Evaluation of surface roughness during turning of Al-SiC and Al-SiC-Gr composites

2018 ◽  
Vol 14 (5) ◽  
pp. 874-890
Author(s):  
P. Suresh ◽  
T. Poongodi
Keyword(s):  
Surface Roughness ◽  
Wear Resistance ◽  
Response Surface ◽  
Dimensional Stability ◽  
Cutting Conditions ◽  
Depth Of Cut ◽  
New Materials ◽  
Content Type ◽  
Higher Temperature ◽  
Strength And Stiffness

Purpose In the current scenario, new materials are gaining popularity due to higher specific properties of strength and stiffness, increase in wear resistance, dimensional stability at higher temperature, etc. Subsequently, the need for precise machining has also been increased enormously. The purpose of this paper is to study the surface roughness during the turning of Al-10%SiC and Al-5%SiC-5%Gr composites under different cutting conditions. Design/methodology/approach Artificial neural network (ANN) has been effectively employed in solving problems with effortless computation in the areas such as fault diagnosis, process identification, property estimation, data smoothing and error filtering, product design and development, optimisation and estimation of activity coefficients. Response surface method is also used to analyse the problems involving a number of input parameters and their corresponding relationship between one or more measured dependent responses. Using Design Expert.8 evaluation software package, a simpler and more efficient statistical RSM model has been designed. RSM models are created by using 27 experimental data measurements obtained from different turning conditions of aluminium alloy composites. Findings In this work, the surface roughness during turning of Al-10%SiC and Al-5%SiC-5%Gr composites under different cutting conditions has been studied. The surface roughness value is proportional with the increase in feed rate and depth of cut while inversely proportional with the cutting speed. In all turning conditions, Al-10%SiC composite has lower surface roughness values than Al-5%SiC-5%Gr hybrid composite. An ANN and response surface models have been developed to predict the surface roughness of machined surface. The experimental results concur well with predicted models. Originality/value In the present trend, new materials are gaining popularity due to higher specific properties of strength and stiffness, increase in wear resistance, dimensional stability at higher temperature, etc. Subsequently, the need for precise machining has also been increased enormously. In this work, the surface roughness during turning of Al-10%SiC and Al-5%SiC-5%Gr composites under different cutting conditions has been studied.

Parameter Optimization of Ball End Milling Process on Inconel 718 Using RSM and TLBO Algorithm

2015 ◽  
Vol 15 (3) ◽  
pp. 293-300 ◽  
Author(s):  
Nandkumar N. Bhopale ◽  
Nilesh Nikam ◽  
Raju S. Pawade
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Surface Integrity ◽  
Inconel 718 ◽  
Tool Path ◽  
End Milling ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Ball End Milling

AbstractThis paper presents the application of Response Surface Methodology (RSM) coupled with Teaching Learning Based Optimization Technique (TLBO) for optimizing surface integrity of thin cantilever type Inconel 718 workpiece in ball end milling. The machining and tool related parameters like spindle speed, milling feed, axial depth of cut and tool path orientation are optimized with considerations of multiple response like deflection, surface roughness, and micro hardness of plate. Mathematical relationship between process parameters and deflection, surface roughness and microhardness are found out by using response surface methodology. It is observed that after optimizing the process that at the spindle speed of 2,000 rpm, feed 0.05 mm/tooth/rev, plate thickness of 5.5 mm and 15° workpiece inclination with horizontal tool path gives favorable surface integrity.

Surface Roughness Identification in End Milling Using Vibration Signals and Fuzzy Clustering

2016 ◽  
Author(s):  
Issam Abu-Mahfouz ◽  
Amit Banerjee ◽  
A. H. M. Esfakur Rahman
Keyword(s):  
Surface Roughness ◽  
Fuzzy Clustering ◽  
Wavelet Transforms ◽  
Fourier Transforms ◽  
End Milling ◽  
Cutting Conditions ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Machined Surface ◽  
Vibration Signals

The study presented involves the identification of surface roughness in Aluminum work pieces in an end milling process using fuzzy clustering of vibration signals. Vibration signals are experimentally acquired using an accelerometer for varying cutting conditions such as spindle speed, feed rate and depth of cut. Features are then extracted by processing the acquired signals in both the time and frequency domain. Techniques based on statistical parameters, Fast Fourier Transforms (FFT) and the Continuous Wavelet Transforms (CWT) are utilized for feature extraction. The surface roughness of the machined surface is also measured. In this study, fuzzy clustering is used to partition the feature sets, followed by a correlation with the experimentally obtained surface roughness measurements. The fuzzifier and the number of clusters are varied and it is found that the partitions produced by fuzzy clustering in the vibration signal feature space are related to the partitions based on cutting conditions with surface roughness as the output parameter. The results based on limited simulations are encouraging and work is underway to develop a larger framework for online cutting condition monitoring system for end milling.

