Maximum Material Removal Rate Research Articles

Parametric analysis of electrical discharge machining on AA6061 with a WC–Cu composite electrode

The AA6061 aluminium alloy surface characteristics presented in this study were obtained after it was machined using die sinking electro discharge machining (EDM) with a composite electrode developed through powder metallurgy. Machining was performed using negative polarity. In order to obtain optimum material removal rate (MRR) and surface roughness (SR), the research has been carried out, and EDM parameters like voltage, current and pulse on time were optimized using the response surface methodology that integrates the central composite design. The parameter interaction effects on EDM machined surface characteristics were studied with the aid of ANOVA. It was determined from model that the regression for MRR and SR were 98.6% and 98.3% respectively, means empirical model is considered sufficient. It was observed that increased MRR and SR were observed in the condition of increased current, but MRR and SR decreased at increased voltage and pulse on time. This could be due to strengthened ionization temperature that increased MRR with acceptable SR. The microstructure of the machine was assessed using microscopic evaluation. The increased current contributed to the formation of a recast layer and debris which hinders the machining process and reduces MRR. The experimental results show that the maximum MRR of 0.087 mg/min and minimum SR of 1.893 µm were achieved. Additionally, the use of WC–Cu composite electrodes led to an increase in hardness from 65 HV to 78 HV in the machined region. It is concluded that WC–Cu composite electrodes typically result in higher hardness, improved MRR and better SR for the AA6061 alloy compared to conventional Cu electrodes.

Optimizing Cylindrical Grinding Proficiency and Surface Finish for EN24 Steel Alloy with the Use of Taguchi Analysis and Artificial Neural Network

Grinding is a material removal procedure used at the end of manufacturing to obtain high dimensional precision and a desirable surface polish. External cylindrical grinding is a type of grinding procedure that used to grind cylindrical things such as engine shafts, connecting rods, spindles, and axles. This study examines how control settings affect response parameters using EN24 alloy steel on a cylindrical grinding machine. Response parameters are material removal rate (MRR) and surface roughness (Ra), whereas control parameters are workpiece speed (v), feed rate (f), and depth of cut (d). Taguchi DOE is employed with L16 orthogonal array to optimize control parameter levels, followed by cylindrical grinding tests.An artificial neural network (ANN) model was created to validate and predict cylindrical grinding reaction parameters. To train the network, experimental data was used, and ANN predictions were compared to real data. Data collection has also completed.In the purposed work minimum Ra is 0.52 µm and maximum MRR is 0.6588 g/sec found and results indicate that feed rate and workpiece speed are the most dominating parameters of cylindrical grinding. The experimental results can be employed by various manufacturing and industrial firms and they can select suitable combinations of input parameters for desired Ra and MRR

Optimizing Cutting Parameters for Effective Turning of EN-31 Steel by Utilizing Vegetable-Based Cutting Fluids as a Coolant

<div>The primary objective of this article is to study the improvement of machining efficiency of EN-31 steel by optimizing turning parameters using newly developed cutting fluids with different proportions of aloe vera gel and coconut oil, utilizing the Taguchi technique. Furthermore, performance metrics including material removal rate (MRR), surface roughness, and tool wear rate (TWR) were assessed. Analysis of variance (ANOVA) suggested that as cutting speed and feed increase, the MRR is positively influenced, but likewise tool wear is intensified. The surface roughness exhibited a positive correlation with cutting speed, and a negative correlation with increasing both cutting speed and feed. It was found that the maximum MRR value was attained at a cutting speed of 275 m/min, a feed rate of 1.00 mm/rev, and a cutting fluid composition of 30% aloe vera and 70% coconut oil. For the best surface smoothness, it is advisable to adjust the cutting speed to 350 m/min and the feed rate to 0.075 mm/rev. A cutting speed of 275 m/min and a feed rate of 1.00 mm/rev led to a lower TWR. The results suggest that the combined use of coconut oil and aloe vera as cutting fluids improves the turning quality of EN-31 steel, particularly when employing a combination of 30% aloe vera and 70% coconut oil. As a possible solution for performance problems in achieving desired results during the turning of EN-31 steels, these recommendations may be used in industries to enhance turning performance.</div>

