Metal Removal Rate Research Articles

Investigations on wire spark discharge and MRR using neural network modeling

TiNiCo alloy is a smart material that can recover its original shape when the temperature is increased or decreased. Due to its unique class of properties, such kinds of materials are used in various industrial applications such as robotics, biomedical and aerospace industries. Conventional machining of these alloys is quite difficult hence non-conventional machining process are found to be more suitable for machining of these alloys. Wire sparks discharge machining process was chosen for the machining of Ti 50 Ni 49 Co 1 and Ti 50 Ni 45 Co 5 alloys. Pulse on the duration and servo voltage was selected as machining process parameters with their five levels and metal removal rate considered as machining response. The error analysis has been carried out through a comparison between experimental values and predicted values. An artificial neural network (ANN) was used as the prediction technique. Predicted values were found to be close to experimental values. 6% error for Ti 50 Ni 49 Co 1 and 5% error have been found in Ti 50 Ni 45 Co 5 alloy.

Multi-response optimization of electrochemical micromachining on masked SS304

This paper investigates on electrochemical micromachining of woven fabric masked stainless steel SS304 using 0.5 mm copper tool electrode with sodium nitrate (NaNO3) Electrolyte. Investigation is carried out to express the performance measures of micro hole such as metal removal rate (MRR), taper angle (TA) and surface roughness (SR). The experimental plan is based on taguchi L16 orthogonal array. Various input process parameters such as voltage, duty ratio, rotational speed, feed rate of tool and electrolyte concentration are varied at four levels. Significant contributions by input process parameters for each output responses such as metal removal rate, taper angle and surface roughness are analysed using contour plots. It is evident that significant contribution to metal removal rate mainly depends on rotational Speed and feed rate of tool. Similarly, duty ratio and feed rate of tool are the significant contributors for both taper angle and surface roughness. Multi response optimization are done for the three output responses using VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to identify the significant process parameter. Performance score of VIKOR and TOPSIS proved that rotational speed of tool, feed rate and duty ratio are important parameters contributing significantly for precision of microfeatures. Both the multi response optimisation methods mutually concluded the best performance is achieved at voltage 21 V, duty ratio 80%, rotational speed of tool 600 rpm, feed rate of tool 0.8 μm s−1 and electrolyte concentration 0.2 M. The confirmation test showed an improvement of performance grade by approximately 0.245.

Metal Removal Rate & Surface Morphological Analysis of Electrical Discharge Machined Co-Cr Alloy

Electrical discharge machining (EDM) confirmed its importance in the machining of hard and complex geometrical material which are difficult to machine or modified by traditional machining technique. The EDM process parameters – namely, pulse-on time, pulse-off time, current, voltage and dielectric medium – significantly influence the machining performance, such as surface traits, roughness and surface films. Therefore, in this study, the influence of EDM performance parameters on the metal removal rate (MRR) and surface roughness (SR) was examined. Experimentation was conducted according to the Taguchi L18 orthogonal array. Further, the analysis of variance (ANOVA) was employed for analyzing the S/N ratio results of the MRR and SR of various samples. The results revealed that cobalt (Co)–chromium (Cr) alloy substrates machined with a tungsten (W)–copper (Cu) electrode at the higher current setting (16 A, P on = 150 μs, P off = 150 μs) in EDM oil exhibited appropriate MRR and surface roughness value. Moreover, the EDM surfaces also exhibited suitable biocompatibility and excellent osseointegration.

