Maximum Material Removal Rate Research Articles

Multi-Objective Optimization of PMEDM Process of 90CrSi Alloy Steel for Minimum Electrode Wear Rate and Maximum Material Removal Rate with Silicon Carbide Powder

This study aims to minimize electrode wear (EW) and maximize material removal rate (MRR) in powder mixed electrical discharge machining (PMEDM) process of 9CrSi alloy steel with silicon carbide powder. To achieve these objectives, Taguchi method and Grey Relational Analysis (GRA) are applied to optimize one two-level and four three-level PMEDM process parameters, including Ton, Toff, CP, IP and SV in eighteen experiments based on an orthogonal array L18 (21 and 43). Results have provided a set of optimal PMEDM process parameters in which Ton has the strongest effect on SW and MRR while that of CP is insignificant. The obtained minimum EW and maximum MRR have been verified and proven by a PMEDM experiment using optimal process parameters. The proposed method can be further applied to optimize other PMEDM process parameters for different objectives.

Study on different types of electric discharge Machining Methods: A review

EDM has played a vital role in machining industry but with advancement of technology, alternative advanced methods of machining has been evolved. This technology have been proven more efficient than traditional EDM in terms of machining performance characteristics such as higher material removal rate (MRR) and improved surface characteristics of the machined surface with high tolerance quality products. Electric discharge machining is an advanced method of machining very hard conductive materials with complex geometries which are very difficult to machine by any other conventional method. In this present study a combination of conductive metallic powder (zinc) along with pressurized mist for powder mixed near dry electric discharge machining (PMND-EDM) has been utilized as a dielectric mixture in order to achieve higher material removal rate (MRR). The maximum material removal rate was found to be more than conventional EDM.

Machining feasibility and sustainability study on end milling process of Monel alloy

Minimizing the resource consumption and reducing the manufacturing system's environmental impact has been increased in today's manufacturing trend. The proposed study deals with the sustainability of the machining process of Monel (K-400) in the End milling process. Spindle speed feed and depth of cut are process parameters of the milling process and are set as four levels. Surface roughness, MRR, Tool wear, tool life, and energy consumption were considered as sustainability factors. The result revealed that factors such as Lower surface roughness (1.26 µm), Minimum tool wear (0.2 mm), Maximum tool life (8,79,200 min), Maximum material removal rate (32 mm3/s) increased the sustainability of the end milling process of Monel material.

Optimization of Milling Process by Taguchi-PSI Method

060A4 steel (Chinese standard) is a steel with good machinability, which is very popularly used in mechanical engineering. Therefore, the study of solutions for improvement of quality and productivity when machining this steel type has great technical and economic significance. In this study, the multi-objective optimization process has been performed when milling this steel type on a vertical milling machine. The cutting tool is a face milling cutter made of High Speed Steel (HSS) material. The effect of spindle speed, feed rate, and cutting depth on surface roughness has been found. The combination of the Taguchi method and PSI method has been applied to determine the optimal value of three input parameters to simultaneously ensure the two criteria of the minimum surface roughness and the maximum Material Removal Rate (MRR). The works which will be done by the authors of this article in the near future has also been presented in the last part of this study.

Multi objective optimization of rough pocket milling strategies during machining of lead-free brass alloys using Desirability function and Genetic algorithms-based analysis

The performance of a machining process is determined by various parameters specially the direction of tool movements during cutting. In this paper, various cutting responses such as machining time (tm), cutting forces (Fr), metal removal rate (MRR), and dimensional accuracy (DA) during the rough pocket milling of the lead-free brass alloys with various toolpath strategies has been studied. The optimization is performed by using the desirability function (DF) and Genetic algorithms-based analysis (GA). The optimization has yielded to minimum production time, cutting forces, dimensional accuracy error and maximum material removal rate considering technological and industrial constrains.

Multi performance optimisation of wire-cut EDM process parameters of Incoloy 800 alloy using grey relational analysis

Abstract Wire Electric Discharge Machining is one of the non-conventional machining processes, used to machine alloy materials with high mechanical strength and also cuts intricate shapes. This paper presents a study in multi performance optimization of machining parameters of Wire electric discharge machining of Incoloy 800 alloy using Taguchi method and grey relational analysis. Incoloy 800 alloy is a nickel, iron and chromium based alloy. The variation in process parameters affects the response variables such as Surface roughness and Material removal rate. Taguchi L27 Orthogonal array is used to perform the experiments. Experiments are performed by considering machining parameters such as Pulse on time, Pulse off time, Gap Voltage, Peak current. By varying the machining parameters accordingly the optimum values are obtained for performance characteristics. The optimization is performed in order to obtain best Surface Roughness and maximum Material Removal Rate. By Grey relational analysis the optimal combination of machining parameters is obtained. ANOVA reveals the most influential factor for Surface roughness and MRR. The results show that the machining parameter Pulse ON time has the greater impact on the performance characteristics.