Optimization of Material Removal Rate and Wear Rate in EDM Machining of Inconel 625 Using a Novel Nano Al-Ni Composite Electrode: A Response Surface Methodology Approach

The electric discharge machine is a novel machining technique. When the tool and the work item do not communicate. Components composed of difficult-to-machine hard materials. In the current experimental inquiry, the process factors that influence the machining concert process and its effectiveness are explored. The response table for each set of machining limitations is used in conjunction with the response surface methodology in the research to determine the appropriate levels of machining factors. The work's machining input parameters are optimized for maximum material removal rate (MRR) and reduce the electrode wear rate (EWR) when electro-discharge machining Inconel 625 using the tool Nano Al-Ni composite electrode. Another analysis of variance is to identify the factors causing the different answers mentioned above. EDAX was also used to investigate the material composition of the workpiece. Machined workpiece surfaces were evaluated using scanning electron microscopy to assess surface accuracy and microstructural characteristics (SEM). The following conclusions may be drawn from this work. The MRR parameter that is most affected is pulse off time. As pulse-off time lengthens, MRR increases. According to the response graph, the greatest MRR value that can be attained under the ideal parameters of Ip = 8A, T-ON = 50μs, and T-OFF= 100μs is 0.0115 g/min. The magnitudes of MRR range from 0.0091 to 0.044 g/min. Impact of T ON and T OFF: Higher EWR is 0.0022 g/min is seen in runs with T ON = 70 μs and T OFF = 100 μs.

Electrical discharge machining of super alloy incoloy 925: a study based on box behnken design and response surface methodology

Incoloy 925, a Nikel-based superalloy, exhibits low machinability with conventional machining techniques due to its inhomogeneous properties. Therefore, there is a need to establish a non-conventional method to efficiently machine this alloy. This work is a novel attempt to present the electric discharge machining (EDM) of the superalloy Incoloy 925 and subsequent multi-response optimization. The model for the analysis was designed using the Box Behnken Design (BBD) technique, and the Response Surface Methodology (RSM) was used for the optimization of the results. The machining was performed using a cylindrical copper tool of 11 mm diameter. The effect of pulse-on time (Ton), current, and pulse-off time (Toff) on the material removal rate (MRR), tool wear rate (TWR), and surface roughness (SR) was investigated. The results from variance analysis confirmed the significance of all the three input factors. The investigation revealed that the maximum MRR (99.2154 mm3/min) was obtained at a pulse-on time of 90 μs, pulse-off time of 5 μs, and current of 30 A. The minimum TWR (0.8866 mm3/min) were achieved at Ton = 60 μs, Toff = 8 μs and current = 10 A. The microscopic images of the machined surfaces revealed very few micro-voids and globules and no cracks, resulting in a fine surface finish of 1.2436 μm, achieved through optimal discharge energy transfer and copper electrodes. The optimal values MRR, TWR, and SR according to composite desirability function are 99.1524 mm3/min, 1.0915 mm3/min, and 1.3925 μm. The experimental results were accurately predicted using RSM and an artificial neural network (ANN), with the ANN showing a predicted correlation coefficient (R) close to 1 indicating high accuracy of the model.

Optimizing the Die-Sink EDM Machinability of AISI 316L Using Ti-6Al-4V-SiCp Electrodes: A Computational Approach