Erosion characteristics on surface texture of additively manufactured AlSi10Mg alloy in SiO2 quartz added slurry environment

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Recep Demirsöz ◽  
Mehmet Erdl Korkmaz ◽  
Munish Kumar Gupta ◽  
Alberto Garcia Collado ◽  
Grzegorz M. Krolczyk
Keyword(s):  
Surface Roughness ◽  
Weight Loss ◽  
Wear Resistance ◽  
Erosive Wear ◽  
Oxide Ceramics ◽  
Slurry Erosion ◽  
Content Type ◽  
Test Setup ◽  
Quartz Sands ◽  
Erosion Test

Purpose The main purpose of this work is to explore the erosion wear characteristics of additively manufactured aluminium alloy. Additive manufacturing (AM), also known as three-dimensional (3D) manufacturing, is the process of manufacturing a part designed in a computer environment using different types of materials such as plastic, ceramic, metal or composite. Similar to other materials, aluminum alloys are also exposed to various wear types during operation. Production efficiency needs to be aware of its reactions to wearing mechanisms. Design/methodology/approach In this study, quartz sands (SiO2) assisted with oxide ceramics were used in the slurry erosion test setup and its abrasiveness on the AlSi10Mg aluminum alloy material produced by the 3D printer as selective laser melting (SLM) technology was investigated. Quartz was sieved with an average particle size of 302.5 µm, and a slurry environment containing 5, 10 and 15% quartz by weight was prepared. The experiments were carried out at the velocity of 1.88 (250 rpm), 3.76 (500 rpm) and 5.64 m/s (750 rpm) and the impact angles 15, 45 and 75°. Findings With these experimental studies, it has been determined that the abrasiveness of quartz sand prepared in certain particle sizes is directly related to the particle concentration and particle speed, and that the wear increases with the increase of the concentration and rotational speed. Also, the variation of weight loss and surface roughness of the alloy was investigated after different wear conditions. Surface roughness values at 750 rpm speed, 10% concentration and 75° impingement angle are 0.32 and 0.38 µm for 0 and 90° samples, respectively, with a difference of approximately 18%. Moreover, concerning a sample produced at 0°, the weight loss at 250 rpm at 10% concentration and 45° particle impact angle is 32.8 mg, while the weight loss at 500 rpm 44.4 mg, and weight loss at 750 rpm is 104 mg. Besides, the morphological structures of eroded surfaces were examined using the scanning electron microscope to understand the wear mechanisms. Originality/value The researchers verified that this specific coating condition increases the slurry wear resistance of the mentioned steel. There are many studies about slurry wear tests; however, there is no study in the literature about the quartz sand (SiO2) assisted slurry-erosive wear of AlSi10Mg alloy produced with AM by using SLM technology. This study is needed to fill this gap in the literature and to examine the erosive wear capability of this current material in different environments. The novelty of the study is the use of SiO2 quartz sands assisted by oxide ceramics in different concentrations for the slurry erosion test setup and the investigations on erosive wear resistance of AlSi10Mg alloy manufactured by AM.

Sustainable machining. Modeling and optimization of temperature and surface roughness in the milling of AISI D2 steel

2019 ◽  
Vol 71 (2) ◽  
pp. 267-277 ◽  
Author(s):  
Aqib Mashood Khan ◽  
Muhammad Jamil ◽  
Ahsan Ul Haq ◽  
Salman Hussain ◽  
Longhui Meng ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Empirical Modeling ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Aisi D2 Steel ◽  
Content Type ◽  
Sustainable Machining ◽  
Aisi D2 ◽  
D2 Steel

Purpose Sustainable machining is a global consensus and the necessity to cope up the serious environmental threats. Minimum quantity lubrication (MQL) and nanofluids-based MQL(NFMQL) are state-of-the-art sustainable lubrication modes. The purpose of this study is to investigate the effect of process parameters, such as feed rate, depth of cut and cutting fluid flow rate, on temperature and surface roughness of the manufactured pieces during face milling of the AISI D2 steel. Design/methodology/approach A statistical technique called response surface methodology with Box–Behnken Design was used to design experimental runs, and empirical modeling was presented. Analysis of variance was carried out to evaluate the model’s accuracy and the validation of the applied technique. Findings A comprehensive analysis revealed the superiority of implementing NFMQL in comparison to MQL within the levels of process parameters. The comparison has shown a significant reduction of temperature under NFMQL at the tool-workpiece interface from 16.2 to 34.5 per cent and surface roughness from 11.3 to 12 per cent. Practical implications This research is useful for practitioners to predict the responses in workshop and select appropriate cutting parameters. Moreover, this research will be helpful to reduce the resource which will ultimately save energy consumption and cost. Originality/value To cope with the industrial challenges and tribological issues associated with the milling of AISI D2 steel, experiments were conducted in a distinct machining mode with innovative cooling/lubrication. Until now, few studies have addressed the key lubrication effects of Al2O3-based nanofluid on the machinability of D2 steel under NFMQL lubrication condition.