Combination of taguchi method and moora method for multi-objective optimization of SCM400 steel milling process

Abstract. In this article, a study on multi-objective optimization of the milling process is presented. CNC milling machine, cutting tool as TiAlN, experimental material as SCM400 steel and coolant as Caltex Aquatex 3180 oil have been used in the experiment. The objective of this study is to simultaneously ensure the minimum surface roughness and the maximum material removal rate (MRR). Taguchi method has been applied to design an experimental matrix with five input parameters, including coolant flow, coolant pressure, cutting velocity, feed rate, and cutting depth. Analysis of experimental results by Pareto chart has determined the effect of input parameters on output parameters. Moora method has been applied to determine the values of input parameters to simultaneously ensure the two criteria as mentioned above. Finally, the direction for further research has also been recommended in this study

Optimization of milling parameters in jute fiber reinforced epoxy composite using GRA

The use of synthetic polymers in composite materials found a great impact on the environment. So nowadays manufacturer concentrates on the development of green composites because of their properties such as biodegradability, strength to weight ratio, durability, less cost, etc. Jute is one of the cheapest and strongest natural fibers. Machining of composite materials results in delamination, fiber pullout, matrix cracking, etc. To overcome this problem, appropriate selection of cutting parameters is necessary. The purpose of this study is to optimize performance responses such as surface roughness (Ra & Rz), material removal rate (MRR) and tool wear rate (TWR). The input variables are feed rate, spindle speed and depth of cut. The Taguchi L27 orthogonal array is chosen and grey relational analysis is used to decrease surfaceroughness and Tool Wear Rate (TWR) with Maximum Material Removal Rate (MRR).

Optimization of Dressing Parameters for Minimum Surface Roughness and Maximum Material Removal Rate in Internal Grinding of SKD11 Tool Steel

This paper introduces a study on multi-objective optimization of dressing parameters in internal grinding of SKD 11 tool steel using Grey based Taguchi method. The L27 orthogonal array of the Taguchi method was selected to design the experiments. The input parameters of the dressing process are the depth of fine, the time of fine dressing, the depth of coarse dressing, the time of coarse dressing, non-feeding dressing, and dressing feed rate. The output factors are surface roughness (SR) and material removal rate (MRR). A grey relation grade was determined by using the signal-to-noise ratio. The ANOVA was applied to find out the effect of input factors on the grey relation grade. In conclusion, the fine dressing times is the parameter that has the strongest impact on multiple performance characteristics, followed by the coarse dressing times. Also, the optimum dressing parameters to get minimum SR and maximum MRR is the depth of coarse dressing of 0.03mm, the time of coarse dressing of 2 times, the depth of fine dressing of 0.01 mm, the time of fine dressing of 2 times, non-feeding dressing of 2 times, and dressing feed rate of 1.2mm/min.

Optimization Study on Turning Process by Using Taguchi-copras Method

In this article, a multi-objective optimization of turning process study is presented. Two output parameters of the turning process taken into consideration are surface roughness and Material Removal Rate (MRR). Taguchi method has been applied to design the experimental matrix with four input parameters including nose radius, cutting velocity, feed rate and cutting depth. Copras method has been employed to solve the multi-objective optimization problem. Finally, the optimal values of the input parameters have been determined to simultaneously ensure the two criteria of the minimum surface roughness and the maximum MRR.

Investigations and optimization of rotary tool micro-USM process for fabrication of microchannels

This article reports on investigations on process parameters of rotary tool micro-USM during machining of glass. Abrasive size, tool rotation speed, concentration, and power rating were the selected process parameters investigated in this study. The material removal rate (MRR) was chosen as response characteristics. Optimal parametric combination for maximum MRR was also determined by adopting Taguchi’s methodology in this investigation. The results obtained from analysis of variance revealed that tool rotation speed followed by abrasive size and concentration with a percentage contribution of 46.37%, 31.78% and 5.55% respectively were the significant parameters for MRR. The MRR increased with increasing the tool rotation speed and concentration and decreasing the abrasive mesh size. The maximum MRR was obtained at lower level of abrasive mesh size and higher level of rotation speed and concentration of abrasive slurry.

