Investigation on Cutting Forces and Surface Finish in Mechanical Micro Milling of Zr-Based Bulk Metallic Glass

2019 ◽  
Vol 18 (01) ◽  
pp. 113-132
Author(s):  
Debajyoti Ray ◽  
Asit Baran Puri ◽  
Nagahanumaiah
Keyword(s):  
Surface Roughness ◽  
Metallic Glass ◽  
Cutting Force ◽  
Bulk Metallic Glass ◽  
Cutting Parameters ◽  
Milling Process ◽  
Spindle Speed ◽  
Micro Milling ◽  
Depth Of Cut ◽  
Axial Depth

Precision micro-component fabrication demands suitable manufacturing processes that ensure making of parts with good form and finish. Mechanical micro milling represents a flexible and powerful process that exhibits enhanced capability to create micro features. Bulk metallic glass (BMG) represents a young class of amorphous alloy material with superior mechanical and physical properties and finds appreciable micro scale applications like biomedical devices and implants, micro parts for sport items and various other micro- components. In the present work, an attempt has been made to analyze the influence of the cutting parameters like spindle speed, feed per tooth and axial depth of cut on the machinability of BMG, in mechanical micro-milling process. The micro-milling process performances have been evaluated concerning to cutting forces and surface roughness generated, by making full slots on the workpiece with solid carbide end mill cutters. The paper presents micro-machining results for bulk metallic glass machined with commercial micro-milling tool at low cutting velocity regime. Response surface methodology (RSM) has been employed for process modeling and subsequent analysis to study the influence of the combination of cutting parameters on responses within the selected domain of cutting parameters. It has been found that the effect of axial depth of cut on the cutting force components is remarkably significant. Cutting force components increases with the increase in axial depth of cut and decreases with increase in spindle speed. At low feed rate, cutting force in the feed direction (Fx, i.e., cutting force along x-direction) increases with a decrease in feed rate. This increase of force could be due to the possible ploughing effect. A similar pattern of variation has been observed with cutting force component in cross-feed direction (Fy) also. It has been found that effect of feed per tooth on the roughness parameter Ra is remarkably significant. Surface roughness increases with feed per tooth. Axial depth of cut does not contribute much to the surface roughness. Surface roughness decrease with the increase of spindle speed.

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.

An experimental investigation of micro-milling brass considering run out by carbide micro-end mills

2017 ◽  
Vol 232 (20) ◽  
pp. 3675-3684 ◽  
Author(s):  
Xiubing Jing ◽  
Yanling Tian ◽  
Yanjie Yuan
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Cutting Speed ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Milling Process ◽  
Micro Milling ◽  
Method Of Calculation ◽  
Micro End Mill ◽  
End Mills

This paper presented the effect of run out on the experimental characteristic of micro-milling brass using carbide micro-end mills. A method of calculation and measurement for the run out of tool-holder-spindle assembly in micro-end mill was developed. A series of micro-milling process experiments were carried out under varying cutting parameters. The effect of run out on cutting forces, effect of cutting parameters on surface roughness, and size effect were analyzed. It was seen that the cutting force signature was seriously affected by run out in the micro-milling process. When the feed per tooth is less than the run out, the cutting force signals showed that only one cutter flute engaged in cutting process due to the effect of run out. It was also seen that the cutting force signature showed erratic variations due to the effect of tool–workpiece and the run out of tool tip at higher spindle speed. Surface roughness was affected by both cutting speed and feed per tooth. For lower cutting speed, there was increase in the surface roughness with the decrease in the cutting speed due to the effect of built-up edge. For higher cutting speed, there was increase in the surface roughness with the increase in the cutting speed due to dominance of the shearing effects. When the feed per tooth was less than the minimum chip thickness, due to the indentation and ploughing-dominated process, nonlinear increase of specific shear energy can be obtained. At lower feed per tooth, the specific energy increases with increased cutting speed. These results are used to provide strategies to optimize cutting parameters and achieve better surface quality in micro-milling brass process.

Investigation of material removal rate and surface roughness using multi-objective optimization for micro-milling of inconel 718

2019 ◽  
Vol 71 (6) ◽  
pp. 787-794 ◽  
Author(s):  
Xiaohong Lu ◽  
FuRui Wang ◽  
Liang Xue ◽  
Yixuan Feng ◽  
Steven Y. Liang
Keyword(s):  
Surface Roughness ◽  
Inconel 718 ◽  
Cutting Parameters ◽  
Spindle Speed ◽  
Micro Milling ◽  
Depth Of Cut ◽  
Multi Objective Optimization ◽  
Content Type ◽  
Cutting Parameter ◽  
Multi Objective

Purpose The purpose of this study is to realize the multi-objective optimization for MRR and surface roughness in micro-milling of Inconel 718. Design/methodology/approach Taguchi method has been applied to conduct experiments, and the cutting parameters are spindle speed, feed per tooth and depth of cut. The first-order models used to predict surface roughness and MRR for micro-milling of Inconel 718 have been developed by regression analysis. Genetic algorithm has been utilized to implement multi-objective optimization between surface roughness and MRR for micro-milling of Inconel 718. Findings This paper implemented the multi-objective optimization between surface roughness and MRR for micro-milling of Inconel 718. And some conclusions can be summarized. Depth of cut is the major cutting parameter influencing surface roughness. Feed per tooth is the major cutting parameter influencing MRR. A number of cutting parameters have been obtained along with the set of pareto optimal solu-tions of MRR and surface roughness in micro-milling of Inconel 718. Originality/value There are a lot of cutting parameters affecting surface roughness and MRR in micro-milling, such as tool diameter, depth of cut, feed per tooth, spindle speed and workpiece material, etc. However, to the best our knowledge, there are no published literatures about the multi-objective optimization of surface roughness and MRR in micro-milling of Inconel 718.

