scholarly journals The effects of the process parameters in electrochemical machining on the surface quality

2020 ◽  
Vol 3 (SI1) ◽  
pp. First
Author(s):  
Nguyen Thi Bich Nhung ◽  
Dao Thanh Liem ◽  
Truong Quoc Thanh
Keyword(s):  
Surface Roughness ◽  
Surface Quality ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
Electrolyte Concentration ◽  
Removal Rate ◽  
Electrochemical Machining ◽  
Electrode Gap

Based on the number of previous studies, this study aims to investigate the effects of process parameters of an Electrochemical Machining process, which are electrolyte concentration, the voltage applied to the machine, feed rate of the electrode, and Inter-Electrode Gap between tool and workpiece. Aluminum samples of 25 mm diameter x 25 mm height and 30mm diameter x 25mm height of the tool is made up of copper with a circular cross-section with 2 mm internal hole. The design of the system is based on the Taguchi method. Here, the signal-to-noise (S/N) model, the analysis of variance (ANOVA) and regression analyses are applied to determine optimal levels and to investigate the effects of these parameters on surface quality. Finally, the experiments that use the optimal levels of machining parameters are conducted to verify the effects of the process parameters on the surface quality of the products. The results pointed out a set of optimal parameters of the ECM process. The Inter-Electrode Gap between the tool and workpiece has extremely effected on these Material Removal rates and surface roughness. The Material Removal Rate increases with diseases in Inter-Electrode Gap, and Ra diseases with diseases in Inter-Electrode Gap. The experimental results show that maximum Material Removal Rate has obtained with electrolyte concentration at 100 g/l, feed rate at 0.0375 mm/min, the voltage at 15V, and Inter-Electrode Gap at 0.5mm. The minimum Ra has obtained with electrolyte concentration at 80 g/l, feed rate at 0.0468 mm/min, the voltage at 10V, and Inter-Electrode Gap at 0.5mm. This result has led to need studies on these parameters in Electrochemical Machining, which are improving productivities and surface roughness of the products.   

scholarly journals Prediction of Surface Roughness and Material Removal Rate in Electrochemical Machining Using Taguchi Method

2017 ◽  
Vol 12 (4) ◽  
pp. 72-80 ◽  
Author(s):  
Abbas Fadhil Ibrahim
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Electrolyte Concentration ◽  
Removal Rate ◽  
Electrochemical Machining ◽  
Maintenance Cost ◽  
Process Conditions ◽  
Machining Parameters

Electrochemical machining is one of the widely used non-conventional machining processes to machine complex and difficult shapes for electrically conducting materials, such as super alloys, Ti-alloys, alloy steel, tool steel and stainless steel.  Use of optimal ECM process conditions can significantly reduce the ECM operating, tooling, and maintenance cost and can produce components with higher accuracy. This paper studies the effect of process parameters on surface roughness (Ra) and material removal rate (MRR), and the optimization of process conditions in ECM. Experiments were conducted based on Taguchi’s L9 orthogonal array (OA) with three process parameters viz. current, electrolyte concentration, and inter-electrode gap. Signal-to-noise (S/N), the analysis of variance (ANOVA) was employed to find the optimal levels and to analyze the effect of electrochemical machining parameters on Ra and MRR. The surface roughness of the workpiece was decreased with the increase in current values and electrolyte concentration while causing an increase in material removal rate. The ability of the independent values to predict the dependent values (R2) were 87.5% and 96.3% for mean surface roughness and material removal rate, respectively.

scholarly journals Multi-Objective Process Parameter Optimization for Surface Roughness and Material Removal Rate in Face Milling of Al 6061 T6 Alloy

2019 ◽  
Vol 9 (2) ◽  
pp. 137-142
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Feed Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Face Milling ◽  
Machining Process ◽  
Depth Of Cut ◽  
Al 6061

