Experimental investigation of surface topography in photochemical machining of Inconel 718

Surface topography is one of the important aspects of micro-components manufacturing. Photochemical machining (PCM) is the most commonly used method in the low-cost micro-manufacturing process. The present investigation focused on the study of the effect of process parameters on the surface topography in PCM of Inconel 718 of two different grain sizes using ferric chloride (FeCl₃). For this work, the input parameters considered are concentration, time and temperature of the etchant. The temperature of the etchant was found to be the most dominant parameter in the PCM of Inconel 718. Moreover, in this study, the effect of grain size of samples on surface roughness was considered. The average increase in surface roughness is 1.227 times due to variation in grain size from 59?µm to 42?µm.     

WEDM of Mg/CRT/BN composites: Effect of materials and machining parameters

The current work presents a detailed exploration on real-time wire electric discharge machining (WEDM) experiments and grey relational analysis (GRA)–based multi-criteria optimization of material and machining characteristics for lowered surface roughness (R_a) and improvised material removal rate (MRR) of the newly developed magnesium/boron nitride/cathode ray tube (Mg/BN/CRT) hybrid metal matrix composites (MMCs). The composites were fabricated through powder metallurgy (PM) route by reinforcing silica-rich E-waste CRT panel glass powder crushed for different particle sizes (10, 30, and 50?µm) at various weight percentages (5%, 10%, and 15%) and with 2% boron nitride (BN). Taguchi-based orthogonal array procedure was utilized to formulate the experimental plan for WEDM considering reinforcement level and size, pulse on time (P_on), pulse off time (P_off), and wire feed (W_f) as the input process parameters. ANOVA results reveal that P_on and wt% of reinforcement has more effect on R_a and MRR than any other considered parameters. The developed mathematical model for R_a and MRR predicted values similar to that of experimental results. Multi-criteria optimization was done through GRA technique and the so recommended optimum parameter set furnishes higher MRR (22.34?mm³/min) and reduced R_a (2.87?µm).     

Controlling the material removal and roughness of Inconel 718 in laser machining

Nickel alloys including Inconel 718 are considered as challenging materials for machining. Laser beam machining could be a promising choice to deal with such materials for simple to complex machining features. The machining accuracy is mainly dependent on the rate of material removal per laser scan. Because of the involvement of many laser parameters and complexity of the machining mechanism it is not always simple to achieve machining with desired accuracy. Actual machining depth extremely varies from very low to aggressively high values with reference to the designed depth. Thus, a research is needed to be carried out to control the process parameters to get actual material removal rate (MRR_act) equals to the theoretical material removal rate (MRR_th) with minimum surface roughness (SR) of the machined surfaces. In this study, five important laser parameters have been used to investigate their effects on MRR and SR. Statistical analysis are performed to identify the significant parameters with their strength of effects. Mathematical models have been developed and validated to predict the machining responses. Optimal set of laser parameters have also been proposed and confirmed to achieve the actual MRR close to the designed MRR (MRR_% = 100.1%) with minimum surface roughness (R_a = 2.67 µm).     

WEDM process parameter optimization of FSPed copper-BN composites

A systematic view on evaluating the machining characteristics of Wire Cut Electrical Discharge Machining (WEDM) employing Taguchi Method and Grey Relational Analysis based multiobjective optimization is provided in this research article. The outcome of various WEDM processing parameters including pulse discharge on time (Pulse_ON), pulse discharge off time (Pulse_OFF), wire feed rate (Wire_FR) along with the material characteristics of varying Boron Nitride (BN) volume fractions while machining a friction stir processed (FSPed) copper-BN surface composite was investigated. The output responses considered in this research include Material Removal Rate (MRR) and Surface roughness (R_a) that was obtained from the L27 orthogonal array based on the above said input factors. ANOVA was performed, and Pulse_ON and BN volume fraction were found most significant for MRR, while Pulse_ON and Pulse_OFF influence the most in attaining minimal R_a values. Based on the obtained experimental values for MRR and R_a, a mathematical model was developed based on the control factors and was proved to be precise in predicting the output response. An optimal combination of input control factors was finalized through grey relational analysis, and the same proved to achieve the utmost MRR (20.19?mm³/min) and nominal R_a(3.01?µs) values.     