Study on tool steel machining with ZNC EDM by RSM, GREY and NSGA

An effort over the process of increasing the Material Removal Rate (MRR) and minimizing the Tool Wear Rate (TWR) is made while machining of Tool steel as work material with copper as the tool electrode with Z-Axis Numerical Control - Electrical Discharge Machine (ZNC-EDM) by maintaining positive polarity. Basically Tool steel by its intrinsic property falls under the hard to cut material type. Moreover where ever precision is the very need, we move from conventional to non conventional machining. Analysis is made by making use of the CCD of Response Surface Methodology. Vin-Spark Voltage, Iin- Spark Current and Ton- Pulse on Time is considered out of many influencing factor for the experimentation purpose as input parameters based on literature support. The most predominant output factor which comes to play in machining process is Metal Removal Rate (MRR), Tool Wear Rate (TWR). In order to expel from the stochastic phenomenon the MRR and TWR factors are concentrated to the extreme level of operating factors domain. A quadratic equation among the output and input factor is acquired with the help of Response Surface Methodology (RSM). For the considered range of domain of experimental values, the equation developed reveals that at 95% confidence level, the peak current inputs makes a major role in deciding the MRR, whereas for the TWR the main impact is produced by input voltage and then spark-on time. For the expected optimal output, the corresponding input setting lies around Voltage level of 1 V, Current value of 15 Amps and On-Time of 60 μsec. By keeping the maximum the best for Material Removal Rate, desirability is 0.367 and by keeping the minimum the best a desirability of 0.693 is obtained for TWR. The experimentally observed set of values well coincides along with the optimization with the help of GREY and Pareto Analysis of NSGA. Fig.7 & Fig. 8 depicts an image for the above mentioned parameter settings and its factor measurement shows

Demetallization of Heavy Oils of High Metal Content through Pyrolysis under Supercritical Water Environment

Through pyrolysis under a supercritical water (SCW) environment, the demetallization of Tsingtao vacuum residuum (VR) and Tahe atmospheric residuum (AR) with a total vanadium and nickel content above 300 ppm was studied. By introducing SCW, pyrolysis of heavy oil can be carried out in an emulsion structure in which heavy fractions rich in metals are concentrated in oil droplets. A metal removal rate higher than 90 % could be obtained in 2 h, which is faster than the pyrolysis under the nitrogen environment. Although two heavy oils have similar apparent properties, Tsingtao VR is characterized by the metal enrichment in the heaviest asphaltenes and the higher condensation activity of asphaltenes. Because of the preferential condensation of heavy fractions rich in metals, the liquid product yield of Tsingtao VR could be 15 wt% higher than that of Tahe AR at the metal removal rate of 70 to 90%.

Microchannel fabrication and metallurgical characterization on titanium by nanosecond fiber laser micromilling

ABSTRACTLaser micromilling technique is used to manufacture microchannel on metals and nonmetals. Microfeatures ≤100 µm are still challenging for fabrication by common methods. Nanosecond fiber laser micromachining has become more popular owing to its prospective implementation in laser micromilling. Microchannel application relies on its geometric dimension, profile, and surface quality. In this study, an attempt was made to explore the impact of process parameters scanning times, scanning velocity, pulse repetition rate, and assist gas pressure on top kerf width, taper, surface roughness, and metal removal rate in laser micromilling experimentally. Microchannel width varied between 45.5 and 70.9 µm. A regression model has been developed for each response. ANOVA (analysis of variance) has been carried out to remove insignificant parameters. Thermal stress analyzed by surface cracks inside microchannel by Scanning Electrone Microscopy (SEM) images. Higher PRR, lower no. of scans, higher scanning speed and high air pressure found suitable for lesser surface cracks. Redeposition observed at slower scanning velocity and minimum scanning times. Oxidation zone from boundary of channel varies between 37 and 58 µm. Oxide formed on Ti surface which increases oxygen content toward center of channel from 51.08 to 76.22% compared to outside surroundings.

Development Of Regression Model For Al6061+ Sic Tool And Optimization Of Process Parameters On Electro Discharge Machining

Proper selection of manufacturing conditions is one of the most important aspects to take into consideration in the majority of manufacturing processes and, particularly, in processes related to Electrical Discharge Machining (EDM). These are the conditions that determine important characteristics such as material removal rate, Electrode Wear. In the present work experiments are conducted on EDM using Al6061+SiC (with 3%,6%,9% composition of SiC in Al 6061 Alloy ),Copper and Brass materials as electrodes and EN8 steel as work material. Discharge current (IP), pulse on time (TON), pulse off time (TOFF) are selected as inout process parameters, Metal Removal Rate (MR), Tool Wear Rate (TWR) as response. Taguchi design of experiment is used to find the influence of process parameters on response and a mathematical model is developed. Percentage contribution of each factor is determined.