Die-sink electric discharge machining (EDM) is essential for shaping complex geometries in hard-to-machine materials. This study aimed to optimize key input parameters, such as the discharge current, gap voltage, pulse-on time, and pulse-off time, to enhance the EDM performance by maximizing the material removal rate while minimizing the surface roughness, residual stress, microhardness, and recast layer thickness. AISI 316L stainless steel was chosen due to its industrial relevance and machining challenges, while a Ti-6Al-4V-SiCp composite electrode was selected for its thermal resistance and low wear. Using Taguchi’s L27 orthogonal array, this study minimized the trial numbers, with analysis of the variance-quantifying parameter contributions. The results showed a maximum material removal rate of 0.405 g/min and minimal values for the surface roughness (1.95 µm), residual stress (1063.74 MPa), microhardness (244.8 Hv), and recast layer thickness (0.47 µm). A second-order model, developed through a response surface methodology, and a feed-forward artificial neural network enhanced the prediction accuracy. Multi-response optimization using desirability function analysis yielded an optimal set of conditions: discharge current of 5.78 amperes, gap voltage of 90 volts, pulse-on time of 100 microseconds, and pulse-off time of 15 microseconds. This setup achieved a material removal rate of 0.13 g/min, with reduced surface roughness (2.46 µm), residual stress (1518.46 MPa), microhardness (259.01 Hv), and recast layer thickness (0.87 µm). Scanning electron microscopy further analyzed the surface morphology and recast layer characteristics, providing insights into the material behavior under EDM. These findings enhance the understanding and optimization of the EDM processes for challenging materials, offering valuable guidance for future research and industrial use.

Chemical-mechanical synergetic effect of single crystal SiC polishing using Fe3O4@MIL-100(Fe) magnetic photo-Fenton catalyst

Achieving an atomically smooth surface on single-crystal silicon carbide (SiC) with a high material removal rate (MRR) is challenging. Traditional chemical mechanical polishing (CMP) often uses aggressive slurries that are inefficient and environmentally hazardous. To address these challenges, we synthesized a novel core-shell structure Fe3O4@MIL-100(Fe) magnetic catalyst and utilized it as a non-homogeneous photo-Fenton catalyst in friction wear tests on SiC wafers within a simulated CMP environment. The catalyst was thoroughly characterized using X-ray diffractometry (XRD), scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS). Additionally, we explored the effects of various components, pH levels, H2O2 concentrations, catalyst concentrations, and light intensities on the friction wear of SiC wafers. The results indicate that, under visible light conditions, Fe3O4@MIL-100(Fe) exhibits a strong Fenton catalytic effect, achieving a maximum material removal rate of 61.076*103μm3/min at a pH of 3, H2O2 concentration of 5 wt%, catalyst concentration of 14 g/L, and light intensity of 500 W. These findings provide valuable theoretical support for visible light assisted catalyzed CMP of SiC.

Machining of Ox-Ox (Al2O3/Al2O3) ceramics matrix composites by ultrafast laser

High-performance Ox-Ox ceramics material composites (CMC) are a strategic building block in the aerospace industry and high-temperature applications. The ceramics material composites are hard to machine due to high hardness, fracture toughness, and heterogeneous structures. Furthermore, it is prone to brittle fracture during the machining process. In this study, we successfully demonstrate ultrafast laser machining technology to machine Ox-Ox CMCs. A picosecond laser has been used to machine slots to understand the impact of laser process parameters on the material removal mechanism by performing deep machining. Different scan rates and a number of over-scans have been employed to understand the material removal mechanism, which is dominated by laser ablation and aided by melting due to the residual surface temperature. The maximum material removal rate of 21.75 mm3/min has been achieved for the scan rate of 300 mm/s. This can be related to the reduction in the ablation threshold and the critical balance between the material removal mechanism by ablation and melting. It was found that, the surface roughness of the cut surface has decreased due to melting and solidification. The cross-sectional examination reveals two distinct surface structures, which are entirely resolidified and thermally eroded regions.

Experimental investigation and parametric optimization of rotary ultrasonic machining of different bio-ceramic materials

Rotary ultrasonic machining (RUM) is a highly promising technique for machining bio-ceramic materials due to its ability to achieve high precision and superior surface quality. This research focuses on an experimental investigation and parametric optimization of RUM for different bio-ceramic materials, intending to optimize multiple machining responses simultaneously. The experimental setup involves utilizing a 3-axis CNC ultrasonic machine to machine three different workpieces with slot cutting. Various machining parameters, such as tool feed rate and tool rotating speed, are studied to determine their impacts. An orthogonal array design based on Taguchi optimization is used to execute the experiments effectively. Material removal rate (MRR) and surface roughness (SR) are monitored and statistically analyzed as a consequence of the responses. ANOVA demonstrates that the tool feed rate has a considerable impact on the output reactions, with material type and tool rotational speed also playing a role. For multiple response optimizations, the Taguchi-Grey method is used to achieve the best trade-off between MRR and Sr The results demonstrate that material type has the most substantial impact on surface roughness, followed by feed rate and spindle speed. In contrast, feed rate has the most significant effect on the material removal rate, followed by the material type and spindle speed. The optimal parameter settings for achieving the desired output parameter are determined. The confirmation experiments validate the effectiveness of the optimized parameters. The feed rate of 5 mm min−1, and spindle speed of 2500 rpm were discovered to be the optimal condition for achieving maximum MRR and minimum Ra. The MRR and surface roughness values were measured as 1.7266 mm3 min−1 and 1.5611 microns respectively.

