Maximum Material Removal Rate Research Articles

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.

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.

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.

Experimental investigation during nano powder added µ-ED milling on nickel-titanium shape memory alloy

Nickel-titanium (NiTi) shape memory alloy (SMA) is one of the smart materials which has a vast application in the aerospace and biomedical industry due to its shape memory effect (SME), strong corrosion and wear resistance. Thus, the present study investigates the influence of process variables like gap voltage (V), powder concentration (PC) and pulse on time (ton) towards the material removal rate (MRR), surface roughness (SR) and micro-hardness (MH) amid graphene nano powder added micro-electrical discharge milling (µ-ED milling) of NiTi SMA. ANOVA analysis has been carried out to determine the % distribution of individual machining parameters towards all responses. The addition of graphene nano particles to the dielectric oil considerably enhanced the MRR, MH, and decreased the SR of the milled micro-channel. Taguchi’s grey relational analysis (GRA) and grey-desirability approach have been applied for multi-response optimisation to find the maximum MRR, MH, and minimum SR. It is discovered that the grey-desirability method improves all the responses. The Field emission scanning electron microscopy (FESEM) micro-graphs confirm defect-free mirror-like surface finish at the optimal grey-desirability setting. The X-ray diffraction (XRD) analysis discovered the formation of oxides and hardened phases in the machined surface. The application of graphene enhanced the recast layer thickness and reduced the indentation depth at subsurface region. The nano indentation test validates the rise in nano hardness and elastic modulus at the grey desirability optimal setting compared to the initial machining condition.

Multi-axis near-dry Electrical Discharge machining using inconel 718 alloy

ABSTRACT In the current research work, in-house developed and fabricated multi-axis near-dry Electrical Discharge Machine (near-dry EDM) has been used having different tool positions, i.e. tool electrodes in horizontal position (Case-I) and vertical positions (Case-II) as a novel machining techniques in hard-to-reach places and also to improve the process performance. Design of Experiment tool has been used with three process parameters: voltage, discharge current, and pulse-on-time for experimentation purposes. In order to maximize Material Removal Rate (MRR), it was necessary to compare and enhance these parameters in both cases, i.e. Case-I, and Case-II. The machining process is significantly influenced by the vertical tool positions, as indicated by the largest percentage contribution in the Analysis of Variance results. The voltage has the least influence, while the pulse-on time is relatively less. In contrast, for the horizontal tool position, the voltage proved the most prominent factor in terms of influence, while the current ranked second in significance. Conversely, the pulse-on time exhibited the least impact among the three factors. The highest MRR 2.45 mm3/min was achieved in the vertical tool position while in horizontal machining, the highest MRR 0.144 mm3/min was observed. These findings provide valuable insights into the multi-axis near-dry EDM with proposed methodology.

Surface topography characterization of USMM during machining of zirconia ceramic using silicon carbide abrasives: An experimental and simulation approach

Zirconia is a highly biodegradable ceramic material with excellent fracture resistance, in biomedical engineering, particularly dental implants. This research work has been focused on optimizing the quality of micro-hole generation in zirconia ceramic through ultrasonic micromachining (USMM). Three key process parameters such as abrasive slurry concentration, tool feed rate, and power rating are considered in this research work. The material removal rate, overcut, and taper angle are considered as responses. Response surface methodology has been employed for modeling during the USMM process, and a mathematical model has been developed to understand material removal mechanisms. Finite element analysis has been utilized to provide insights into the impacting process for industry requirements. A 3D model has been created to perform dynamic analysis under practical conditions. Multi-objective optimization has been applied to achieve optimum material removal rate (MRR), overcut, and taper angle. From multi-objective optimization, a slurry concentration of 49.59% g/l, tool feed rate of 1.16 mm/min, and power rating of 386.87 W has been found and in this parameter settings maximum MRR of 0.5333 mm3/min, minimum taper angle of 0.3428 degrees, and minimum overcut of 36.64 µm has been obtained during machining of ZrO2 ceramics.

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.

