Multiple performance characteristics optimization in end milling of thin-walled parts using desirability function

2020 ◽  
Vol 44 (1) ◽  
pp. 84-94 ◽  
Author(s):  
Djordje Cica ◽  
Stevo Borojevic ◽  
Goran Jotic ◽  
Branislav Sredanovic ◽  
Sasa Tesic
Keyword(s):  
Surface Roughness ◽  
Wall Thickness ◽  
End Milling ◽  
Influential Factor ◽  
Machining Process ◽  
Cnc Machine Tools ◽  
Reference Plane ◽  
Machining Parameters ◽  
Machining Strategy ◽  
Thin Walled

With the development of high-performance CNC machine tools, milling has been established as one of the main means of machining thin-walled parts. Thus, the selection of process parameters for milling operations is an important issue in end milling of thin-walled parts to assure product quality and increase productivity. The current study explores three machining parameters, namely wall thickness, feed, and machining strategies, that influence dimensional and form errors, surface roughness, and machining time milling of 7075-T6 aluminum alloy thin-walled parts. The effects of machining parameters on each of the response variables were analyzed using graphs of the main effects and three-dimensional surface plots. Analysis of the results show that the most influential factor for wall thickness deviation, dimensions deviation, perpendicularity deviation, flatness deviation, surface roughness of inner walls, surface roughness of outer walls, and surface roughness of reference plane was machining strategy, while feed is the most influential parameter affecting the machined time, followed by the machining strategy. The desirability concept has been used for simultaneous optimization in terms of machining parameters of the thin-walled parts machining process. Finally, a confirmation test with the optimal parameter settings was carried out to validate the results.

Processing and End Milling Behavioural Study of A356-SiCp Composite

2012 ◽  
Vol 710 ◽  
pp. 338-343 ◽  
Author(s):  
K. Jayakumar ◽  
Jose Mathew ◽  
M.A. Joseph ◽  
R. Suresh Kumar ◽  
P. Chakravarthy
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
End Milling ◽  
Cutting Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Pressing Method ◽  
Reinforced Composite ◽  
Effect Of Particle Size

Machining process such as milling receives less attention in the study of machinability of composites due to its interrupted cutting and the complexity of the process. In the present study, A356 aluminium alloy powder reinforced with 10 volume % SiC particles of various sizes (1,12.5 and 25 µm) were synthesized by vacuum hot pressing method and the effect of particle size on the composites were analysed for its mechanical properties and machinability. End milling of these composites were carried out and the surface roughness and resultant cutting force were analysed with the change of machining parameters and varying SiC particle sizes. The minimum cutting force and surface roughness were obtained for a finer particle (1 µm) reinforced composite with higher cutting speed, low feed and depth of cut.

Prediction of Surface Roughness in Compressed Air Jet Assisted High Speed End Milling of Silicon Using Diamond Coated Tools

2012 ◽  
Vol 576 ◽  
pp. 41-45
Author(s):  
A.K.M. Nurul Amin ◽  
M.A. Mahmud ◽  
M.D. Arif
Keyword(s):  
Mathematical Model ◽  
Surface Roughness ◽  
Surface Finish ◽  
High Speed ◽  
End Milling ◽  
Silicon Wafers ◽  
Compressed Air ◽  
Machining Parameters ◽  
High Quality ◽  
Ductile Mode

The majority of semiconductor devices are made up of silicon wafers. Manufacturing of high-quality silicon wafers includes numerous machining processes, including end milling. In order to end mill silicon to a nano-meteric surface finish, it is crucial to determine the effect of machining parameters, which influence the machining transition from brittle to ductile mode. Thus, this paper presents a novel experimental technique to study the effects of machining parameters in high speed end milling of silicon. The application of compressed air, in order to blow away the chips formed, is also investigated. The machining parameters’ ranges which facilitate the transition from brittle to ductile mode cutting as well as enable the attainment of high quality surface finish and integrity are identified. Mathematical model of the response parameter, the average surface roughness (Ra) is subsequently developed using RSM in terms of the machining parameters. The model was determined, by Analysis of Variance (ANOVA), to have a confidence level of 95%. The experimental results show that the developed mathematical model can effectively describe the performance indicators within the controlled limits of the factors that are being considered.

