Surface Roughness Analysis of Magnesium Pieces Obtained by Intermittent Turning

2013 ◽  
Vol 773-774 ◽  
pp. 377-391 ◽  
Author(s):  
Eva M. Rubio ◽  
María Villeta ◽  
Beatriz de Agustina ◽  
Diego Carou
Keyword(s):  
Experimental Study ◽  
Surface Roughness ◽  
Design Of Experiments ◽  
Feed Rate ◽  
Great Influence ◽  
Depth Of Cut ◽  
Roughness Analysis ◽  
Intermittent Turning ◽  
Sources Of Variation ◽  
Intermittent Cutting

This paper presents an experimental study to analyze the surface roughness reached in pieces of UNS M11917 magnesium alloy obtained by intermittent turning. A design of experiments (DOE) was established to carry out the study. Namely, factors identified as posible sources of variation of the surface roughness and their levels, written between parentheses, are the following: depth of cut (1), feed rate (2), spindle speed (2), type of tool (2), quantity of lubrication (3), type of interruption (3), measurement length (3) and measurement generatrice (3). Due to the high number of possible combinations that can be generated with the set of factors and levels identified a combined design of experiments L4x32 was performed. Data are was analyzed by means of the analysis of variance (ANOVA) method. The main results of the statistical analysis highlight the great influence of the feed rate on surface roughness among the set of factors and their interactions considered. In addition, focusing on the intermittent cutting, type of interruption and its interaction with the type of tool used are also important sources of variation, but at a lower level than feed rate.

scholarly journals Investigate the Effect of Cutting Parameters on Surface Roughness When Milling X12m Steel

2021 ◽  
pp. 258-263
Author(s):  
Do Thi Kim Lien ◽  
Nguyen Dinh Man ◽  
Phung Tran Dinh
Keyword(s):  
Experimental Study ◽  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Tool ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Face Milling ◽  
Negligible Effect ◽  
Depth Of Cut ◽  
The Relationship

In this paper, an experimental study on the effect of cutting parameters on surface roughness was conducted when milling X12M steel. The cutting tool used in this study is a face milling cutter. The material that is used to make the insert is the hard alloy T15K6. The cutting parameters covered in this study include the cutting speed, the feed rate and depth of cut. The experiments are performed in the form of a rotating center composite design. The analysis shows that for both Ra and Rz: (1) the feed rate has the greatest influence on the surface roughness while the depth of cut, the cutting speed has a negligible effect on the surface roughness. (2) only the interaction between the feed rate and the depth of the cut has a significant effect on both Ra and Rz while the interaction between the cutting speed and the feed rate, the interaction between the cutting speed and the depth of cut have a negligible effect on surface roughness. A regression equation showing the relationship between Ra, Rz, and cutting parameters has also been built in this study.

Inserts Selection for Intermittent Turning of Magnesium Pieces

2012 ◽  
Vol 217-219 ◽  
pp. 1581-1591 ◽  
Author(s):  
Eva María Rubio ◽  
José Luis Valencia ◽  
Diego Carou ◽  
Adolfo J. Saá
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Spindle Speed ◽  
The Other ◽  
Influential Factor ◽  
Depth Of Cut ◽  
Hybrid Parts ◽  
Intermittent Turning ◽  
Low Performance ◽  
Performance Conditions

The present work shows an experimental study for selecting the best tools to use in the intermittent turning of pieces of UNS M11917 magnesium alloy under low performance conditions based on the surface roughness. Namely, two types of tools are considered: one, specific for non-ferrous materials, and the other, for materials usually combined with the magnesium to form hybrid parts such as titanium or steel. In order to carry out this study, a combined design of experiments (DOE) L4x32 is established. Concretely, the factors that are taken into account in the design, in addition to the type of tool, are considered the next ones: depth of cut, feed rate, spindle speed, quantity of lubrication, type of interruption, and measurement zones of the surface roughness in terms of the measurement length and of the measurement generatrix. Obtained data are analysed by means of the analysis of variance (ANOVA) method. In this case, feed rate is the most influential factor on the variability of surface roughness followed, although at a large distance, by: type of interruption, interaction feed rate-quantity of lubrication, type of tool, quantity of lubrication, interaction type of tool-type of interruption and spindle speed. As conclusion, it is possible to affirm that, in general, the surface roughness is slightly lower when using non-ferrous tools than when using the other types tried.