Optimizing Single Point Diamond Turning for Mono-Crystalline Germanium Using Grey Relational Analysis

In this paper the results of an experimental study conducted for precision machining of mono-crystalline germanium with single point diamond turning (SPDT) have been reported. The input parameters include the top rake angle, tool overhang, depth of cut, tool feed rate, and rotational speed of the workpiece. The flat profile is generated on a disk of mono-crystalline germanium possessing three performance characteristics: surface roughness (R_a), profile error (P_t), and waviness error (W_a). The process parameters are optimized to obtain the best surface finish with minimum profile and waviness errors by using the Taguchi method. The grey relational analysis is employed for carrying out multiresponse optimization of performance parameters. The best value of surface finish obtained after multiresponse optimization is 10.7 nm having a profile error and a waviness error of 0.202 µm and 0.046 µm, respectively.     

Improving the machining performance characteristics of the µEDM drilling process by the online cryogenic cooling approach

Productivity and surface quality would significantly affect the performance of the micro electrical discharge machining process (µEDM). Thus, the machining performance would be enhanced by improving the material removal rate (MRR) and surface quality. In this investigation, cryogenic LN₂ cooling was introduced to the conventional µEDM setup for developing an innovative process of cryogenically cooled µEDM process (CµEDM). The favorable outcomes of this process were estimated by selecting discharge current (I_p) and pulse on duration (T_on) for determining the effects of the machining performance including MRR and surface integrity. Surface quality was also analyzed by microstructural analysis and a scanning electron microscope (SEM) for evaluating the effects of the cryogenically cooled µEDM process. The experimental result shows 54–62% improvement in MRR and 22–36% improvement in average roughness values. Hence, it is suggested that cryogenically cooled µEDM facilitates improvement in productivity and surface quality.     

Microstructural Analysis and Multiresponse Optimization During ECM of Inconel 825 Using Hybrid Approach

In the current study, electrochemical machining of Inconel 825, a Ni-based super alloy, was carried out using tungsten as a tool electrode material and NaCl as electrolyte. The present investigation attaches particular emphasis on explaining the mechanism of material removal of Ni-based super alloys in the ECM process. The influence of various ECM parameters such as voltage (V), concentration (C), and tool feed (F) has been investigated on the evolution of the surface morphology of Inconel 825 after ECM. Different performance measures in ECM such as material removal rate (MRR), surface roughness (SR), and radial overcut (ROC) have been measured. Grey relational analysis that uses grey relational grade as performance index has been adopted to simultaneously optimize multiple performance characteristics and determine optimal combination of ECM parameters. Moreover, principal component analysis is utilized to determine the weighting values corresponding to various output responses so that their relative importance can be adequately expressed. Optimal condition was found to be V = 16 V, C = 45 g/L, and F = 0.3 mm/min. Confirmation test was further performed to authenticate the approach applied for determining the optimal conditions that resulted in MRR of 20.867 mm³/min, SR of 0.156 µm, and ROC of 0.0697 mm, which were superior to those corresponding to all previous experimental runs.     

Effect of deep cryotreated tungsten carbide electrode and SiC powder on EDM performance of AISI 304

Abstract

Powder mixed electric discharge machining (PMEDM) is a further advancement of conventional EDM process in which electrically conductive powder is suspended in the dielectric fluid to enhance the material removal rate (MRR) along with the surface quality. Cryotreatment is introduced in this process for improving the cutting tool properties as well as tool life. In this investigation, EDM is performed for the machining of AISI 304 stainless steel using cryotreated double tempered tungsten carbide electrode when SiC powder is suspended in the kerosene dielectric. The influence of process parameters viz. pulse on time, peak current, duty cycle, gap voltage and powder concentration on tool wear rate (TWR), surface roughness (R_a), and MRR has been studied. Metallographic analysis was carried out for the machined surfaces. By the addition of powder concentration and cryotreated double tempered electrode, significant improvement in the machining efficiency has been found out. When cryotreated electrode used MRR, TWR and R_a decreased by 12%, 24% and 13.3%, respectively and when SiC powder used MRR increased by 23.2%, TWR and R_a decreased by about 25% and 14.2%, respectively.     