A combination method for multi-criteria decision making problem in turning process

This paper presents a multi-criteria decision making (MCDM) for a turning process. An experimental process was performed according to the sequence of a matrix using the Taguchi method with nine experiments. The parameters including workpiece speed, feed rate, depth of cut, and nose radius were selected as the input variables. At each experiment, three cutting force components that were measured in the three directions X, Y, and Z, were Fx, Fy, and Fz, respectively. The value of Material Removal Rate (MRR) was also calculated at each experiment. The main purpose of this study is determination of an experiment in total performed experiments simultaneously ensuring the minimum Fx, Fy, and Fz and the maximum MRR. The Entropy method was applied to determine the weights for parameters Fx, Fx, Fx, and MRR. Eight MCDM methods were applied for multi-criteria decision making, this has not been performed in any studies. The implementation steps of each method were also presented in this paper. Seven ones of these eight methods determined the best experiment in total nine performed experiments. A new multi-criteria decision-making method as well as orientation for the further works were also proposed in this study.

Combining Taguchi method and DEAR method for multi-objective optimization of grinding process

In this paper, a study on multi-objective optimization of the cylindrical grinding process is presented. The experimental material used in this study is X12M steel. The two output parameters of the grinding process considered in this study are surface roughness and material removal rate (MRR). The cutting mode parameters including cutting speed, feed rate, and cutting depth have been selected as input parameters of the experimental process. Experimental matrix by Taguchi method has been used to design a matrix with 27 experiments. Analysis of experimental results by Pareto chart has determined the effect of input parameters on output parameters. The Data Envelopment Analysis-based Ranking (DEAR) method has been applied to determine the values of input parameters to simultaneously ensure the two criteria of minimum surface roughness and maximum MRR. Finally, the development direction for further studies has also been recommended in this study.

Effect of discharge gap on EDM using desirability function analysis

Electro Discharge Machining (EDM) has been developed as a precise machining process to produce accurate features in electrically conducting materials. A high-speed self- adjusting EDM approach is needed with feedback system to remove the debris in the machining process. In the current study, the micro feature machining in the copper plate is investigated in order to get the optimum gap distance in EDM process. With the change in the gap distance and depth of the hole drilled, the linear actuator automatically adjusts the gap for the electrode. So it is crucial to find out the optimum input parameters that contribute for maximum result. For the experimental analysis Taguchi L27 orthogonal array technique is used. With the help of Desirability Function Analysis (DFA) and Analysis of Variance (ANOVA), the optimum parameters values had found out for maximum Material Removal Rate (MRR) with minimum Tool Wear Rate (TWR) and Radial Over Cut (ROC). The parameters values for optimum result are found to be voltage (39.95 V), Frequency (4.67 KHz), Duty Factor (67.47%) and Gap distance (0.5 mm). The ANOVA revealed that, the parameters have almost equal contribution for getting the optimum values that affects the surface finish and material removal rate. The results from the experiment reveals that the desirable result will be get at 0.5 mm gap distance and this would be taken as the optimum gap distance for the automatic feeding mechanism. In addition, low voltage and current would benefit for the EDM process working in micro level and for the removal of the recast layer.

Study on Effectiveness of HSS and HSS-Cobalt Twisted Drills on Surface Roughness

This paper focuses on the optimization of drilling parameters by using Taguchi method for achieving maximum Material Removal Rate (MRR) and minimum Surface Roughness (Ra). The experiments were carried out on material EN8, medium carbon steel using HSS and HSS-Cobalt drills. Four cutting parameters such as Drill Type (HSS, HSS-Cobalt), Point Angle (90º, 118º, 135º), feed rate (90, 240, 450 mm/min), speed (900, 1200, 1500 RPM) were considered as the control factors. The signal-to-Noise (S/N) Ratios and the analysis of variance (ANOVA) have been employed to determine the effectiveness of parameters on the responses. The results revealed that feed rate was the most significant factor for material removal rate and Drill–type was for surface roughness. The models predicted for the responses were found to be best fit and accurate for the future predictions.

On investigating the soda-lime shot blasting of AZ31 alloy: Effects on surface roughness, material removal rate, corrosion resistance, and bioactivity

Abstract In the present study, a novel method of surface finish improvement is proposed using shot blasting of soda lime (SBSL) beads on the Mg-AZ31 alloy. The effect of the soda blasting process parameters, such as blast pressure, stand-off distance, and blast duration, have been studied in-response of material removal rate (MRR) and surface roughness (SR) and corresponding statistical models have been obtained. The multi-objective optimization has also been performed to obtain parameters for maximum MRR and minimum SR. The corrosion behavior of the treated specimens has been performed to study their in-vitro biodegradability in simulated body fluid (SBF) for 1, 3, 7, 10, 15, and 21 days. The wettability study of the SBSL treated samples has been investigated using sessile drop methodology. Further, cell adhesion test has also been performed to study the biocompatibility characteristics of the SBSL treated samples using Huh7 liver cell lines. Based on obtained quantitative data as well as scanning electron microscopy analysis of treated samples, the SBSL treatment of the AZ31 alloy has been found highly useful in producing biocompatibility surfaces along with desirable morphological features.