Ex-vivo parametric study of laser ablation-based drilling of cortical bone.

Frequently orthopedic surgeries require mechanical drilling processes especially for inserted biodegradable screws or removing small bone lesions. However mechanical drilling techniques induce large number of forces as well as have substantially lower material removal rates resulting in prolong healing times. This study focuses on analyzing the impact of quasi-continuous laser drilling on the bone's surface as well as optimizing the drilling conditions to achieve high material removal rates. An ex-vivo study was conducted on the cortical region of desiccated bovine bone. The laser-based drilling on the bovine bine specimens was conducted in an argon atmosphere using a number of laser pulses ranging from 100 to 15,000. The morphology of the resulting laser drilled cavities was characterized using Energy dispersive Spectroscopy (EDS) and the width and depth of the drills were measured using a laser based Profilometer. Data from the profilometer was then used to calculate material removal rates. At last, the material removal rates and laser processing parameters were used to develop a statistical model based on Design of Experiments (DOE) approach to predict the optimal laser drilling parameters. The main outcome of the study based on the laser drilled cavities was that as the number of laser pulses increases, the depth and diameter of the cavities progressively increase. However, the material removal rates revealed a decrease in value at a point between 4000 and 6000 laser pulses. Therefore, based on the sequential sum of square method, a polynomial curve to the 6th power was fit to the experimental data. The predicted equation of the curve had a p-value of 0.0010 indicating statistical significance and predicted the maximum material removal rate to be 32.10 mm3/s with 95%CI [28.3,35.9] which was associated with the optimum number of laser pulses of 4820. Whereas the experimental verification of bone drilling with 4820 laser pulses yielded a material removal rate of 33.37 mm3/s. Therefore, this study found that the carbonized layer formed due to laser processing had a decreased carbon content and helped in increasing the material removal rate. Then using the experimental data, a polymetric equation to the sixth power was developed which predicted the optimized material removal rate to occur at 4820 pulses.

An investigation of machinability in micro-EDM drilling of ZrB2/Fly ash/AA7075 hybrid aluminium metal matrix composite

This work investigates the importance of micro-drilling in Hybrid aluminum metal matrix composites (HAMMCs), particularly for the aerospace and automotive industries. The HAMMCs (AA7075/5% ZrB2/2% fly) ash was fabricated using the ultrasonic assisted stir casting method. Taguchi’s design of experiments is employed to optimize the material removal rate (MRR) and tool wear rate (TWR). Analysis of variance (ANOVA) is then used to determine the significance of the model. The study also utilizes a hybrid artificial neural network-genetic algorithm (ANN-GA) approach to optimize both MRR and TWR. By optimizing machining processes for HAMMCs, manufacturers can achieve high-precision micro holes. The optimal input parameters were found to be a feed rate of 10 μm sec−1, a capacitance of 1 nF, and a voltage of 85 V, achieving the minimum TWR and maximum MRR.