Surface integrity and removal mechanism in grinding sapphire wafers with novel vitrified bond diamond plates

In order to improve machining efficiency of sapphire wafer machining using the conventional loose abrasive process, fixed-abrasive diamond plates are investigated in this study for sapphire wafer grinding. Four vitrified bond diamond plates of different grain sizes (40?µm, 20?µm, 7?µm, and 2.5?µm) are developed and evaluated for grinding performance including surface roughness, surface topography, surface and subsurface damage, and material removal rate (MRR) of sapphire wafers. The material removal mechanisms, wafer surface finish, and quality of the diamond plates are also compared and discussed. The experiment results demonstrate that the surface material is removed in brittle mode when sapphire wafers are ground by the diamond plates with a grain size of 40?µm and 20?µm, and in ductile mode when that are ground by the diamond plates of grain sizes of 7?µm and 2.5?µm. The highest MRR value of 145.7?µm/min is acquired with the diamond plate with an abrasive size of 40?µm and the lowest surface roughness values of 3.5?nm in Ra is achieved with the 2.5?µm size.     

Optimization of EDM Parameters on Machining Si3N4–TiN Composite for Improving Circularity,Cylindricity, and Perpendicularity

The dominance of the spark eroding process in complex ceramic components has promoted a significant growth analysis in the ceramic composites domain in modern manufacturing industries. The latest developments in ceramic components are concentrated on both the enhancement of the mechanical properties and the machinability of complex 3D parts while using spark EDM. The current (I), pulse on time (T_on), pulse off time (T_off), and dielectric flushing pressure (DP) are considered sparking parameters for the machining of a Si₃N₄–TiN ceramic composite. These composites find their application in high-temperature environments, viz. metal forming, extrusion dies, turbine blade, and non-ferrous molten metal handling components. Taguchi's orthogonal array (OA), L₁₈, has been used to design the experiments. The optimal machining inputs are determined by the grey relational grade (GRG), which is attained from the grey relation analysis (GRA) for various response characteristics, such as the material removal rate (MRR), tool wear rate (TWR), circularity (CIR), cylindricity (CYL), and perpendicularity (PER). The significant parameters are identified via an analysis of variance (ANOVA). Finally, the optimized process parameters resulting in a higher MRR, lower TWR, lower form tolerance, and decreased orientation tolerance are verified through a confirmation test demonstrating that sparking process responses can be effectively improved.     

Optimization of Process Parameters to Improve Form and Orientation Tolerances in EDM of MoSi2-SiC Composites

In this research, an investigation and experimental work were carried out on electric discharge machining (EDM) of intermetallic base MoSi₂-SiC ceramic composite with copper electrode. It is extremely difficult to machine MoSi₂-SiC composite using conventional machining techniques. However, it can be easily machined by executing spark EDM parameters to induce the correct optimum result. These composites find their application in high-temperature environments, viz. fuel turbo pump rotors, inlet nozzles, combustion chambers, injectors, nozzle throats, and nozzle extensions. The sparking parameters, namely current (I), pulse on time (T_on), pulse off time (T_off), spark gap (SG), and dielectric pressure (DP), were investigated by L₁₈ orthogonal array. The optimal process parameters were determined by the grey relational grade (GRG) obtained through the grey relational analysis (GRA) for multiple performance characteristics, viz. material removal rate (MRR), electrode wear rate (EWR), circularity (CIR), cylindricity (CYL), and perpendicularity (PER). The significant process parameters were obtained by analysis of variance (ANOVA) based on GRG, which showed current, pulse on time, and DP. The results were finally established using a confirmatory experiment, which showed the spark eroding process could effectively be improved.     

Constrained multi-objective optimization of EDM process parameters using kriging model and particle swarm algorithm

This paper investigates the highly nonlinear relationship between process parameters and machining responses, including material removal rate (MRR), surface roughness (SR), and electrode wear rate (EWR) of electric discharge machining (EDM) using Kriging model. Subsequently, an emerging multi-objective optimization algorithm called particle swarm is used to determine the best machining conditions that not only maximize the machining speed but also minimize the EWR with a constraint of the SR. The experiment was carried out with P20 steel on a CNC EDM machine using copper electrode. The research result shows that the MRR increases sharply when increasing the discharge current just like other researches pointed out. However, the relationship between EWR and current is complicated. EWR appears the minimum value when the current is around 30?A. The speed of change of MRR per unit of EWR is the highest when the SR is around 14.5?µm. The combination of Kriging regression model and particle swarm optimization is considered as an intelligent process modeling and optimization of EDM machining. The proper selection of process parameters helps the EDM operator to reduce the machining time and cost.     