scholarly journals Study of wire-electrical discharge machining parameters of titanium alloy by using taguchi method

2018 ◽  
Vol 7 (2.8) ◽  
pp. 10
Author(s):  
A VS Ram Prasad ◽  
Koona Ramji ◽  
B Raghu Kumar
Keyword(s):  
Surface Roughness ◽  
Taguchi Method ◽  
Process Parameters ◽  
Optimization Technique ◽  
Machining Process ◽  
Machining Parameters ◽  
Wire Edm ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Edm Process

Machining of Titanium alloys is difficult due to their chemical and physical properties namely excellent strength, chemical reactivity and low thermal conductivity. Traditional machining of such materials leads to formation of continuous chips and tool bits are subjected to chatter which leads to formation of poor surface on machined surface. In this study, Wire-EDM one of the most popular unconventional machining process which was used to machine such difficult-to-cut materials. Effect of Wire-EDM process parameters namely peak current, pulse-on- time, pulse-off-time, servo voltage on MRRand SR was investigated by Taguchi method. 0.25 mm brass wire was used in this process as electrode material. A surface roughness tester (Surftest 301) was used to measure surface roughness value of the machined work surface. A multi-response optimization technique was then utilized to optimize Wire-EDM process parameters for achieving maximum MRR and minimum SR simultaneously.

scholarly journals Influence of Ultrasonic Vibration-Assisted Ball-End Milling on the Cutting Performance of AZ31B Magnesium Alloy

2020 ◽  
Vol 9 (4) ◽  
pp. 271-276
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Ultrasonic Vibration ◽  
Biomedical Applications ◽  
End Milling ◽  
Cutting Temperature ◽  
Cutting Performance ◽  
Machining Process ◽  
Dry Conditions ◽  
Good Biocompatibility

Magnesium alloys have a tremendous possibility for biomedical applications due to their good biocompatibility, integrity and degradability, but their low ignition temperature and easy corrosive property restrict the machining process for potential biomedical applications. In this research, ultrasonic vibration-assisted ball milling (UVABM) for AZ31B is investigated to improve the cutting performance and get specific surface morphology in dry conditions. Cutting force and cutting temperatures are measured during UVABM. Surface roughness is measured with a white light interferometer after UVABM. The experimental results show cutting force and cutting temperature reduce due to ultrasonic vibration, and surface roughness decreases by 34.92%, compared with that got from traditional milling, which indicates UVABM is suitable to process AZ31B for potential biomedical applications.

scholarly journals Findings of performance evaluation of EDM for different materials of electrodes and work pieces- a review

2018 ◽  
Vol 7 (4.5) ◽  
pp. 542
Author(s):  
Harshalkumar R. Mundane ◽  
Dr. A. V. Kale ◽  
Dr. J. P. Giri
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Performance Measure ◽  
Machining Process ◽  
Machining Parameters ◽  
Spark Erosion ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time ◽  
Time Pulse

EDM (Spark erosion) is non-conventional machining process which uses as removing unwanted material by electrical spark erosion. EDM Machining parameters affecting to the performance and the industries goal is to produce high quality of product with less time consuming and cost. To achieve these goals, optimizing the machining parameters such as pulse on time, pulse off time, cutting speed, depth of cut, duty cycle, arc gap, voltage etc. The performance measure of EDM is calculated on the basis of Material Remove Rate(MRR), Tool Wear Rate(TWR), and Surface Roughness(SR).The main objective of present work is to investigate of the influence of input EDM (Electro Discharge Machining) parameters on machining characteristics like surface roughness and the effects of various EDM process parameters such as pulse on time, pulse off time, servo voltage, peak current, dielectric flow rate, on different process response parameters such as material removal rate (MRR), surface roughness (Ra), Kerf (width of Cut), tool wear ratio(TWR)and surface integrity factors. In this paper few selected research paper related to Die-sinker EDM with effect of MRR, TWR, surface roughness (SR) and work piece material have been discussed.   