Chemical mechanical polishing of sapphire elucidated by densely discrete phase model and verified using atomic force microscopy

The chemical mechanical polishing (CMP) is extensively applied in sapphire substrate processing. However, the mechanism is unclear because of the challenging in the dynamic characterization. In this paper, effects of the polishing speeds, slurry concentrations, and abrasive sizes on the removal action of granular flow in sapphire CMP are investigated using the discrete particle model (DPM) and densely discrete phase model (DDPM). Contours of the residence time, concentration, and abrasive velocity present that rotation speeds of the wafer and pad (30 and 80 rpm respectively) are beneficial to improving sapphire CMP performance. When the SiO2 slurry concentration is higher than 1 wt%, DDPM is more suitable for the fluid-solid flow in sapphire CMP compared to DPM. As the slurry concentration increases, the growth trend of material removal rate (MRR) slows down because of the reduction of the integral particle erosion ratio (PER). The 100 nm SiO2 abrasive can obtain the maximum MRR (10.90×10−9 nm/s), although its PER is 2 × 10−5 of 5 µm particles’ PER. The in-situ atomic force microscopy experiments prove the MRR function of granular flow owing to the hydro-dynamic contact. In addition, the removal ability will be improved by enhancing the interactive force between the abrasive and sapphire. It provides a novel idea to boost the efficiency of sapphire CMP.

Multi-objective optimization of machining variables for wire-EDM of LM6/fly ash composite materials using grey relational analysis

Abstract With the enhancement in science and technology, necessity of complex shapes in manufacturing industries have become essential for more versatile applications. This leads to the demand for lightweight and durable materials for applications in aerospace, defense, automotive, as well as sports and thermal management. Wire electric discharge machining (WEDM) is an extensively utilized process that is used for the exact and indented shaped components of all materials that are electrically conductive. This technique is suitable in practically all industrial sectors owing to its widespread application. The present investigation explores WEDM for LM6/fly ash composites to optimize different process variables for attaining performance measures in terms of maximum material removal rate (MRR) and minimum surface roughness (SR). Taguchi’s L27 OA design of experiments, grey relational analysis, and analysis of variance (ANOVA) were employed to optimize SR and MRR. It has been noted from ANOVA that reinforcement (R) percentage and pulse on time are the most influential aspects for Grey Relational Grade (GRG) with their contributions of 28.22 and 18.18%, respectively. It is found that the best process variables for achieving the highest MRR and lowest SR simultaneously during the machining of the composite are gap voltage of 30 V, pulse on time of 10 µs, pulse off time of 2 µs, wire feed of 8 m/min, and R of 9%. The predicted GRG is 0.84, and the experimental GRG value is 0.86. The validation experiments at the optimized setting show close agreement between predicted and experimental values. The morphological study by optical microscopy revealed a homogenous distribution of reinforcement in the matrix which enhances the composite’s hardness and decreases the density.

Finite element analysis of wire EDM process parameters on performance characteristics of Al–SiC hybrid composite with micro and nano reinforcements

Aluminum Hybrid Composites (AHC) microchannels find extensive applications in aerospace, refrigeration and air conditioning (RAC), microelectronics, automotive, biomedical, and marine industries due to their improved mechanical properties. The combination of lower density, high hardness, elevated thermal and electrical conductivity, superior elasticity, and heightened oxidizing ability at low temperatures makes machining aluminum hybrid composites challenging through orthogonal methods in an open environment. Therefore, it is imperative to investigate the impact of various machining conditions to determine optimal parameter values for microchannel fabrication in aluminum hybrid composite materials. This study aims to identify the ideal machining parameters for Al–SiC micro-SiC nano hybrid composites using wire electrical discharge machining. Four distinct process parameters (pulse on time, gap voltage, wire tension, and wire feed rate) and two response parameters (material removal rate (MRR) and surface roughness (SR)) were considered for process optimization. Additionally, finite element modeling was conducted for the aforementioned process, and the results were compared with experimental outcomes. Single-variable optimization yielded maximum MRR at 125 tons (μs), 25 SV (volt), 12 WT (kgf), and 2 WFR (m/min), and minimum SR at 125 tons (μs), 10 SV (volt), 12 WT (kgf), and 4 WFR (m/min). Single-variable optimization for simulations resulted in maximum MRR at 125 tons (μs), 40 SV (volt), 4 WT (kgf), and 6 WFR (m/min), and minimum SR at 110 tons (μs), 10 SV (volt), 12 WT (kgf), and 2 WFR (m/min). Precise modeling aids in minimizing unnecessary machining, enabling exploration of a broader range of experimental results, thereby promoting environmentally friendly and sustainable machining practices.