Optimization of Dry Machining Parameters for High-Purity Graphite in End-Milling Process

The machining factors affecting the tool wear and surface finish produced in the end milling process are generally the cutting speed, the feed rate, the depth of cut, etc. This paper describes a study that identifies the influence of the machining parameters on the groove width and the surface roughness average for the end-milling of high-purity graphite under dry machining conditions. The experiments are based on an orthogonal arrays and grey relational analysis method is then applied to determine an optimal machining parameter setting. The dimensional accuracy of the groove width and the surface roughness average are selected as the quality targets. In this study, the feed rate is the most significant controlled factors for the machining process according to the weighted sum grade of the Δ and the R _a .     

Multi-attribute decision-making of cryogenically cooled micro-EDM drilling process parameters using TOPSIS method

The geometrical characteristics of the micro-holes along with the performance measures are matter of critical concern in micro-electrical discharge machining (μEDM) process. This paper presents the multi-attribute decision-making of cryogenically cooled micro-EDM (CμEDM) drilling process. Current (I_p), pulse on duration (T_on), pulse off duration (T_off), and gap voltage (V_g) were the input process parameters preferred to optimize the multiple responses of geometrical characterization including taper angle (TA), overcut (OC), circularity at the entry and exit (C_ent and C_exit), and performance measures including material removal rate (MRR), tool wear rate (TWR), and average roughness (R_a). The Taguchi-based L₂₇ orthogonal array (OA) is used to carry out the experimental runs, and technique for order of preference by similarity ideal solution (TOPSIS) approach is used for the identification of optimal parameters on AISI 304 stainless steel. The optimized result achieved from this approach suggests improved TA, OC, C_ent, C_exit, MRR, and lower TWR, surface roughness (SR) with the combinations of CμEDM drilling process such as I_p of 15 A, T_on of 10?µs, T_off of 30?µs, and V_g of 30?V. Analysis of variance (ANOVA) was conducted to identify the major influencing parameter.     

Effect of process parameters and optimization for photochemical machining of brass and german silver

This article focuses on parametric optimization for photochemical machining (PCM) of brass and german silver. The aim of the study is to analyze the effect of control parameters on response measures, that is, surface roughness, material removal rate, and edge deviation and optimization of parameters considering different weight percentage for each performance measure. The control parameters have been selected as etchant concentration, etching temperature, and etching time. Using full factorial method of design of experiments, PCM has been carried out using ferric chloride as etchant. Surface roughness and edge deviation should be less, while material removal rate is desired high. For satisfying this multi-objective condition, overall evaluation criteria (OEC) have been formulated by assigning different and equal weight percentage to response measures. The optimized condition for particular OEC is obtained, and analysis of variance (ANOVA) has been performed for observing effect of control parameters on response measures. Surface topography study has been performed using scanning electron microscopy, and material composition analysis has been carried out using energy dispersive spectroscopy. The surface roughness is observed lower for brass, while the edge deviation is found lesser for german silver. The material removal rate is observed higher for brass compared to german silver.     

Performance evaluation of Al2O3 nano powder mixed dielectric for electric discharge machining of Inconel 825

Electrical discharge machining (EDM) process is popular for machining conductive and difficult-to-cut materials, but low material removal rate (MRR) and poor surface quality are major limitations of the process. These limitations can be overcome by adding the suitable powder in the dielectric. The powder particles influence electric field intensity during the EDM process which in turn improve its performance. The size (micro to nano) and properties of the mixed powder also influence the machining efficiency. In this regard, the objective of the present work is to study the performance of EDM process for machining Inconel 825 alloy by mixing Al₂O₃ nanopowder in deionized water. The experimental investigation revealed that maximum MRR of 47?mg/min and minimum SR of 1.487?µm, which are 44 and 51% higher in comparison to conventional EDM process, respectively, can be achieved by setting optimal combinations of process parameters. To analyze these observed process behavior, pulse-train data of the spark gap were acquired. The discharge waveform identifies the less arcing phenomenon in the modified EDM process compared to conventional EDM. Further, surface-topography of the machined surface was critically examined by capturing field emission scanning electron microscopy and atomic force microscopy images.     