Experimental Investigation of Effects of Machining Parameters on Surface Roughness and Chip Formation of Aluminum Alloys by Face Turning

2015 ◽  
Vol 799-800 ◽  
pp. 299-306
Author(s):  
Meshack Olygen Kusimba ◽  
Seong Joo Choi
Keyword(s):  
Surface Roughness ◽  
Chip Formation ◽  
Feed Rate ◽  
Aluminium Alloys ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Atomic Force ◽  
Roughness Analysis ◽  
The Face

This paper investigates the effect of process parameters on surface roughness and chips formation in face turning of aluminium A2025 alloy international standard or A3035 alloy Korean standard using conventional lathe. The parameters namely the spindle speed, depth of cut and feed rate are varied to study their effect on surface roughness and chip characteristics. The experiments are conducted with all possible combination of factors in order to get the influence of every factor. The study reveals that the surface roughness is directly influenced by the spindle speed, depth of cut and feed rate. It is observed that the surface roughness increases with increased feed rate and depth of cut and is higher atlower speeds. The surface roughness analysis was done by atomic force microscope (AFM).The chips formed were continuous but varied in size and shape basing on the machining parameters. The depth of cut has no significant influence on the chips formation. The results shown here shows the ability of face turning method to test the surface roughness and chip formation on aluminium alloys. The face turning method used is simple and effective.

scholarly journals Effect of cutting parameters on surface roughness in turning of annealed AISI-1020 steel

2018 ◽  
Vol 27 (47) ◽  
pp. 109
Author(s):  
Omar Zurita ◽  
Verónica Di-Graci ◽  
María Capace
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Optimum Parameters ◽  
Proposed Model ◽  
Roughness Analysis ◽  
Regression Techniques ◽  
Predicted Values

This study focuses on the effects of cutting parameters such as cutting speed (Vc), feed rate (f), and depth of cut (d) on roughness induced on the surface of annealed AISI 1020 steel when machined by turning using carbide insert tools. The results indicated that surface roughness increased when feed rate increased and cutting speed decreased. Depth of cut slightly influenced roughness. Analysis of variance and multiple regression techniques were used to formulate a quantitative equation for estimating predicted values of roughness as functions of the cutting parameters. The results showed that cutting speed is the most influencing parameter on surface roughness (69.35%), followed by feed rate (30.13%), while depth of cut failed to affect the responses substantially (0.52%). The proposed model can be used to select the optimum parameters for minimum surface roughness in metal turning.

Prediction of Surface Roughness and Optimization of Cutting Parameters in CNC Turning of Rotational Features

2020 ◽  
Vol 38 (8A) ◽  
pp. 1143-1153
Author(s):  
Yousif K. Shounia ◽  
Tahseen F. Abbas ◽  
Raed R. Shwaish
Keyword(s):  
Surface Roughness ◽  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Feed Rate ◽  
Cutting Parameters ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Non Linear ◽  
Optimization Of Cutting Parameters

This research presents a model for prediction surface roughness in terms of process parameters in turning aluminum alloy 1200. The geometry to be machined has four rotational features: straight, taper, convex and concave, while a design of experiments was created through the Taguchi L25 orthogonal array experiments in minitab17 three factors with five Levels depth of cut (0.04, 0.06, 0.08, 0.10 and 0.12) mm, spindle speed (1200, 1400, 1600, 1800 and 2000) r.p.m and feed rate (60, 70, 80, 90 and 100) mm/min. A multiple non-linear regression model has been used which is a set of statistical extrapolation processes to estimate the relationships input variables and output which the surface roughness which prediction outside the range of the data. According to the non-linear regression model, the optimum surface roughness can be obtained at 1800 rpm of spindle speed, feed-rate of 80 mm/min and depth of cut 0.04 mm then the best surface roughness comes out to be 0.04 μm at tapper feature at depth of cut 0.01 mm and same spindle speed and feed rate pervious which gives the error of 3.23% at evolution equation.