Optimization for Machining Parameters in Turning of AISI 52100 Steel for Manufacturing Services-Genetic Algorithm Method

Because of its high wear and corrosion resistance, AISI 52100 steel is mostly used in automobile and aerospace applications. It is a high strength chromium steel with hardness usually greater than 45HRC.The prime objective of this study is to identify the influential machining parameters affecting metal removal rate (MRR) and cutting forces. During turning of AISI52100 steels, a central composite design (CCD) through response surface methodology (RSM) was employed to generate a model for predicting the MRR and cutting forces. The significant parameters and their contribution percentage were identified using analysis of variance (ANOVA). Furthermore, the affect of machining parameters in the MRR and cutting forces were examined and validated for identifying the accuracy of the predicted model. To conclude, the optimum values of MRR and cutting force along with the optimum parameters were ascertained using genetic algorithm (GA).

Removal of Zn and Cd from Overlying Water by Mangrove Sediments: Testing the Effects of Sediment Resuspension/Redeposition Events

Coastal sediment redeposition after resuspension events may change the sediment capacity to sequester pollutants after the formation of new sediment-water interfaces. To test this hypothesis, radiotracer experiments were performed to evaluate zinc (65Zn) and cadmium (109Cd) removal kinetics by redeposited mangrove sediments. After 24-h experiments, average inventories within redeposited sediments were close to those from control sediments (~ 20% lower in redeposited sediments), while average decreases of 41% (109Cd) and 27% (65Zn) in the half-removal times (t1/2) from overlying water were promoted by redeposited sediments in comparison with control sediments. High variability in metal removal rates, however, implied in no statistically significant differences between t1/2 values, suggesting a low influence of sediment redeposition on the metal removal capacity of mangrove sediments. More limited depth diffusion of metals was observed within redeposited sediments, always within the uppermost centimeter. Possible benefits to water quality by a slightly faster metal diffusion into redeposited sediments may be less effective due to this trend since the metal retention very close to the sediment top can facilitate new remobilization to the overlying water.

EDM ASSISTED BY MAGNETIC FIELD FOR ARMOURED STEEL

The present paper presents a study on the performance of electrical discharge machining (EDM) assisted by magnetic field for armoured steel (HV500). Response surface methodology (RSM) has been utilized to model, analyze and determine the optimal parameters setting in the EDM process assisted by magnetic field. The process performance criteria such as; material removal rate (MRR), tool wear rate (TWR), were evaluated. Peak current, magnetic flux density, duty factor, and dielectric fluid pressure have been considered the main factors affecting EDM assisted by magnetic field performance. RSM was employed to develop the experimental models. The EDM process assisted by magnetic field process has proved its adequacy to machine armoured steel alloy under acceptable metal removal rate and minimum tool wear rate. The metal removal rate generally increases with the increase of the magnetic flux density and peak current value. The effect of duty factor was limited and dielectric fluid pressure has a moderate effect. Further, the minimum tool wear rate has been obtained at the parametric combination of higher magnetic flux density and higher duty factor when machined by EDM assisted by magnetic field with copper electrodes. It has also been clarified that the effect of magnetic flux density was limited on metal removal rate with graphite electrodes. It has also been found that the minimum tool wear rate was obtained at the parametric combination of higher magnetic flux density, higher peak current and lower duty factor, when machined by EDM assisted by magnetic field, with graphite electrodes.

Investigations on electrochemical machining (ECM) of Al7075 material using copper electrode for improving geometrical tolerance

This research work focuses on electrochemical machining performance evaluation of Al7075 material ECM has become the most important and high precision technique in the manufacturing sector, since many intricate 3D profiles can be machined using a copper electrode. ECM process widely applied in aerospace industries using of multiple hole drilling, turbine blades within close limits and drilling jet engine turbine blades, etc. The objective of this experiment is found the maximum Material Removal Rate (MRR), reducing the machining time, good hardness and surface finish. The machining parameter considered were current (12 V), duty cycle (75%), and electrolyte concentration (32%). The performance measures such as metal removal rate (MRR), the machining time (min), hardness, form and orientation tolerance were examined. Main effect plot, interaction plot and contour plot analysis were used to optimize the process parameters for ECM processes. As a result, metal removal rate is maximized by increasing the electrolyte concentration (36 g/l), duty cycle (95%) and machining voltage (16 v). Metal hardness is improved by decreasing the machining voltage (12 V), duty cycle (75%) and increasing the electrolyte concentration (36 g/l). Minimum circularity is achieved at machining voltage, electrolyte concentration, and duty cycle are reduced. Minimum cylindricity is obtained while increasing the electrolyte concentration and decreasing the machining voltage. Minimum perpendicularity is achieved to increase of voltage and decrease of electrolyte concentration.