Surface and porous recast layer analysis in µ-EDM of MWCNT-Al2O3 composites

Machining of ceramic materials has been a major challenge owing to high hardness and brittleness. The reinforcement of a conducting filler allows permissible machining in electrical discharge machining (EDM) process. The current effort analyses the impact of multi-walled carbon nanotubes (MWCNT) of concentrations of 2.5 and 5 vol. %, as conducting filler towards machinability of alumina composites in µ-EDM process. The influence of tool materials and its rotation are closely analyzed. A successful machining process is observed in both the two composites, with a higher material removal rate (MRR) in 5 vol. % MWCNTs. When the tool starts to rotate at 750 rpm, an increment of around 60–65% is observed in MRR for both the two composites. Similarly, the surface roughness (R_a) decreases by a factor of 20?25%. The brass tool is observed to yield better machining capabilities due to the frequent initiation of sparks. A highly porous machined surface is observed in both the two composites. This scenario depicts the spalling effect as more dominant than melting-evaporation effect. The extent of porous recast layer on the drilled edges is found to reduce with increasing the speed of tool rotation.     

Influence of materials and machining parameters on WEDM of Al/AlCoCrFeNiMo0.5 MMC

The current study intends to optimize the wire electric discharge machining (WEDM) parameters while machining the newer AlCoCrFeNiMo_0.5 high entropy alloy (HEA) particles-reinforced aluminum composites. AlCoCrFeNiMo_0.5 HEA particles produced through arc melting technique are reinforced here for different weight % (0%, 3%, 6%, 9%, 12%, and 15%) along with pure aluminum by the way of powder metallurgy. WEDM studies were conducted by varying the appropriate parameters, namely, pulse ON time, pulse OFF time, and wire feed. Based on the selected parameters, through Taguchi method L18 orthogonal array is designed; the optimal parameter combination for better surface finish, material removal rate (MRR), and reduced kerf width (KW) is identified. For better understanding, through ANOVA, also the effect of each input variables over these adopted response variables was analyzed. The yielded results reveal that addition of AlCoCrFeNiMo_0.5 HEA as reinforcement has considerable effect over the response variablessuch that MRR and KW reduces; surface roughness increases with increase in HEA %. ANOVA results confirm that pulse ON time has higher effect over the response variables than any other parameters involved for the study. Multi-objective optimization done through Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methodology answers that MRR and surface finish have improved, whereas KW gets reduced noticeably.     

Experimental investigation and optimization during the fabrication of arrayed structures using reverse EDM

In recent years, reverse electric discharge machining (R-EDM) has been evolved as a method for the fabrication of arrayed structures for surface texturing which find applications in fabrication of fins and component assembly. In this study, the feasibility of R-EDM process in the fabrication of arrayed features of ?3?mm and height 2?mm on mild steel has been investigated utilizing response surface methodology (RSM)-based experimentation. Influence of control variables such as peak current (I_p), pulse-on time (T_on), and flushing pressure (F_p) on some of the vital geometric characteristics like taper and cylindricity error along with material removal rate (MRR), surface roughness (SR), microhardness, and surface morphology of pillared structure has been investigated. Analysis of variance (ANOVA) results show that I_p has a significant influence followed by T_on on MRR. I_p has a significant contribution toward SR, taper, and cylindricity error. High microhardness was found in heat-affected zone (HAZ). The optimal combination of parameter obtained using principal component analysis (PCA)-based grey relational analysis (GRA) is determined to be I_p?=?10 A, T_on?=?100 μs, and F_p?=?0.3?kg/cm², which was further ascertained using confirmatory test.     

Investigation of multiple process parameters in abrasive water jet machining of tiles

This paper discusses the optimization of an abrasive water jet machining process with multiple characteristics, using the Taguchi orthogonal array and grey relational analysis (GRA). The machining process variables, such as mesh size, nozzle diameter, abrasive flow rate, water pressure, stand-off distance, and feed rate, were optimized with respect to multiple performance characteristics, namely, the surface roughness and the kerf angle. Experiments were performed using an L₁₈ orthogonal array, and the optimum machining process variables were determined, using GRA. Analysis of variance was used to identify the most significant factor in the machining performance. A confirmatory test was performed to verify the improvement of the performance characteristics. The microstructure of the machined surfaces was also examined by scanning electron microscopy and atomic force microscopy. The results showed that the surface roughness and kerf angle were minimized under optimal machining conditions.