Nature instigated Grey wolf algorithm for parametric optimization during machining (Milling) of polymer nanocomposites

2021 ◽  
pp. 089270572199320
Author(s):  
Prakhar Kumar Kharwar ◽  
Rajesh Kumar Verma
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Polymer Nanocomposites ◽  
Feed Rate ◽  
Fitness Function ◽  
Depth Of Cut ◽  
Multiwall Carbon Nanotube ◽  
Grey Wolf ◽  
Milling Characteristics ◽  
The Impact

The new era of engineering society focuses on the utilization of the potential advantage of carbon nanomaterials. The machinability facets of nanocarbon materials are passing through an initial stage. This article emphasizes the machinability evaluation and optimization of Milling performances, namely Surface roughness (Ra), Cutting force (Fc), and Material removal rate (MRR) using a recently developed Grey wolf optimization algorithm (GWOA). The Taguchi theory-based L27 orthogonal array (OA) was employed for the Machining (Milling) of polymer nanocomposites reinforced by Multiwall carbon nanotube (MWCNT). The second-order polynomial equation was intended for the analysis of the model. These mathematical models were used as a fitness function in the GWOA to predict machining performances. The ANOVA outcomes efficiently explore the impact of machine parameters on Milling characteristics. The optimal combination for lower surface roughness value is 1.5 MWCNT wt.%, 1500 rpm of spindle speed, 50 mm/min of feed rate, and 3 mm depth of cut. For lower cutting force, 1.0 wt.%, 1500 rpm, 90 mm/min feed rate and 1 mm depth of cut and the maximize MRR was acquired at 0.5 wt.%, 500 rpm, 150 mm/min feed rate and 3 mm depth of cut. The deviation of the predicted value from the experimental value of Ra, Fc, and MRR are found as 2.5, 6.5 and 5.9%, respectively. The convergence plot of all Milling characteristics suggests the application potential of the GWO algorithm for quality improvement in a manufacturing environment.

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.

Investigation of Surface Roughness and Material Removal Rate for High Speed Micro End Milling on PMMA

2015 ◽  
Vol 1115 ◽  
pp. 12-15
Author(s):  
Nur Atiqah ◽  
Mohammad Yeakub Ali ◽  
Abdul Rahman Mohamed ◽  
Md. Sazzad Hossein Chowdhury
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
High Speed ◽  
End Milling ◽  
Removal Rate ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Micro End Milling

Micro end milling is one of the most important micromachining process and widely used for producing miniaturized components with high accuracy and surface finish. This paper present the influence of three micro end milling process parameters; spindle speed, feed rate, and depth of cut on surface roughness (Ra) and material removal rate (MRR). The machining was performed using multi-process micro machine tools (DT-110 Mikrotools Inc., Singapore) with poly methyl methacrylate (PMMA) as the workpiece and tungsten carbide as its tool. To develop the mathematical model for the responses in high speed micro end milling machining, Taguchi design has been used to design the experiment by using the orthogonal array of three levels L18 (21×37). The developed models were used for multiple response optimizations by desirability function approach to obtain minimum Ra and maximum MRR. The optimized values of Ra and MRR were 128.24 nm, and 0.0463 mg/min, respectively obtained at spindle speed of 30000 rpm, feed rate of 2.65 mm/min, and depth of cut of 40 μm. The analysis of variance revealed that spindle speeds are the most influential parameters on Ra. The optimization of MRR is mostly influence by feed rate. Keywords:Micromilling,surfaceroughness,MRR,PMMA

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 Experimental Study on Machinability of Zr-Based Bulk Metallic Glass during Micro Milling

Micromachines ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 86 ◽  
Author(s):  
Tao Wang ◽  
Xiaoyu Wu ◽  
Guoqing Zhang ◽  
Bin Xu ◽  
Yinghua Chen ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Metallic Glass ◽  
Bulk Metallic Glass ◽  
Feed Rate ◽  
Rotation Speed ◽  
Amorphous Structure ◽  
Micro Milling ◽  
Depth Of Cut ◽  
Milling Force ◽  
Coated Cemented Carbide

The micro machinability of Zr41.2Ti13.8Cu12.5Ni10Be22.5 bulk metallic glass (BMG) was investigated by micro milling with coated cemented carbide tools. The corresponding micro milling tests on Al6061 were conducted for comparison. The results showed that the tool was still in stable wear stage after milling 300 mm, and the surface roughness Ra could be maintained around 0.06 μm. The tool experienced only slight chipping and rubbing wear after milling the BMG, while a built-up edge and the coating peeling off occurred severely when milling Al6061. The influence of rotation speed on surface roughness was insignificant, while surface roughness decreased with the reduction of feed rate, and then increased dramatically when the feed rate was below 2 μm/tooth. The surface roughness increased gradually with the axial depth of cut (DOC). Milling force decreased slightly with the increase in rotation speed, while it increased with the increase in axial DOC, and the size effect on milling force occurred when the feed rate decreased below 1 μm/tooth. The results of X-ray diffraction (XRD) showed that all milled surfaces were still dominated by an amorphous structure. This study could pave a solid foundation for structural and functional applications.

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