High-efficiency green machining of single crystal 4H–SiC based on tribo-oxidation

High efficiency, high quality and green machining of single crystal silicon carbide (SiC) is an important issue in the third-generation semiconductor industry. In this paper, a novel machining method for single crystal SiC based on tribo-oxidation is proposed. The formula and preparation process of polysaccharide bonded soft abrasive tool were designed. Dry machining of C-face of 4H–SiC substrate was carried out with the prepared environmentally friendly abrasive tool sample. The material removal mechanism of the proposed machining method was preliminarily analyzed, and the material removal rate, surface roughness and subsurface residual stress were studied. The experimental results show that the maximum material removal rate of 4H–SiC can reach 1.03 μm/min with a corresponding average surface roughness of Sa 0.816 nm. The machined surface has no brittle flaw, and subsurface residual compressive stress exists with a maximum value of 58.9 MPa. The material removal mainly attributed to the active oxidation of SiC surface induced by the friction between alumina abrasives and SiC substrate. The proposed machining method has potential application value in thinning of SiC wafers.

Evaluating the optimum abrasive water jet machinability for CARALL composites with various fiber orientations

AbstractCarbon Fiber Reinforced Aluminum Laminated (CARALL) composites are widely used in aircraft structures due to their ability to be produced in different shapes with desired properties and their high impact resistance properties. As with other layered composite materials, processing of CARALL composites by conventional manufacturing methods results in many damage mechanisms such as fiber breakage, deformation in the hole region, stress concentration, resin‐fiber separation and microcracks. One of the modern manufacturing methods, Abrasive Water Jet (AWJ), is a processing method in which the material is removed by abrasion and almost any material can be cut without thermal degradation. There are no experimental studies in the literature on the drilling of CARALL composites by modern manufacturing methods. The aim of this study is to investigate the impact of machining parameters on the output variables (kerf taper angle (K), roundness error (Re) and material removal rate (MRR)) as well as the effect of fiber orientation on the drilling of CARALL composites with different fiber orientations on an AWJ machine. PROMETHEE‐GAIA weighted by Entropy Weighting Method were used to ascertain the optimum levels of control factors. CARALL composites with different fiber orientations were drilled with an 8 mm diameter AWJ with three different water pressures, three different nozzle feed rates. With PROMETHEE‐GAIA multi‐criteria optimization method, the optimum levels of the factors that provide both minimum Re and K values and maximum MRR value were obtained with twill woven material, 1680 mm/min feed rate and 1680 bar water pressure.Highlights CARALL composite materials with two different fiber orientations (twill weave and UD) were used. CARALL composite materials were drilled at different machining parameters. Abrasive water jet was used in drilling experiments. Optimum drilling parameters were determined to achieve minimum roundness error, minimum kerf angle and maximum material removal rate. PROMETHEE‐GAIA was used as a multi‐criteria decision‐making method.

Application of Taguchi Method, ANOVA Analysis, and TOPSIS Technique in Optimization of Process Parameters for Surface Roughness and Material Removal Rate in Electrochemical Machining of Al-SiC MMCs

Objectives: To evaluate the significance of advanced machining techniques, such as EDM, ECM, and USM, in increasing productivity and overcoming challenges associated with outdated Al-SiC MMC machining. To assess the surface roughness, tool wear, and machining cost implications of employing advanced machining methods for Al-SiC MMCs. Methods The parameters studied were voltage (V), feed rate (F), and electrolyte concentration (C) in electrochemical machining (ECM) of Al/15%SiC composites. To optimise process parameters, the Taguchi method for Design of Experiments (DOE) with an L27 orthogonal array was used. Signal responsiveness is optimised using the Taguchi approach. The Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) is used to find optimal machining settings. Findings: The outcome of this research is that the parameters affecting surface roughness and material removal rate are voltage, electrolyte concentration and feed rate. The minimum Surface Roughness achieved by selecting the best combination level is A2, B3, C3 (smaller is better) i.e., voltage 20 V, feed rate (f) 0.4 mm/min., electrolyte concentration (c) 30 g/lit. The maximum Material Removal Rate achieved by selecting the best combination level is A3, B3, C3 (larger-is-better) i.e., voltage 25V, feed rate (f) 0.4 mm/min., electrolyte concentration (c) 30 g/lit. Novelty : In this work, TOPSIS technique paired with Taguchi method is used which is rarely studied by other researchers. TOPSIS technique provides the best optimal solution as compared to other techniques. Keywords: Al-SiC MMCs, ECM, MRR, Ra, Taguchi method, TOPSIS