Machining Evaluation of High-Speed Milling for Thin-Wall Machining of Al7075-T651

2014 ◽  
Vol 541-542 ◽  
pp. 785-791 ◽  
Author(s):  
Joon Young Koo ◽  
Pyeong Ho Kim ◽  
Moon Ho Cho ◽  
Hyuk Kim ◽  
Jeong Kyu Oh ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Surface Integrity ◽  
Cutting Forces ◽  
High Speed ◽  
Surface Condition ◽  
Cutting Conditions ◽  
Depth Of Cut ◽  
Thin Wall ◽  
Machined Surface ◽  
High Speed Milling

This paper presents finite element method (FEM) and experimental analysis on high-speed milling for thin-wall machining of Al7075-T651. Changes in cutting forces, temperature, and chip morphology according to cutting conditions are analyzed using FEM. Results of machining experiments are analyzed in terms of cutting forces and surface integrity such as surface roughness and surface condition. Variables of cutting conditions are feed per tooth, spindle speed, and axial depth of cut. Cutting conditions to improve surface integrity were investigated by analysis on cutting forces and surface roughness, and machined surface condition.

Modeling & Optimization of Surface Roughness & Vibration Amplitude in Heat Assisted End Milling of SKD 11 Tool Steel Using Ball Nose Tool

2012 ◽  
Vol 538-541 ◽  
pp. 799-803 ◽  
Author(s):  
A.K.M. Nurul Amin ◽  
Muhd Hafiz B. Md. Saad ◽  
Muammer Din Arif
Keyword(s):  
Surface Roughness ◽  
Response Surface ◽  
Tool Steel ◽  
Vibration Amplitude ◽  
End Milling ◽  
Heating Temperature ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Primary Input ◽  
Coated Carbide

Tool steel - SKD 11 is frequently used in industries for making dies and molds. This grade is chosen for its toughness, strength, and hardness maintained up to high temperature. However, the same properties make the steel extremely difficult and expensive to machine using conventional approaches. Heat assisted machining has been found wide spread application in recent years to improve machinability of difficult-to-cut materials. This research paper presents the outcome of an investigation on heat assisted end milling of SKD 11 conducted on a vertical machining center using ball nose coated carbide inserts. The Design of Experiments (DoE) was done using the Response Surface Methodology, in order to develop empirical mathematical models of surface roughness and vibration in terms of cutting speed, feed, axial depth of cut, and heating temperature. The models were checked for significance using Analysis of Variance (ANOVA). 3-D response surface graphs of the interactions of primary cutting parameters with the responses were plotted. Optimization was then performed by using the desirability function approach. From the graphs and optimized results it was concluded that the primary input parameters could be controlled in order to reduce vibration amplitude and produce semi-finished machined surfaces applying induction heat assisted technique.

Optimization of Surface Grinding Process Parameters for Minimum Surface Roughness in AISI 1080 Using Response Surface Methodology

2014 ◽  
Vol 984-985 ◽  
pp. 118-123 ◽  
Author(s):  
S. Periyasamy ◽  
M. Aravind ◽  
D. Vivek ◽  
K.S. Amirthagadeswaran
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Process Parameters ◽  
Surface Grinding ◽  
Steel Plates ◽  
Medium Effect ◽  
Depth Of Cut ◽  
Design Expert ◽  
Minimum Surface

In this study, the response surface methodology was used to optimize the process parameters of constant speed horizontal spindle surface grinding. The experiments were conducted based on the design expert software. The surface roughness characteristics were investigated in AISI 1080 steel plates using A60V5V grinding wheels. The optimum parameters for minimum surface roughness were found using Design Expert software. The parameters for a particular surface roughness value can also be determined using the results of this experiment. This results shows that feed has a greater effect on surface roughness and feed has medium effect on surface roughness. While dressing depth of cut has a very minimal effect on surface roughness.