Modeling of Top Burr Formation in Micro-End Milling of Zr-Based Bulk Metallic Glass

2019 ◽  
Vol 7 (4) ◽  
Author(s):  
Debajyoti Ray ◽  
Asit Baran Puri ◽  
Naga Hanumaiah ◽  
Saurav Halder
Keyword(s):  
Metallic Glass ◽  
Bulk Metallic Glass ◽  
End Milling ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Milling Process ◽  
Burr Formation ◽  
Depth Of Cut ◽  
Glass Work ◽  
Micro End Milling

Abstract In this study, an analysis is presented for the formulation of a model in top burr formation to estimate the width of the top burrs formed in micro-end milling process. In this analysis, the width of the top burrs, considered to be the measure of burr size of top burrs, represents the extent of burr formation. The model is applied to quantify the burr formation in Zr-based bulk metallic glass, an amorphous metallic alloy. In this study, micromilling experiments were carried out on the bulk metallic glass work material at different levels of feed rate, axial depth of cut, and cutting speed to compare the experimental values of top burr width with the predicted values. Analysis is carried out to characterize top burr formation based on the experimental results of burr sizes in the up-milling and down-milling side edges, and the influential effects of the cutting parameters on the burr formation are analyzed.

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.

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

In-Process Prediction of Surface Roughness in Grinding Process by Monitoring of Cutting Force Ratio

2014 ◽  
Vol 627 ◽  
pp. 29-34 ◽  
Author(s):  
Vichaya Thammasing ◽  
Somkiat Tangjitsitcharoen
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Spindle Speed ◽  
Least Square ◽  
Depth Of Cut ◽  
Grinding Process ◽  
Average Surface Roughness ◽  
Average Surface ◽  
Developed Surface ◽  
Force Ratio

The purpose of this research is to develop the models to predict the average surface roughness and the surface roughness during the in-process grinding by monitoring the cutting force ratio. The proposed models are developed based on the experimentally obtained results by employing the exponential function with four factors, which are the spindle speed, the feed rate, the depth of cut, and the cutting force ratio. The experimentally obtained results showed that the dimensionless cutting force ratio is usable to predict the surface roughness during the grinding process, which can be calculated and obtained by taking the ratio of the corresponding time records of the cutting force Fy in the spindle speed direction to that of the cutting force Fz in the radial wheel direction. The multiple regression analysis is utilized to calculate the regression coefficients with the use of the least square method at 95% confident level. The experimentally obtained models have been verified by the new cutting tests. It is proved that the developed surface roughness models can be used to predict the in-process surface roughness with the high accuracy of 93.9% for the average surface roughness and 92.8% for the surface roughness.

Optimization of Process Parameters for Cutting Force for Aluminium 7010 in CNC End Milling Process

2018 ◽  
Vol 10 (6) ◽  
Author(s):  
M. Kishanth ◽  
P. Rajkamal ◽  
D. Karthikeyan ◽  
K. Anand
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Process Parameters ◽  
End Milling ◽  
Milling Process ◽  
Machining Process ◽  
Depth Of Cut ◽  
Optimization Of Process Parameters ◽  
Cnc End Milling ◽  
End Milling Process

In this paper CNC end milling process have been optimized in cutting force and surface roughness based on the three process parameters (i.e.) speed, feed rate and depth of cut. Since the end milling process is used for abrading the wear caused is very high, in order to reduce the wear caused by high cutting force and to decrease the surface roughness, the optimization is much needed for this process. Especially for materials like aluminium 7010, this kind of study is important for further improvement in machining process and also it will improve the stability of the machine.

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.

The Effects of Cutting Parameters to the Surface Roughness in High Speed Cutting of Micro-Milling Titanium Alloy Ti-6Al-4V

2020 ◽  
Vol 846 ◽  
pp. 133-138
Author(s):  
Gandjar Kiswanto ◽  
Adrian Mandala ◽  
Maulana Azmi ◽  
Tae Jo Ko
Keyword(s):  
Surface Roughness ◽  
Titanium Alloy ◽  
Weight Reduction ◽  
Feed Rate ◽  
High Speed ◽  
Cutting Parameters ◽  
Micro Milling ◽  
Depth Of Cut ◽  
High Speed Cutting ◽  
Micro Scale

Micro-milling offers high flexibility by producing complex 3D micro-scale products. Weight reduction are one of the optimizations of the product that can make it stronger and more efficient nowadays. Titanium are the most commonly used for micro-scale products especially in biomedical industries because of the biocompatibility properties. Titanium alloys offers high strength with low density and high corrosion resistance that is suitable for weight reduction. This study aims to investigate the influence of high speed cutting parameters to the surface roughness in micromilling of titanium alloy Ti-6Al-4V as high speed cutting offers more productivity since producing more cutting length in the same time. experiments are carried out by micromilling process with variations in high speed cutting parameters of spindle speed and feed rate with a constant depth of cut using a carbide cutting tool of with a diameter of 1 mm. The machining results in the form of a 4 mm slot with a depth as the same as depth of cut, which then measures its surface roughness. It was found that higher feed rate that is followed by higher spindle speed will produce better surface roughness.

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