Development of conductive SiC-ZrN-TiB2 ceramics: A pathway towards electrical discharge machinable SiC based ceramics

Dense silicon carbide (SiC) composites with 0–30 vol% (ZrN-TiB2) were fabricated by using liquid phase spark plasma sintering at a relatively lower sintering temperature (1800 °C) and shorter holding time (5 min). The effects of co-addition of ZrN and TiB2 on densification, mechanical properties, and electrical conductivity of SiC ceramics were investigated. The reinforcement significantly enhanced density of sintered composites, while the phase analysis and microstructure confirm the suppression of β→α phase transformation in the SiC matrix. The fracture toughness ranged from 4.1 to 4.6 MPa·m0.5, hardness from 19.5 to 20.3 GPa, and electrical conductivity from 4.85 ×101 to 1.25 ×103 (Ω·cm)−1. Incorporating conductive reinforcements and nitrogen additives enhanced electrical conductivity. Successful wire-EDM cutting of SiC-ZrN-TiB2 composites demonstrate the feasible alternative to conventional machining of non-oxide ceramics with a maximum material removal rate of 8.54 mm2/min.

Optimization of process parameters in plasma arc cutting of commercial-grade aluminium plate

Abstract Plasma arc cutting (PAC) has emerged as a versatile and efficient method for the precision cutting of various materials, including commercial-grade aluminium plates. The optimization of process parameters is crucial for achieving high-quality cuts, minimizing material wastage, and enhancing overall productivity. This study aims to systematically investigate and optimize the key process parameters in PAC of commercial-grade aluminium plates. The experimental design involves the manipulation of parameters such as arc current, gas pressure, and workpiece thickness. A Design of Experiments approach, specifically Taguchi’s orthogonal array, is employed to efficiently explore the parameter space and identify the optimal combination of settings. The response variables considered for optimization include minimum surface roughness, minimum burr height, and maximum material removal rate (MRR). Analysis of variance is performed to get the percentage influence of each process parameter on the performance characteristic. The results obtained from the optimization process are expected to provide valuable insights into enhancing the efficiency and precision of PAC for commercial-grade aluminium plates. Arc current is found to be the most significant parameter in altering the surface roughness. The thickness of the material is the most significant parameter in altering burr height. None of the parameters is found to be significant in altering the MRR from Analysis of Variance analysis. From signal-to-noise ratio analysis and average performance graph, the optimum combination of processes in altering the bur height and MRR are found as arc current at 50 amp, the gas pressure at 5.4 bar, and the thickness of the workpiece at 6 mm.

Parametric optimization of the machining performance of Al-SiCp composite using combination of response surface methodology and desirability function

In this study, machining parameters such as speed, feed, and depth of cut were optimized for maximum material removal rate (MMR) of Al-SiCp composite turned with a tungsten carbide tool using response surface methodology based central composite design while keeping tool wear and surface roughness within specified limits. The influence of turning factors on flank wear and surface roughness height was investigated using regression models. ANOVA analysis is used to assess the appropriateness of the projected models and the significant factors for response optimization using the desirability method. The percentage contribution of the significant machining parameters and their interactions for optimization of the response is determined using ANOVA technique. Cutting speed is found to be the most significant factor for flank wear, average roughness height Ra and maximum roughness height Rt with contribution of 65.38%, 58.7% and 37.9% respectively for optimization of the response. Confirmation tests were carried out and the percentage error between observed and predicted value of the responses is found to be within acceptable limits, demonstrating that the created models correlates well with the experimental data. Under optimal conditions, utilizing a tungsten carbide tool can prove to be a cost-effective alternative for turning Al-SiCp composite.