Markopoulos
Keyword(s):  
Surface Roughness ◽  
Surface Quality ◽  
Process Parameters ◽  
Manufacturing Industry ◽  
High Surface ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
High Surface Quality ◽  
Trochoidal Milling

Surface quality has always been an important goal in the manufacturing industry, as it is not only related to the achievement of appropriate geometrical tolerances but also plays an important role in the tribological behavior of the surface as well as its resistance to fatigue and corrosion. Usually, in order to achieve sufficiently high surface quality, process parameters, such as cutting speed and feed, are regulated or special types of cutting tools are used. In the present work, an alternative strategy for slot milling is adopted, namely, trochoidal milling, which employs a more complex trajectory for the cutting tool. Two series of experiments were initially conducted with traditional and trochoidal milling under various feed and cutting speed values in order to evaluate the capabilities of trochoidal milling. The findings showed a clear difference between the two milling strategies, and it was shown that the trochoidal milling strategy is able to provide superior surface quality when the appropriate process parameters are also chosen. Finally, the effect of the depth of cut, coolant and trochoidal stepover on surface roughness during trochoidal milling was also investigated, and it was found that lower depths of cut, the use of coolant and low values of trochoidal stepover can lead to a considerable decrease in surface roughness.

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.

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.

Statistical Analysis of Process Parameters in Drilling of Al/Al2O3p Metal Matrix Composites

2014 ◽  
Vol 14 (3) ◽  
pp. 171-175 ◽  
Author(s):  
Yashvir Singh ◽  
Amneesh Singla ◽  
Ajay Kumar
Keyword(s):  
Surface Roughness ◽  
Statistical Analysis ◽  
Process Parameters ◽  
Metal Matrix ◽  
Design Method ◽  
Experimental Studies ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Signal To Noise ◽  
Drilling Parameters

AbstractThis paper presents a statistical analysis of process parameters for surface roughness in drilling of Al/Al2O3p metal matrix composite. The experimental studies were conducted under varying spindle speed, feed rate, point angle of drill. The settings of drilling parameters were determined by using Taguchi experimental design method. The level of importance of the drilling parameters is determined by using analysis of variance. The optimum drilling parameter combination was obtained by using the analysis of signal-to-noise ratio. Through statistical analysis of response variables and signal-to-noise ratios, the determined significant factors are depth of cut and drill point angle with the contributions of 87% and 12% respectively, whereas the cutting speed is insignificant contributing by 1% only. Confirmation tests verified that the selected optimal combination of process parameter through Taguchi design was able to achieve desired surface roughness.

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.

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