This study uses Taguchi methodology and Gray Relational Analysis approach to explore the optimization of face milling process parameters for Al 6061 T6 alloy.Surface Roughness (Ra), Material Removal Rate (MRR) has been identified as the objective of performance and productivity.The tests were performed by selecting cutting speed (mm / min), feed rate (mm / rev) and cutting depth (mm) at three settings on the basis of Taguchi's L9 orthogonal series.The grey relational approach was being used to establish a multiobjective relationship between both the parameters of machining and the characteristics of results. To find the optimum values of parameters in the milling operation, the response list and plots are used and found to be Vc2-f1-d3. To order to justify the optimum results, the confirmation tests are performed.The machining process parameters for milling were thus optimized in this research to achieve the combined goals such as low surface roughness and high material removal rate on Aluminum 6061 t6.It was concluded that depth of cut is the most influencing parameter followed by feed rate and cutting velocity.

scholarly journals Effect on Material Removal Rate and Surface Finish in ECM Process When Machining Stainless Steel-316 with Cu Electrode

2019 ◽  
Vol 8 (4) ◽  
pp. 2933-2941
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Process Parameters ◽  
Surface Finish ◽  
Feed Rate ◽  
Electrolyte Concentration ◽  
Removal Rate ◽  
Electrochemical Machining ◽  
Machining Process ◽  
Machining Processes

Electrochemical Machining process is one of the popular non-traditional machining processes which is used to machine materials such as super alloys, Ti-alloys, stainless steel etc. Its working principle is based upon Faraday law of electrolysis. The aim of the present work is to optimize the ECM process parameters with the combination of SS 316 (job material) and Copper electrode (tool material). To explore the effect of ECM process parameters such as electrolyte concentration, voltage and current, feed rate on MRR and surface finish (Ra) of the job, total 27 experiments were conducted as per experimental scheme. The results of these experiments revealed that increase in electrolyte concentration decrease the mrr and surface roughness initially increases then decreases. Further, increase in current increases mrr initially and then decreases, surface roughness also increases. It is also noticed that increase in Feed rate mrr decreases and then increases, also surface roughness decreases then increases. Through RSM analysis it is found that the optimum conditions for maximum MRR, and minimum Surface roughness (Ra) is electrolyte concentration 150gm/lit, Voltage 13.5 V & feed 0.8 mm/min. The findings are discussed in the light of previous researches and subsequently conclusions are drawn.

Effect of Process Parameters on MRR and Surface Roughness in ECM of EN 31 Tool Steel Using WPCA

2017 ◽  
Vol 4 (2) ◽  
pp. 45-63 ◽  
Author(s):  
Milan Kumar Das ◽  
Tapan Kumar Barman ◽  
Kaushik Kumar ◽  
Prasanta Sahoo
Keyword(s):  
Surface Roughness ◽  
Tool Steel ◽  
Process Parameters ◽  
Electrolyte Concentration ◽  
Removal Rate ◽  
Electrochemical Machining ◽  
Machining Parameters ◽  
Electrode Gap ◽  
En 31 ◽  
Taguchi Orthogonal Design

Weighted principal component analysis is used to predict the optimal machining parameters for EN 31 tool steel in electrochemical machining for minimum surface roughness and maximum material removal rate based on L27 Taguchi orthogonal design. For this, multi-response performance index is calculated to derive an equivalent single objective function and then Taguchi method is used to optimize the process parameters. The separable influence of individual machining parameters and the interaction between these parameters are also investigated by using analysis of variance (ANOVA). Results show that the main significant factor on MRR and surface roughness is electrolyte concentration. The effects of process parameters viz. electrolyte concentration, voltage, feed rate and inter-electrode gap on MRR and surface roughness are also investigated using 3D surface and contour plots. Finally, the surface morphology is studied with the help of scanning electron microscopy (SEM) images.

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

Optimization of Process Parameters in Plasma Arc Cutting Applying Genetic Algorithm and Fuzzy Logic

2018 ◽  
pp. 123-139
Author(s):  
Nehal Dash ◽  
Apurba Kumar Roy ◽  
Sanghamitra Debta ◽  
Kaushik Kumar
Keyword(s):  
Genetic Algorithm ◽  
Surface Roughness ◽  
Fuzzy Logic ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Plasma Arc ◽  
Plasma Arc Cutting ◽  
Optimization Of Process Parameters

Plasma Arc Cutting (PAC) process is a widely used machining process in several fabrication, construction and repair work applications. Considering gas pressure, arc current and torch height as the inputs and among all possible outputs, in the present work Material Removal Rate and Surface Roughness would be considered as factors that determines the quality, machining time and machining cost. In order to reduce the number of experiments Design of Experiments (DOE) would be carried out. In later stages applications of Genetic Algorithm (GA) and Fuzzy Logic would be used for Optimization of process parameters in Plasma Arc Cutting (PAC). The output obtained would be minimized and maximized for Surface Roughness and Material Removal Rate respectively using Genetic Algorithm (GA) and Fuzzy Logic.