The Investigation of Material Removal Rate on Electrical Discharge Machining of Titanium Alloys (Ti-6Al-4V) at Different Peak Currents and Pulse Durations by Using RBD Palm Oil and Kerosene as Dielectric Fluids

The type of dielectric fluid is the most significant component that might affect the machining performance of EDM such as material removal, tool wear, and electrode surface roughness. However, the most serious of these issues is the inability to comply with health and environmental rules when the conventional dielectric was harmful to the surrounding ecosystem. One approach to ensure the long-term sustainability of EDM is to use vegetable oil as the dielectric fluid as it is environmentally friendly and biodegradable. To satisfy industrial objectives, the machining industry must ensure that the maximum material removal rate (MRR) can be achieved. This paper investigated the effect of kerosene and refined, bleached, and deodorised (RBD) palm oil as dielectric fluids with different peak currents (6, 9, and 12A) and pulse duration (50, 100 and 150µs) settings on MRR of Titanium alloy. Kerosene was used as a benchmark to compare the performance of the EDM process. The implementation of RBD palm oil recorded the lowest MRR at the lowest peak current of 6A with the lowest pulse duration of 50µs, which is 1.1260mm3/min. In contrast, the highest MRR with a value of 12.1323mm3/min was recorded at the highest peak current of 12A with a pulse duration of 150µs. Overall, RBD palm oil shows an excellent MRR performance for substituting hydrocarbon or mineral oil as a dielectric fluid in EDM applications, improving cost, time, and production efficiency.

Multi-objective optimization for balancing surface roughness and material removal rate in milling hardened SKD11 alloy steel with SIO2 nanofluid MQL

In manufacturing practice, manufacturers always strive to achieve both quality and productivity targets simultaneously. In the first part, this study examines the relationship between input factors, including cutting speed, depth of cut, and feed rate, and the output response, which is surface roughness, when milling hardened SKD11 alloy steel under minimum coolant lubrication conditions using SiO2 nanofluid. The input parameters are divided into four levels to determine their influence on surface roughness and to find the optimal conditions for achieving the minimum surface roughness. The experimental design was conducted using an L16 array. A second-order regression model was developed to describe the relationship between the input variables and the output response. In the second part, multi-objective optimization was performed to simultaneously achieve the minimum surface roughness and the maximum material removal rate (MRR). The Response Surface Methodology (RSM) was employed in this study. The results indicated that to achieve the minimum surface roughness, machining should be performed at a cutting speed of 100 m/min, a cutting depth of 0.2 mm, and a feed rate of 0.01 mm/tooth. With these settings, the predicted surface roughness could reach 0.0451 µm. On the other hand, for the multi-objective optimization, to achieve the minimum surface roughness and the maximum MRR simultaneously, machining should be carried out at a cutting speed of 100 m/min, a cutting depth of 0.36 mm, and a feed rate of 0.0168 mm/tooth. With this cutting condition, the predicted surface roughness could reach 0.1069 µm, and the predicted MRR could reach 775.06 mm3/min

Investigation on the effect of chemical mechanical polishing sapphire substrate on chemical vapor deposition growth of two-dimensional MoS2

Two-dimensional molybdenum disulfide (2D MoS2), with atomic-level thickness, whose crystal crystallinity and size are easily influenced by the surface morphology of the substrate during growth. This work systematically investigates the impact of chemical mechanical polishing (CMP) sapphire substrate on chemical vapor deposition (CVD) growth of 2D MoS2. A green and highly efficient CMP method for the sapphire substrate is first proposed, whose maximum material removal rate (MRR) of 4.27 µm/h with surface roughness (Ra) of 0.10 nm (AFM, scanning area of 5 × 5 μm2) can be attained. The size and thickness statistics of 2D MoS2 domains grown on different substrates indicate that the CMP sapphire substrate in this work can promote the size and monolayer uniformity of 2D MoS2 during CVD growth. Meanwhile, Raman and photoluminescence (PL) spectra of monolayer MoS2 grown on different substrates also indicates the monolayer MoS2 grown on the CMP sapphire substrate in this work has superior crystalline quality and optical properties. The above findings have provided new insights into the mechanisms underlying 2D MoS2 growth on surfaces in various states and are expected to accelerate the development of large size large-size and high-quality growth of two-dimensional material for further device applications.

Bi-objective optimization of an EDM process with Cu-MWCNT composite tool using single-valued neutrosophic grey relational analysis