Definition of Cutting Conditions for Thin-to-Thin Milling of Aerospace Low Rigidity Parts

2008 ◽  
Author(s):  
F. J. Campa ◽  
L. N. Lopez de Lacalle ◽  
G. Urbikain ◽  
D. Ruiz
Keyword(s):  
Dimensional Stability ◽  
High Speed ◽  
Tool Path ◽  
Three Dimensional ◽  
Stability Diagram ◽  
Spindle Speed ◽  
Cutting Conditions ◽  
Depth Of Cut ◽  
Compliant Parts ◽  
Tool Position

The main drawback of the high speed milling of monolithic parts for the aerospace industry is the high buy-to-fly ratio that leads to a huge material waste. This problem is caused by the need to stiffen the part during the machining in order to avoid chatter, excessive vibration and residual stresses. The present work proposes a methodology for the milling of compliant parts based on the selection of cutting conditions free of chatter. First, the modal parameters of the part in the most problematic stages of the machining are calculated by means of the finite elements method. Secondly, a three-dimensional stability model is used in each stage to calculate a three-dimensional stability lobes diagram dependent on the tool position along the whole tool path. Given the fact that the depth of cut is defined by the bulk of material, the three-dimensional stability diagram can be reduced to a two-dimensional one, which relates tool position during the machining and spindle speed, and indicates how to change the spindle speed in order to avoid the unstable areas. What is more, the proposed methodology can also be used to dimension the bulk of material, select the proper tool or improve the fixturing of the part. Finally, the methodology is validated experimentally on a test part.

Optimization of Surface Roughness in Turning of Ti-6Al-4V Using Response Surface Methodology and TLBO

2015 ◽  
Author(s):  
Neelesh Ku. Sahu ◽  
A. B. Andhare
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Titanium Alloys ◽  
Response Surface ◽  
Feed Rate ◽  
Cutting Speed ◽  
Maximum Error ◽  
Depth Of Cut ◽  
Interaction Variables ◽  
Teaching Learning

Surface roughness is an important surface integrity parameter for difficult to cut alloys such as Titanium alloys (Ti-6Al-4V). In the present work, initially a mathematical model is developed for predicting surface roughness for turning operation using Response Surface Methodology (RSM). Later, a recently developed advanced optimization algorithm named as Teaching Learning Based Optimization (TLBO) is used for further parameter optimization of the equation developed using RSM. The design of experiments was performed using central composite design (CCD). Analysis of variance (ANOVA) demonstrated the significant and non-significant parameters as well as validity of predicted model. RSM describes the effect of main and mixed (interaction) variables on the surface roughness of titanium alloys. RSM analysis over experimental results showed that surface roughness decreased as cutting speed increased whereas it increased with increase in feed rate. Depth of cut had no effect on surface roughness. By comparing the predicted and measured values of surface roughness the maximum error was found to be 7.447 %. It indicates that the developed model can be effectively used to predict the surface roughness. Further optimization of the roughness equation was carried out by TLBO method. It gave minimum surface roughness as 0.3120 μm at the cutting speed of 1704 RPM (171.217 m/min), feed rate of 55.6 mm/min (.033 mm/rev) and depth of cut of 0.7 mm. These results were confirmed by confirmation experiment and were better than that of RSM.

The effect of EBM process parameters upon surface roughness

2016 ◽  
Vol 22 (3) ◽  
pp. 495-503 ◽  
Author(s):  
Rebecca Klingvall Ek ◽  
Lars-Erik Rännar ◽  
Mikael Bäckstöm ◽  
Peter Carlsson
Keyword(s):  
Surface Roughness ◽  
Electron Beam ◽  
Surface Properties ◽  
Process Parameters ◽  
Electron Beam Melting ◽  
Design Methodology ◽  
New Materials ◽  
Content Type ◽  
Melt Pool ◽  
Practical Implications

Purpose The surface roughness of products manufactured using the additive manufacturing (AM) technology of electron beam melting (EBM) has a special characteristic. Different product applications can demand rougher or finer surface structure, so the purpose of this study is to investigate the process parameters of EBM to find out how they affect surface roughness. Design/methodology/approach EBM uses metal powder to manufacture metal parts. A design of experiment plan was used to describe the effects of the process parameters on the average surface roughness of vertical surfaces. Findings The most important electron beam setting for surface roughness, according to this study, is a combination of “speed and current” in the contours. The second most important parameter is “contour offset”. The interaction between the “number of contours” and “contour offset” also appears to be important, as it shows a much higher probability of being active than any other interaction. The results show that the “line offset” is not important when using contours. Research limitations/implications This study examined “contour offset”, “number of contours”, “speed in combination with current” and “line offset”, which are process parameters controlling the electron beam. Practical implications The surface properties could have an impact on the product’s performance. A reduction in surface processing will not only save time and money but also reduce the environmental impact. Originality/value Surface properties are important for many products. New themes containing process parameters have to be developed when introducing new materials to EBM manufacturing. During this process, it is very important to understand how the electron beam affects the melt pool.

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