Material Removal Research Articles

Wear behaviour of abrasive tools and its effect on surface integrity during polishing superalloy GH4169G with abrasive cloth flap wheels

In polishing nickel-based superalloys, the surface quality and dimensional accuracy of the workpiece are closely related to the wear of the abrasive tools. Over the years, several researchers have studied the wear of grinding wheels or abrasive belts, including the effects of various machining methods, abrasive materials, and machining parameters on the wear of abrasive tools. However, there is not enough research on the wear mechanism of the abrasive cloth flap wheel (ACFW). In this paper, during polishing GH4169G with ACFW, the wear evolution mechanism of ACFW and its effect on the surface integrity of GH4169G were investigated. First, the variations in material removal and ACFW wear amounts during the polishing process were analysed, and the different wear stages were divided based on the polishing ratio. Second, the mic-morphology and surface element distribution of ACFW at different wear stages were investigated using SEM and, EDS, and the wear evolution mechanism of ACFW was analysed. Finally, the effects of ACFW wear on the surface morphology, surface oxidation and microstructure of GH4169G were investigated by SEM, EDS, XRD, and EBSD. The results showed that the primary wear forms of ACFW were stepped fracture, cleavage fracture, blunt, pull-out, and adhesion wear. During the initial wear stage, the proportion of each wear form was relatively balanced. In the medium wear stage, fracture wear was the main wear form. Blunt and adhesive wear were the primary forms of wear during the final wear stage. In addition, with ACFW wear, the surface roughness tend to decrease first and then increase, however, the refinement level of the grains, the intensity of plastic deformation and the intensity of the oxidation reaction gradually increased. This study provides effective guidance for developing more wear-resistant abrasive tools and optimising the grinding and polishing processes.

Use of vegetable oils as dielectric fluids for electrical discharge machining. A case study

Electrical discharge machining with solid electrodes represents an efficient solution to generate blind cavities with complex geometry. Vegetable oils represent an alternative to conventional dielectrics, which are considered harmful for the environment and human health. This study tested the feasibility of two widely used vegetable oils, sunflower and soybean, under intense machining of three alloys with application in aeronautic industry, aiming for high process productivity and a good surface quality. The results have revealed that vegetable oils are capable to ensure an improvement of the material removal rates that can reach up to 55.15% compared to mineral oil. Also, the vegetable dielectrics allowed an improvement of surface quality for non-ferrous alloys, up to a maximum of 19.70%, whereas for the stainless steel, the mineral oil has provided a better surface finish.

Milling Stability Modeling by Sample Partitioning with Chatter Frequency-Based Test Point Selection

This paper describes a sample partitioning approach to retain or reject samples from an initial distribution of stability maps using milling test results. The stability maps are calculated using distributions of uncertain modal parameters that represent the tool tip frequency response functions and cutting force model coefficients. Test points for sample partitioning are selected using either (1) the combination of spindle speed and mean axial depth from the available samples that provides the high material removal rate, or (2) a spindle speed based on the chatter frequency and mean axial depth at that spindle speed. The latter is selected when an unstable (chatter) result is obtained from a test. Because the stability model input parameters are also partitioned using the test results, their uncertainty is reduced using a limited number of tests and the milling stability model accuracy is increased. A case study is provided to evaluate the algorithm.

Machinability and pulse characteristics of Ti-16Al-14Nb (α/β) alloy in wire-electric discharge machining process: A surface integrity study