Purpose In many of today’s manufacturing industries, such as automobile, aerospace, defence, die and mould making, medical and electrical discharge machining (EDM) has emerged as an effective material removal process. In this process, a series of discontinuous electric discharges is used for removing material from the workpiece in the form of craters generating a replica of the tool into the workpiece in a dielectric environment. Appropriate selection of the tool electrode material and combination of input parameters is an important requirement for performance enhancement of an EDM process. This paper aims to optimize an EDM process using single-valued neutrosophic grey relational analysis using Cu-multi-walled carbon nanotube (Cu-MWCNT) composite tool electrode. Design/methodology/approach This paper proposes the application of grey relational analysis (GRA) in a single-valued neutrosophic fuzzy environment to identify the optimal parametric intermix of an EDM process while considering Cu-MWCNT composite as the tool electrode material. Based on Taguchi’s L9 orthogonal array, nine experiments are conducted at varying combinations of four EDM parameters, i.e. pulse-on time, duty factor, discharge current and gap voltage, with subsequent measurement of two responses, i.e. material removal rate (MRR) and tool wear rate (TWR). The electrodeposition process is used to fabricate the Cu-MWCNT composite tool. Findings It is noticed that both the responses would be simultaneously optimized at higher levels of pulse-on time (38 µs) and duty factor (8), moderate level of discharge current (5 A) and lower level of gap voltage (30 V). During bi-objective optimization (maximization of MRR and minimization of TWR) of the said EDM process, the achieved values of MRR and TWR are 243.74 mm3/min and 0.001034 g/min, respectively. Originality/value Keeping in mind the type of response under consideration, their measured values for each of the EDM experiments are expressed in terms of linguistic variables which are subsequently converted into single-valued neutrosophic numbers. Integration of GRA with single-valued neutrosophic sets would help in optimizing the said EDM process with the Cu-MWCNT composite tool while simultaneously considering truth-membership, indeterminacy membership and falsity-membership degrees in a human-centric uncertain decision-making environment.

Controlling recast layer and material removal in reverse µEDM for sustainable fabrication of microelectrode arrays

Microelectrode arrays (MEAs) are essential for researching neurons and heart tissue because they record and stimulate neuronal activity. For manufacturing MEAs on conductive materials, reverse microelectrical discharge machining, or reverse µEDM, presents a viable method. However, achieving precise MEAs requires control over recast layers generated during micromachining. This study focuses on recast layer thickness (RLT) and material removal rate (MRR) as key performance indicators for sustainable reverse µEDM fabrication of MEAs. RLT affects surface stability, while MRR influences energy consumption and cost. Optimising these responses depends on three input factors: feed rate, capacitance, and voltage. ANOVA analysis reveals that capacitance is crucial in both MRR and recast layer thickness (RLT) in reverse µEDM, contributing to 88.71% and 94.04% simultaneously. A hybrid artificial neural network-genetic algorithm for global optimisation was employed. The optimised parameters 46.5nF capacitance, 110 V voltage, and 5 µm/sec feed yielded a minimum RLT of 1.58 µm and a maximum MRR of 0.3 mm³/min. These advancements signify significant improvements in the precision and efficiency of MEAs fabrication through reverse µEDM, contributing to its sustainable implementation.

Investigation of micro-electro-discharge machining process parameters during machining of M2 hardened die-steel

Micro-electro-discharge machining (micro-EDM) is a well-known micromachining method to create microstructures on hard-to-cut materials. To further exploit the capability of micro-EDM, the present research work investigates the effect of various important micro-EDM process parameters on the material removal rate (MRR), tool wear rate (TWR), and overcut (OC) during micro-cavity machining of M2-hardened die-steel. A Taguchi experimental design was used to study the effects of three process parameters namely pulse-on-time (Ton), peak current (Ip), and gap voltage (Vg). The experimental results showed that the most influencing process parameter in the present experimental investigation is peak current, Ip followed by pulse-on-time, Ton and gap voltage, Vg. Furthermore, a recent and effective method i.e. Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) has been successfully employed to determine optimal process parametric combination for micro-EDM process to achieve maximum MRR and minimum TWR and OC during machining of micro-cavity on M2-hardened die-steel. From the present research investigation, the optimal micro-EDM process parametric combinations obtained for higher MRR, lower TWR and OC are found as 1 A of peak current, 30 μs pulse-on time and gap voltage of 60 V. Furthermore, through various scanning electron microscope micrographs of micro-cavities and micro-machined surfaces, analysis has been done to find out the micro-cavity with best geometrical accuracy and surface feature to validate the best and most ideal combinations of micro-EDM input parameters for micromachining operations. The results of this study show that micro-EDM is a promising process for machining M2-hardened die-steel. The optimization of process parameters using the MARCOS methodology can further improve the machining efficiency and accuracy of micro-EDM.