Investigating the influence of electrical discharge machining process parameter on fatigue strength during machining of titanium grade-2

High strength, excellent corrosion resistance, and low density are the main properties that make titanium attractive for a variety of applications such as the production of airframes, engine components, steam turbine blades, superconductors, missiles, etc. Machining of titanium alloy by conventional machines causes the problems such as chipping and premature tool failure, deflections of the work-piece, increases the temperature at the tool-work piece interface, etc. Hence under such circumstances, nonconventional Die sink Electrical Discharge Machining (EDM) process can be alternative to overcome such problems. The primary aim of this paper is to investigate the effects of process parameters (factors) on material removal rate (MRR) in the EDM process. The process parameters considered for this investigation are current (C), voltage (V), pulse on time (Ton), and pulse off time (Toff) for EDM machining of titanium (grade-2) alloy with copper as an electrode material. The experiments were designed with the Taguchi method, orthogonal array L9. The maximum MRR obtained was 0.073 mm3/min with the voltage of 40 V, current of 8A, pulse on at 60 µs, and pulse off at 9 µs respectively. While the secondary aim of this research is to investigate the effect of process parameters on fatigue strength of titanium (grade-2) alloy. During fatigue test it was observed, fatigue strength decreases with an increase in current and pulse on time.

Parametric studies on SiC-abrasive jet assisted machining of alumina ceramics

Abstract Present study investigates machinability of K-90 alumina ceramic for Fluidized-Bed Abrasive Jet Machining (FB-AJM) in presence of Silicon Carbide (SiC) abrasives. Four input process factors such as pressure, standoff distance, abrasive temperature, and abrasive mesh size are considered associated with L16 orthogonal array design of experiment. Effects of AJM parameters on output responses viz. Material Removal Rate (MRR), Overcut (OC), and circularity error (deviation) are studied. In addition, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) integrated with Taguchi method is applied to determine the most appropriate setting of AJM parameters in purview of maximum MRR, minimal OC, and minimal circularity error.

Experimental modeling and optimization of magnetic field assisted electrical discharge turning: Applicable for wind power turbine elements

Electrical discharge turning (EDT) process is finding its application in machining of rotary elements that is usually difficult to be machined with conventional processes. In order to perform the process more efficient, in the present work a new modification through assistance of magnetic field with EDT process was adopted. Here, an experimental study was made to investigate effect of magnetic field assisted EDT parameters i.e. magnetic flux density, current, pulse time and spindle speed on performance measures i.e. material removal rate (MRR), overcut (OC), surface roughness (Ra), recast layer thickness (RLT) and hardness (H). Number of 30 experiments were carried out using face-centered central composite design taken into account three levels for each parameter. Empirical models were developed using regression analysis with 95% confidence level to correlate relationship between inputs and outputs. Analysis of variances was also carried out to check the adequacy of developed model and to identify which factor has greatest influence on performance measures. Finally, desirability approach function was utilized for multi-objective optimization of process taking into account maximum MRR and hardness as well minimum overcut, surface roughness and recast layer thickness. The research findings indicated that discharge current and pulse on time are most influential parameter on MRR and H; while, magnetic flux density has greatest effect on OC, Ra and RLT. Effectiveness of magnetic field assistance showed that this parameter results in 56% and 38% increase in MRR and H, respectively; also, it results in 31%, 43% and 47% reduction of overcut, surface roughness and recast layer thickness, respectively. Finally, the optimization results demonstrated that magnetic flux density of 0.4 T is an optimum value, however, upon the condition of roughing or finishing, the remaining parameter setting should can be changed.

Modeling and prediction of die sinking EDM process parameters for A6061/6%B4C metal matrix composite material

Abstract The aluminium metal matrix composites (AMMCs) are used in aerospace applications due to their excellent mechanical properties. The die-sinking electrical discharge machining (EDM) is suitable for machining complex shapes and sizes in conductive metals. The present research focused on the machining of aluminium 6061 with 6% wt boron carbide metal matrix composite (A6061/6%B4C MMC). The input process parameters are designed based on the central composite design (CSD) and optimized using response surface methodology. The maximum material removal rate (MRR), minimum surface roughness (SR), and minimum electrode wear rate (EWR) are obtained from the analysis of variance (ANOVA) and are analyzed using the response surface method (RSM). The percentage improvement in MRR, SR, and EWR were calculated. The combination of parameters for the optimized results was obtained and the results show improvement in predicted results. An increase of 0.167% in MRR and 9.31%, 2.61% reduction in EWR and SR respectively were obtained in the predicted results.