Multi-Response Optimization of Electrochemical Machining of Al-Si/B4C Composites Using RSM

2013 ◽  
Vol 3 (3) ◽  
pp. 42-56 ◽  
Author(s):  
Sadineni Rama Rao ◽  
G. Padmanabhan
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Feed Rate ◽  
Electrolyte Concentration ◽  
Electrochemical Machining ◽  
Casting Process ◽  
Stir Casting ◽  
Machining Parameters ◽  
Electron Microscopic ◽  
Sem Images

The present work reports the electrochemical machining (ECM) of the aluminium-silicon alloy/boron carbide (Al-Si /B4C) composites, fabricated by stir casting process with different weight % of B4C particles. The influence of four machining parameters including applied voltage, electrode feed rate, electrolyte concentration and percentage of reinforcement on the responses surface roughness (SR) and radial over cut (ROC) were investigated. The process parameters are optimized based on the response surface methodology (RSM) and the optimum values for minimizing surface roughness and radial over cut are voltage 15.25 V, feed rate 1.0 mm/min, electrolyte concentration 13.56g/lit and percentage of reinforcement 7.36 wt%. The quality of the machined surfaces is studied by using scanning electron microscopic (SEM) images. The surface plots are generated to study the effect of process parameters and their interaction on the surface roughness and radial over cut, for the machined Al-Si/B4C composites.

Multi Response Optimization of Process Parameters of Abrasive Water Jet Machining for Stainless Steel AISI 304 Using VIKOR Approach Coupled with Signal to Noise Ratio Methodology

2015 ◽  
Vol 14 (02) ◽  
pp. 107-121 ◽  
Author(s):  
Vedansh Chaturvedi ◽  
Diksha Singh
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Material Removal Rate ◽  
Material Removal ◽  
Removal Rate ◽  
Aisi 304 ◽  
Steel Aisi ◽  
Machining Characteristics ◽  
Stainless Steel Aisi ◽  
Experimental Runs

As the population of the world is continuously increasing, demand of the mechanical manufactured products is also increasing. Machining is the most important process in any mechanical manufacturing, and in machining two factors, i.e. material removal rate (MRR) and surface roughness (SR) are the most important responses. If the MRR is high, the product will get desired shape in minimum time so the production rate will be high, but we could not scarify with the surface finishing also because in close tolerance limit parts like in automobile industry, if the surface is rough exact fit cannot take place. The term optimization is intensively related to the field of quality engineering. Abrasive water jet machining is an important unconventional machining, in order to obtain better response, i.e. material removal rate and surface roughness. Various process parameters of AWJM need to be observed and selected to improve machining characteristics. Better machining characteristics can be achieved by optimizing various process parameters of AWJM. This study considers four process control parameters such as transverse speed, standoff distance, abrasive flow rate and water pressure. The response is taken to be material removal rate and surface roughness. The work piece for stainless steel AISI 304 material of size 15 cm × 10 cm × 2 cm is selected for experiments. Sixteen experimental runs (two trials for each experimental runs) were carried out for calculating MRR and SR and average value of these two trials have been taken for analysis. MRR is normalized according to higher-is-better and SR is normalized according to lower is better. The experiment data analysis is done and VIKOR index is found. Finally, the analysis of VIKOR index using S/N ratio is done and found the most significant factor for AWJM and predicted optimal parameters setting for higher material removal rate and lower surface roughness. Verification of the improvement in quality characteristics has been made through confirmation test with the predicted optimal parameters setting. It is found that the determined optimum combination of AWJM parameters gives the lowest VIKOR INDEX which shows the successful implementation of VIKOR Method coupled with S/N ratio in AWJM.

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