Study on Surface Roughness of Ultrasonic Vibration Assisted Milling

2012 ◽  
Vol 426 ◽  
pp. 309-312 ◽  
Author(s):  
Xue Hui Shen ◽  
Jian Hua Zhang ◽  
H. Li ◽  
J.J. Wang
Keyword(s):  
Surface Roughness ◽  
Ultrasonic Vibration ◽  
End Milling ◽  
Target Surface ◽  
Side Surface ◽  
Machining Parameters ◽  
Small Surface ◽  
Vertical Side ◽  
Combined Action ◽  
Respective Surface

The object of this paper is to experimentally investigate the effects of ultrasonic vibration on the roughness of surface produced by the side cutting edge of an end milling cutter. Two respective surface roughness models for conventional milling (CM) and ultrasonic vibration assisted milling (UVAM) were proposed using experimental data. RSM and ANOVA were used for analysis. As a result, it is found that the surface roughness of vertical side surface of slot improves obviously after applying ultrasonic vibration. The result of ANOVA indicated that the target surface roughness depends on the combined action of several key machining parameters in UVAM, and therefore their choosing and optimizing is very important to achieving small surface roughness.

Surface Roughness Optimization in End Milling of Stainless Steel AISI 304 with Uncoated WC-Co Insert Under Magnetic Field

2012 ◽  
Vol 576 ◽  
pp. 119-122 ◽  
Author(s):  
A.K.M. Nurul Amin ◽  
Syidatul Akma Sulaiman ◽  
Siti Noor Izzati Mohd Zainun ◽  
M.D. Arif
Keyword(s):  
Magnetic Field ◽  
Surface Roughness ◽  
Magnetic Fields ◽  
Permanent Magnets ◽  
End Milling ◽  
Desirability Function ◽  
Low Carbon Steel ◽  
Machining Process ◽  
Low Carbon ◽  
Novel Approach

Chatter phenomenon is a major issue as it greatly affects the topography of machined parts. Due to the inconsistent character of chatter, it is extremely difficult to predict resultant surface roughness in a machining process, such as end milling. Also, recent studies have shown that chatter can be suitably damped using magnetic fields. This paper, thus, focuses on a novel approach of minimizing surface roughness in end milling of Mild (Low Carbon) Steel using uncoated WC-Co inserts under magnetic field from permanent magnets. In this experiment, Response Surface Methodology (RSM) approach using DESIGN EXPERT 6.0 (DOE) software was used to design the experiments. The experiments were performed under two different cutting conditions. The first one was cutting under normal conditions, while the other was cutting under the application of magnetic fields from two permanent magnets positioned on opposite sides of the cutter. Surface roughness was measured using Mitutoyo SURFTEST SV-500 profilometer. The subsequent analysis showed that surface roughness was significantly reduced (by as much as 67.21%) when machining was done under the influence of magnetic field. The experimental results were then used to develop a second order empirical mathematical model equation for surface roughness and validated to 95% confidence level by using ANOVA. Finally, desirability function approach was used to optimize the surface roughness within the limiting values attainable in end milling.

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.

Modeling & Analysis of End Milling Process Parameters Using Artificial Neural Networks

2014 ◽  
Vol 592-594 ◽  
pp. 2733-2737 ◽  
Author(s):  
G. Harinath Gowd ◽  
K. Divya Theja ◽  
Peyyala Rayudu ◽  
M. Venugopal Goud ◽  
M .Subba Roa
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Process Parameters ◽  
End Milling ◽  
Milling Process ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Artificial Neural ◽  
End Milling Process

For modeling and optimizing the process parameters of manufacturing problems in the present days, numerical and Artificial Neural Networks (ANN) methods are widely using. In manufacturing environments, main focus is given to the finding of Optimum machining parameters. Therefore the present research is aimed at finding the optimal process parameters for End milling process. The End milling process is a widely used machining process because it is used for the rough and finish machining of many features such as slots, pockets, peripheries and faces of components. The present work involves the estimation of optimal values of the process variables like, speed, feed and depth of cut, whereas the metal removal rate (MRR) and tool wear resistance were taken as the output .Experimental design is planned using DOE. Optimum machining parameters for End milling process were found out using ANN and compared to the experimental results. The obtained results provβed the ability of ANN method for End milling process modeling and optimization.

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