Multi Response Optimization of Setting Process Variables in Face Milling of ZE41 Magnesium Alloy using Ranking Algorithms and ANOVA

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
S.P. Sundar Singh Sivam ◽  
V.G. Umasekar ◽  
Ganesh Babu Loganathan ◽  
D Kumaran ◽  
K. Saravanan
Keyword(s):  
Cutting Speed ◽  
Chip Thickness ◽  
Numerical Control ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Setting Process ◽  
Order Preference ◽  
Tool Diameter ◽  
Cutting Point

This study presents the optimization of machining parameters on ZE41 Mg alloy fabricated by gravity die casting and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Focus on the optimization of machining parameters using the technique to get minimum surface roughness, cutting force, thermal stress, residual stress, chip thickness and maximum MRR. A number of machining experiments were conducted based on the L27 orthogonal array on computer numerical control vertical machining center. The experiments were performed on ZE41 using cutting tool of an ISO 460. 1-1140-034A0-XM GC3 of 20, 25 and 30mm diameter with cutting point 140 degrees, for different cutting conditions. TOPSIS and ANOVA were used to work out the fore most important parameters cutting speed, feed rate, depth of cut and tool diameter which affect the response. The expected values and measured values are fairly close. Finally, the study for optimizing machining process is surveyed and results show improvement in real experiments.

scholarly journals Multi Response Optimization of Setting Input Variables for Getting Better Product Quality in Machining of Magnesium AM60 by Grey Relation Analysis and ANOVA

2018 ◽  
Author(s):  
S. P. Sundar Singh Sivam ◽  
Sathiya Moorthy Karuppaiah ◽  
Bhaskar Karthik Yedida ◽  
Jai Ram Atluri ◽  
Shubhang Mathur
Keyword(s):  
Orthogonal Array ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Cnc Machine ◽  
Grey Relation Analysis ◽  
Relation Analysis ◽  
Tool Diameter ◽  
Cutting Point ◽  
Grey Relation

This study presents the optimization of Machining parameters on AM60 Mg alloy manufactured by Gravity Die Casting and with responses supported orthogonal array with Grey relation analysis. Focuses on the optimization of Machining input parameters using the technique to get minimum surface roughness, Minimum Tool Wear, Cutting Time, Power Requirement, Torque and Maximum MRR. A number of Machining trails were conducted based on the L9 orthogonal array on CNC machine. The experiments were performed on AM60 alloy using cutting tool of an ISO 460.1-1140-034A0-XM GC3 of 12,16 and 25 mm diameter with cutting point 140 degrees, throughout the experimental work under different cutting conditions. Grey relation analysis & ANOVA were used to work out the fore most important parameters Cutting speed, feed rate, Depth of Cut and Tool Diameter which affects the Response. The expected response and measured response are fairly close. The given model could be used to select the level of Machining parameters.

scholarly journals The Experimental Investigation of Surface Roughness After Dry Turning of Steel S235

2019 ◽  
Vol 26 (4) ◽  
pp. 179-184
Author(s):  
Justyna Molenda
Keyword(s):  
Surface Roughness ◽  
Surface Finish ◽  
Cutting Speed ◽  
Scientific Work ◽  
Machining Process ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Workpiece Material ◽  
Important Indicator

AbstractNowadays lot of scientific work inspired by industry companies was done with the aim to avoid the use of cutting fluids in machining operations. The reasons were ecological and human health problems caused by the cutting fluid. The most logical solution, which can be taken to eliminate all of the problems associated with the use of cooling lubricant, is dry machining. In most cases, however, a machining operation without lubricant finds acceptance only when it is possible to guarantee that the part quality and machining times achieved in wet machining are equalled or surpassed. Surface finish has become an important indicator of quality and precision in manufacturing processes and it is considered as one of the most important parameter in industry. Today the quality of surface finish is a significant requirement for many workpieces. Thus, the choice of optimized cutting parameters is very important for controlling the required surface quality. In the present study, the influence of different machining parameters on surface roughness has been analysed. Experiments were conducted for turning, as it is the most frequently used machining process in machine industry. All these parameters have been studied in terms of depth of cut (ap), feed rate (f) and cutting speed (vc). As workpiece, material steel S235 has been selected. This work presents results of research done during turning realised on conventional lathe CDS 6250 BX-1000 with severe parameters. These demonstrate the necessity of further, more detailed research on turning process results.