Parametric study of WEDM of titanium grade 12 using RSM and desirability approach

The present experimental study aims to scrutinize the effect of different process parameters on the material removal rate (MRR) and surface roughness (SR) of titanium grade 12 alloy during wire electro-discharge machining (WEDM) using response surface methodology. Four parameters (pulse-on time, pulse-off time, wire feed and gap voltage) and three levels of each selected variable are considered to conduct the experimental work. Depending on experimental results, a mathematical model is generated for both MRR and SR. An analysis of variance (Anova) study is performed to find significant process parameters. The Anova results show that the developed models for both MRR and SR are significant, and pulse-on time is found to be the most significant parameter. Additionally, the desirability approach is used to scrutinize the single-objective and multi-objective criteria of response variables. The desirability functions for all of the cases are found to be 1. The maximum MRR is observed to be 12.4845 mm3/s, while the minimum value of SR is found to be 1.4911 μm. For multi-objective optimization, the maximum value of MRR and the minimum value of SR are obtained as 12.0942 mm3/min and 1.7167 μm, respectively. Finally, the surface morphology of the machined surfaces is examined using scanning electron microscopy micrographs.

Synergistic effect of abrasive friction and glycine on improving chemical mechanical polishing performance of single-crystal GaN substrate

With the rapid development of the third-generation semiconductor materials, the chemical mechanical polishing rate and surface quality of single-crystal gallium nitride (GaN) substrates have been a research hot-spot. In this work, the synergistic effect of abrasive friction and glycine (Gly) on improving the chemical mechanical polishing (CMP) performance of single-crystal GaN substrate is proposed and studied systematically. The results indicated that the polishing solutions with Gly have a 2.3-fold improvement in material removal rate (MRR) as well as scratch-free surface than that without Gly. The maximum MRR of the single-crystal GaN substrate is 129.4 nm/h with surface roughness (Ra) of 0.64 nm attained by using the polishing solutions containing only 3 wt% potassium persulfate (K2S2O8). In contrast, when Gly is added as a reaction reagent, which can be activated by abrasive friction, the maximum MRR is increased to 304.2 nm/h with Ra of 0.42 nm. Meanwhile, the epitaxial evaluation indicates that two-dimensional (2D) MoS2 grown on processed single-crystal GaN substrate has superior crystalline quality and optical properties. Finally, the polishing mechanism of the single-crystal GaN substrate using the mixed solutions of K2S2O8 and Gly is discussed. The proposed CMP method has potential applications in the semiconductor and microelectronics industries.

Assessment of machinability behaviour of LM24 – nano Al2O3 – gr hybrid composites through stir casting technique

Abstract This study is focused on developing a novel combination of a hybrid MMC made of LM24 aluminium alloy, nano Al2O3 and Graphite for enhanced machinability. The study conducts a series of experimental runs and evaluates surface roughness and material removal rate. The process parameters of spindle speed, feed, and depth of cut have been varied, while different weight percentages of nano Al2O3 (1%, 3%, and 5%) were incorporated into the LM24 metal matrix alloy along with 1 wt% of Gr. Response Surface Methodology (RSM) is used to optimize the turning parameters and enhance the machining performance for better quality and productivity. The derived optimal machining parameters have been verified through confirmatory tests. An analysis of variance (ANOVA) was used to determine the individual contributions of each parameter to the machinability characteristics. Surface morphology analysis revealed the uniform distribution of nanoparticle reinforcements in the metal matrix. The surface roughness and material removal rate of the machined nanocomposites were studied. The optimized outputs are a minimum surface roughness Ra 0.522 μm and maximum material removal rate MRR 110.2 mm3s–1 The maximum hardness of the MMC composites has been 60.5 HRB.

Erosion-corrosion failure analysis of the elbow pipe of steam distribution manifold

This work discusses a case study of the failure of rice condition plant boiler pipe fittings. The failure analysis was performed on the 45° and 90° API 5LX65 steel pipe elbows connected to a steam manifold in a boiler of a rice conditioning plant. Failure analysis was performed by visual observation, microscopic analysis, hardness measurements, and numerically by Computational Fluid Dynamics (CFD). It was confirmed that the mechanism of failure was due to erosion-corrosion. The results showed also that, erosion-corrosion at the outlet of the 90° and 45° elbows due to the maximum particle impact in the high pressure and high turbulence intensity region. Microscopic analysis of the 90° and 45° elbows showed that large pits and cuts were the main reason for leakage perforation. Erosion at the inner bend of the 90° and 45° elbows is lower than at the outer bend, which is related to the higher particle–wall impaction, pressure, and turbulence intensity. The main cause of leakage and wall thinning in both elbows is the development of limescale which leads to pitting corrosion and the formation of leaks at higher oxygen concentrations. The simulation results show that the maximum material removal rate in the 45° elbow is 42 % lower than in the 90° elbow, the erodent impaction and higher wall shear are liable for the development of the perforation near the exit of 90° and 45° elbows.