Optimization of cylindrical grinding process parameters using meta-heuristic algorithms

Owing to the complexity of grinding process, it has been very difficult to predict the optimal machining conditionswhich have been resulted in smooth surface finish, accurate geometric measurements and higher production rate. In thiswork, empirical models for surface roughness, roundness error and metal removal rate have been developed based onregression analysis. These models have been associated the grinding process parameters (work speed, feed rate and depth ofcut) with machining performances (metal removal rate, roundness error and surface roughness). Using these models, theoptimization has been carried out based on simulated annealing (SA) and genetic algorithm (GA) which have been the twopopular meta-heuristic optimization techniques. Finally, the results of the proposed techniques l have compared andexperimentally validated.

Wire electrical discharge machining (WEDM) analysis into MRR and SR on copper alloy

Wire electric discharge machining (WEDM) is a widely accepted non-traditional material removal process for manufacturing of components with intricate shapes. Wire electric discharge machining is assessed on basic of metal removal rate (MRR) and surface roughness (Ra). WEDM is extensively used in machining of conductive materials where precision is of major factor. The process output is affected by large number of input variables. Experimentation has been done using Taguchi's L9 orthogonal array. Each experiment was conducted under different combinations of pulse on time, pulse off time and peak current. The optimum machining parameter combination was obtained by using the analysis of signal to noise (S/N) ratio, analysis of means and analysis of variance (ANOVA). Further, the level of importance of the machining parameters on copper alloys was determined by using ANOVA. The study shows that the Taguchi's method is suitable to solve the stated problem with minimum number of trails.

Design and evaluation of a feed handle for a bench drilling machine.

Despite extensive industrial use, no major modifications to the bench drilling machine, with respect to ease of operation, have been undertaken. The objectives of the study were to design a new feed handle (NFH) to perform the drilling task on a bench drilling machine and evaluate the existing (EFH) and new feed handles on the basis of performance measures like drilling productivity in terms of metal removal rate (MRR) and worker performance in terms of perceived discomfort score (PDS). Participants performed the drilling task on a steel block for three different working durations at two drilling speeds. ANOVA analysis carried out for the MRR data showed that drilling speed had a statistically significant effect on the task performance of the operator for both handles. However, the task duration was found to be statistically significant only for the EFH. The ANOVA results obtained on the PDS data showed that the task duration and drilling speed had a statistically significant effect on the task performance of the operator for both systems. The MRR obtained was higher when the drilling task was carried out using NFH. An appreciable decrease in PDS was also observed using the proposed system.

ANFIS based predictive model for wire edm responses involving material removal rate and surface roughness of Nitinol alloy

Nickel titanium (Nitinol) alloys are functional materials which find extensive applications in aerospace, automotive and medical applications. Nitinol alloy is very hard to machine using conventional process due to its ductility, temperature sensitivity, severe work hardening and minimum thermal conductivity, resulting in massive tool wear and very poor surface finish. Wire electro discharge machining (WEDM) is the most versatile among all unconventional machining processes for machining difficult to cut materials. This work reports the relationship between WEDM machining parameters: pulse on time (Ton), pulse off time (Toff), peak current (Ipeak) gap voltage (V), and output parameters: metal removal rate (MRR) and surface roughness (SR) analyzed using artificial neuro fuzzy inference system (ANFIS) predicted model.Results attained from ANFIS model were distinguished from experimental values and it was found that anticipated values of the output attributes are in good agreement with actual values. Correlation Coefficient (R) of both MRR and surface roughness was almost 0.9945 which is nearly equal to one, and the coefficient of determination (R2) and avg error(%) erected for surface roughness were 0.9891 and 2.04 respectively whereas for material removal rate, coefficient of determination (R2) and avg error (%) were found to be 0.9738 and 1.70% respectively. Experimental data was employed for prediction modeling of MRR and SR with an accuracy of 98.3% and 98.75% respectively.