scholarly journals OPTIMASI PARAMETER PERMESINAN TERHADAP WAKTU PROSES PADA PEMROGRAMAN CNC MILLING DENGAN BERBASIS CAD/CAM

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
I G.N.K. Yudhyadi ◽  
Tri Rachmanto ◽  
Adnan Dedy Ramadan
Keyword(s):  
Cutting Speed ◽  
Operation Time ◽  
Milling Process ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Milling Machine ◽  
Cnc Milling ◽  
Cnc Milling Machine ◽  
Machining Parameter

Milling process is one of many machining processes for manufacturing component. The length of time in the process of milling machining is influenced by selection and design of machining parameters including cutting speed, feedrate and depth of cut. The purpose of this study to know the influence of cutting speed, feedrate and depth of cut as independent variables versus operation time at CNC milling process as dependent variables. Each independent variable consists of three level of factors; low, medium and high.Time machining process is measured from operation time simulation program, feed cut length and rapid traverse length. The results of statistically from software simulation MasterCam X Milling, then do comparison to CNC Milling machine.  The data from experiments was statistical analyzed by Anova and Regression methods by software minitab 16.Results show that the greater feedrate and depth of cut shorten the operation time of machinery, whereas cutting speed is not significant influence. Depth of cut has the most highly contribution with the value of 49.56%, followed by feedrate 43% and cutting speed 0.92%. Optimal time of machining process total is 71.92 minutes, with machining parameter on the condition cutting speed is 75360 mm/minutes, feedrate is 800 mm/minutes and depth of cut = 1 mm. Results of comparison time machining process in software Mastercam X milling with CNC Milling machine indicates there is difference not significant with the value of 0,35%.

scholarly journals The influence of machining parameters on surface roughness of MDF in milling operation

BioResources ◽  
2019 ◽  
Vol 14 (2) ◽  
pp. 3266-3277
Author(s):  
Ümmü K. İşleyen ◽  
Mehmet Karamanoğlu
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Medium Density Fiberboard ◽  
Spindle Speed ◽  
Numerical Control ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Milling Operation ◽  
Four Levels ◽  
Tool Diameter

This paper examined the effect of machining parameters on surface roughness of medium density fiberboard (MDF) machined using a computer numerical control (CNC) router. The machining parameters such as spindle speed, feed rate, depth of cut, and tool diameter were examined for milling. The experiments were conducted at two levels of spindle speeds, four levels of feed rates, two levels of tool diameters, and two levels of axial depths of cut. The surface roughness values of MDF grooved by CNC were measured with stylus-type equipment. Statistical methods were used to determine the effectiveness of the machining parameters on surface roughness. The influence of each milling parameter affecting surface roughness was analyzed using analysis of variance (ANOVA). The significant machining parameters affecting the surface roughness were the feed rate, spindle speed, and tool diameter (p < 0.05). There was no significant influence of axial depth of cut on the surface roughness. The surface roughness decreased with increasing spindle speed and decreasing feed rate. The value of surface roughness increased with the increase of tool diameter.

Cutting forces analysis of micro-milling process on Inconel 718 – a finite element approach

2020 ◽  
Vol 11 (02) ◽  
pp. 2050011
Author(s):  
Padmaja Tripathy ◽  
Kalipada Maity
Keyword(s):  
Finite Element ◽  
Cutting Forces ◽  
Inconel 718 ◽  
Cutting Speed ◽  
Fem Analysis ◽  
Milling Process ◽  
Machining Process ◽  
Micro Milling ◽  
Depth Of Cut ◽  
Machining Parameters

This paper presents a modeling and simulation of micro-milling process with finite element modeling (FEM) analysis to predict cutting forces. The micro-milling of Inconel 718 is conducted using high-speed steel (HSS) micro-end mill cutter of 1mm diameter. The machining parameters considered for simulation are feed rate, cutting speed and depth of cut which are varied at three levels. The FEM analysis of machining process is divided into three parts, i.e., pre-processer, simulation and post-processor. In pre-processor, the input data are provided for simulation. The machining process is further simulated with the pre-processor data. For data extraction and viewing the simulated results, post-processor is used. A set of experiments are conducted for validation of simulated process. The simulated and experimental results are compared and the results are found to be having a good agreement.

Relationship Between Measurement of Cutting Force and Sensor Location in Turning Process

2012 ◽  
Vol 59 (2) ◽  
Author(s):  
Jaharah A. Ghani ◽  
Poh Siang Jye ◽  
Che Hassan Che Haron ◽  
Muhammad Rizal ◽  
Mohd Zaki Nuawi
Keyword(s):  
Cutting Force ◽  
Strain Gauge ◽  
Cutting Speed ◽  
Strain Gauges ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Sensor Location ◽  
Turning Process ◽  
Feed Force ◽  
Cutting Point

Turning process is widely used in the production of components for automotive and aerospace applications. The machinability of a work material is commonly assessed in terms of cutting tool life, surface finish, and cutting force. These responses are dependent on machining parameters such as cutting speed, feed rate, and depth of cut. In this study, the relationships between cutting force, cutting speed, and sensor location in the turning process were investigated. Strain gauge was chosen as the sensor for the detection of cutting force signal during turning of hardened plain carbon steel JIS S45C. Two strain gauges were mounted on a tool holder at a defined location of I, II, or III at a distance of 37, 42, or 47 mm, respectively, from the cutting point. Only one set of machining experiments was conducted at spindle speed = 1000 rpm, feed = 0.25 mm/rev, and depth of cut = 0.80 mm. The turning process was stopped and the insert was discarded when average flank wear reached 0.30 mm. The main cutting force and the feed force for each cycle measured by the strain gauges at location I, II, and III were collected and analyzed. Results show that when cutting speed was increased, the main cutting force and the feed force were decreased accordingly. The change of was inversely proportional to the change of cutting speed, but the did not decrease continuously and behaved contrarily. A strain gauge placed at a distance of approximately 43 mm from the cutting point was found to be the best and most suitable for sensing accurate force signals.

Minimized Wear and Debris Generation Through Optimized Machining of Co-Cr-Mo Alloys for Use in Metal-on-Metal Hip Implants

2012 ◽  
Author(s):  
Ashish Deshpande ◽  
Shu Yang ◽  
Dave Puleo ◽  
David Pienkowski ◽  
Oscar Dillon ◽  
...  
Keyword(s):  
Residual Stresses ◽  
Wear Debris ◽  
Wear Behavior ◽  
Cutting Speed ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Machining Conditions ◽  
Metal On Metal ◽  
Tool Edge