Eksperimentalno istraživanje kriogeno potpomognute obrade čelika za kalupe abrazivnim vodenim mlazom

This paper reports the investigation on parametric optimization of the abrasive aqua jet (AAJ) and cryogenic assisted abrasive aqua jet (CAAAJ) processes for cutting AISI D2 steel using multi objective TOPSIS approach. The input parameters considered were aqua jet pressure, abrasive grit size and jet impingement angle. In this study, depth of penetration, metal removal rate, kerf taper ratio and average roughness were taken as the performance characteristics. The results showed that the CAAAJ process exhibited better performance characteristics than the AAJ process. The AAJ machining process with an inclined jet impact angle influences the output responses, which is evident from an optimal selection of parameters. Besides, the influencing process variables were determined by using the analysis of variance. The overall machining performance of the AAJ and CAAAJ processes were improved by using the optimum process variables through the TOPSIS method.

Optimization of Surface Topography of Electro- Discharge Machined Super Alloy Inconel 825: Using TOPSIS Integrated with Taguchi Philosophy

The aim of this research work is to find the optimum combination of input process parameters such as Peak Current(I P ), Open Voltage(V g ), Pulse-On-Time(T on ) & Duty Factor(τ) for machining of Inconel 825 on EDM using copper electrode. The experiment has been designed on 4 levels 4 factors i.e. L 16 orthogonal array. The output response parameters studied were Metal Removal Rate (MRR), Electrode Wear Rate (EWR) and Surface Roughness (R a ). During our study we have used Taguchi method to identify the proper control factors to obtain the optimum results of the process.

An overview of conventional and non-conventional techniques for machining of titanium alloys

Machining is one of the major contributors to the high cost of titanium-based components. This is as a result of severe tool wear and high volume of waste generated from the workpiece. Research efforts seeking to reduce the cost of titanium alloys have explored the possibility of either eliminating machining as a processing step or optimising parameters for machining titanium alloys. Since the former is still at the infant stage, this article provides a review on the common machining techniques that were used for processing titanium-based components. These techniques are classified into two major categories based on the type of contact between the titanium workpiece and the tool. The two categories were dubbed conventional and non-conventional machining techniques. Most of the parameters that are associated with these techniques and their corresponding machinability indicators were presented. The common machinability indicators that are covered in this review include surface roughness, cutting forces, tool wear rate, chip formation and material removal rate. However, surface roughness, tool wear rate and metal removal rate were emphasised. The critical or optimum combination of parameters for achieving improved machinability was also highlighted. Some recommendations on future research directions are made.

A comparative study for biomachining of aluminium alloy 4004 using Acidithiobacillus ferrooxidans and Aspergillus niger

Biomachining is one of the fastest growing technologies in the coming future. Besides, there are many advantages of biomachining such as low energy consumption, environmental friendly and no use of coolant; some of the shortcomings reported by early researchers is less metal removal rate. In this work, a comparative study on biomachining of aluminium alloy 4004 has been done using Acidithiobacillus ferrooxidans and Aspergillus niger. Taguchi design of experiments (DOE) L16 approach is used to analyse the influence of process parameters (shaking rate, pH, time and concentration) to enhance the performance of biomachining. Thus, based on the analysis of results, it has been concluded that Acidithiobacillus ferrooxidans provides better results in comparison to Aspergillus niger. Additionally, optimal values of process parameters have been suitably compared in case of both bacteria and fungus for improved material removal rate, surface finish and hardness.

Investigation on machining characteristics of T6-Al7075 during EDM with Cu tool in steady and rotary mode

In this paper, aluminium alloy T6-Al7075 is machined using Electrical-discharge machining (EDM). For machining the material, L9 orthogonal array with three different levels of process parameters has been used. To study the machining performances three process variables, such as spark gap, pulse-off time and peak current have been selected. Metal removal rate (MRR), tool wear rate (TWR), roughness parameters Ra and Rq are considered as responses where tool is in steady and rotary mode. The multi-objective optimization for the responses have been analyzed using TOPSIS method. Furthermore, the investigation for surface texture has been carried out in both the machining condition. MRR increases in the case of tool in rotary mode than the steady mode.