More than 380,000 hips are replaced with total joint prostheses each year in the U.S. Wear debris generated by metal-on-metal implant designs is of concern due to potential adverse biological effects arising from chronic exposure of human tissue to the wear debris. This paper presents a new methodology for optimizing the wear performance of prosthesis made of Co-Cr-Mo alloys by varying tool edge geometry and machining conditions to alter the wear behavior of this alloy, while also controlling the residual stresses induced during the machining process. The machining process causes inhomogeneous inelastic deformations near the surface layer of machined parts which create residual stresses in the surface of machined components. Residual stresses in the machined surface and the subsurface are affected by cutting tool material, tool geometry, workpiece, tool-work interface conditions, and the cutting parameters such as feed rate, depth of cut and cutting speed. In the current work, residual stresses were measured using X-ray diffraction technique (XRD). The surface residual stresses in two directions (radial and hoop) were measured on the machined pins after machining with different machining conditions, but prior to the wear test. Wear behavior of Co-Cr-Mo alloy pin specimens, produced from machining with varying tool edge geometry and machining conditions, was studied using a custom-made biaxial motion pin-on-disc tribological testing system in which the pin specimen is immersed in a simulated bio-fluid environment. Wear-induced weight loss (± 10 μg) and changes in surface roughness (± 0.001 μm) were obtained at 100,000 cycle intervals upto 500,000 cycles. Metallographic analysis was performed on the machined pin specimens to analyze the microstructure and microhardness before and after testing. The rate of wear for the specimens was lowest for those pins where the change of the subsurface microhardness was small due to prevention of additional steady state wear after the initial run-in wear in the wear tester. A combination or response surface methodology and genetic algorithm (GA) was used in to optimize the various machining parameters for minimized wear generation. The optimal combination of the four machining parameters (feed 0.18mm/rev, nose radius 0.6 mm, cutting speed 27.6 m/min and depth of cut 0.38) produced the largest compressive residual stresses on the surface and subsurface of the implants thereby reducing the wear/debris generation by about fifty percent.

Optimizing the Machining Parameters in Glass Grinding Operation on the CNC Milling Machine for Best Surface Roughness

2010 ◽  
Vol 154-155 ◽  
pp. 721-726 ◽  
Author(s):  
Mohd Sayuti ◽  
Ahmed Aly Diaa Mohammed Sarhan ◽  
Mohd Hamdi Bin Abd Shukor
Keyword(s):  
Surface Roughness ◽  
Machining Process ◽  
Depth Of Cut ◽  
Response Analysis ◽  
Machining Parameters ◽  
Milling Machine ◽  
Cnc Milling ◽  
Cnc Machine ◽  
Cnc Milling Machine ◽  
Tool Diameter

Glass is one of the most difficult materials to be machined due to its brittle nature and unique structure such that the fracture is often occurred during machining and the surface finish produced is often poor. CNC milling machine is possible to be used with several parameters making the machining process on the glass special compared to other machining process. However, the application of grinding process on the CNC milling machine would be an ideal solution in generating special products with good surface roughness. This paper studies how to optimize the different machining parameters in glass grinding operation on CNC machine seeking for best surface roughness. These parameters include the spindle speed, feed rate, depth of cut, lubrication mode, tool type, tool diameter and tool wear. To optimize these machining parameters in which the most significant parameters affecting the surface roughness can be identified, Taguchi optimization method is used with the orthogonal array of L8(26). However, to obtain the most optimum parameters for best surface roughness, the signal to noise (S/N) response analysis and Pareto analysis of variance (ANOVA) methods are implemented. Finally, the confirmation test is carried out to investigate the improvement of the optimization. The results showed an improvement of 8.91 % in the measured surface roughness.

Optimisation of Machining Parameters for Milling Polyetheretherketones (PEEK) Biomaterial

2014 ◽  
Vol 699 ◽  
pp. 198-203 ◽  
Author(s):  
Raja Izamshah Raja Abdullah ◽  
Aaron Yu Long ◽  
Md Ali Mohd Amran ◽  
Mohd Shahir Kasim ◽  
Abu Bakar Mohd Hadzley ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Tools ◽  
Cutting Speed ◽  
Processing Parameters ◽  
Machining Process ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Dimensional Precision ◽  
Good Surface

Polyetheretherketones (PEEK) has been widely used as biomaterial for trauma, orthopaedic and spinal implants. Component made from Polyetheretherketones generally required additional machining process for finishing which can be a problem especially to attain a good surface roughness and dimensional precision. This research attempts to optimize the machining and processing parameters (cutting speed, feed rate and depth of cut) for effectively machining Polyetheretherketones (PEEK) implant material using carbide cutting tools. Response Surface Methodology (RSM) technique was used to assess the effects of the parameters and their relations towards the surface roughness values. Based on the analysis results, the optimal machining parameters for the minimum surface roughness values were by using cutting speed of 5754 rpm, feed rate of 0.026 mm/tooth and 5.11 mm depth of cut (DOC).

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.

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