The goal of the present work is to produce the efficient cutting of Ti-16Al-14Nb (α/β) alloy through wire-electric discharge machining and contemplate the terminologies such as machining ability, surface integrity and material removing capability. For this, the experimentation has been designed by considering three process parameters, pulse-on time ( Ton), pulse-off time ( Toff) and peak current ( Ip) at three significant levels (low, high, intermediate) in L27 order designed from design of experiments. The effect of these process variables on pulse characteristics, surface roughness ( Ra), kerfwidth ( Kw) and material removal rate ( MRR) is analyzed and mathematically modeled with analysis of variance. The results state that the highest MRR (0.521, 0.51, 0.506 mm3/sec) and low surface roughness (8.91, 8.89, 8.68 µm) values are observed at the highest level (110 µs, 15 µs, 8 A). If the pulse duration is kept at low ( Ton = 40µs, Toff = 3µs), the increase in peak current from 3 A to 8 A leads to a 64.54% increase in MRR and a 52.9% increase in Ra values. ANOVA results stated that Ton has contributed 20.4%, 35.8% and 19.3%, and Ip has contributed 43.1%, 30.5% and 46.6% influence on MRR, Kw and Ra respectively. The voltage–current characteristics studies confirmed that the strong intense pulses at a higher peak current (8 A) resulted in the increased MRR (0.521 mm3/sec) and Ra (8.43 µm) leading to the formation of swages and ridges. The surface integrity analysis derived from Abbott–Firestone curve agreed that the lowest level has shown better skewness ( Rsk = −0.274) and at highest level showed a larger deviation in skewness ( Rsk = +2.672) signifies that higher asymmetry (poor) of the surface.

Parametric analysis, modeling and optimization of the process parameters in electric discharge machining of aluminium metal matrix composite

Optimizing electric discharge machining (EDM) for aluminum/SiCp metal matrix composites poses challenges due to intricate machine parameters and process complexity, impacting process economy and elevating product costs. The research aims to find the optimal combination of process parameters which include pulse on-time, pulse current, duty cycle (%), gap voltage, sensitivity and flushing pressure for EDM of Al/SiCp-MMC using a copper electrode for the selected response factors such as material erosion rate and surface roughness, Ra. The experiments were designed using the central composite design of response surface methodology and an advanced optimization technique known as Teaching–learning-based optimization (TLBO), is applied to find the optimal combination of process parameters to obtain maximum material erosion rate subject to the desired range of surface roughness (SR), Ra. The combination of the high pulse on-time (i.e. 150 μs) and high pulse current (i.e. 12A) results in high material removal rate with deep craters on the machined surface clearly visible in SEM images contrasting the minimized surface roughness at lower values of pulse on-time (50 μs) and the pulse current (4A). Pulse on - time (Ton) is found to be the most significant factor for material erosion rate and surface roughness with percentage contribution of 70.86 and 54.9 respectively for optimization of the response. The regression models were developed at 95% confidence level for material removal rate and surface roughness with R2 value of 0.93 and 0.95 respectively signifying high degree of accuracy in predicting the response. Confirmation tests conducted to check the adequacy of the established models revealed that the percentage error between the predicted and experimental responses is found to be within acceptable levels. Electron discharge machining of the aluminium metal matrix composite at the optimized conditions could provide economical aspect in the aerospace and automobile industry.

Enhancing EDM performance with multi-objective decision-making using copper-coated aluminum electrodes and TOPSIS methodology for Ti-6Al-4V machining

The exploration of Electrical Discharge Machining (EDM) with coated electrodes represents a relatively novel research avenue, thereby yielding limited published research outcomes. The choice of coating material plays a pivotal role in the EDM machining process, and alterations in coating materials can directly influence the adjustment of technological parameters in EDM. Consequently, research dedicated to optimizing these technological parameters for EDM employing coated electrodes is of paramount importance, and it promises to advance the practical implementation of this cutting-edge technique. In this study, we systematically investigate the technological parameters for EDM employing a copper-coated aluminum electrode in the context of Ti-6Al-4V machining. Our research outcomes are framed within a multi-objective optimization paradigm, with a focus on Material Removal Rate (MRR) and Surface Roughness (SR) as vital quality indicators. To address the intricate multi-objective optimization challenge, we have harnessed the combined power of the Taguchi methodology and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The amalgamation of these techniques enables us to navigate the complexities of EDM parameter optimization effectively. Our findings reveal that the most favorable process parameters entail a configuration of [Formula: see text][Formula: see text]V, [Formula: see text] A, [Formula: see text][Formula: see text][Formula: see text]s, resulting in an MRR of 0.028[Formula: see text]mg/min and an SR of 7.56[Formula: see text][Formula: see text]m. These optimized parameters exemplify a substantial enhancement in machining efficiency and surface quality when utilizing coated electrodes. Moreover, our study scrutinizes the quality of the machined surface under optimal conditions with coated electrodes. We employ the TOPSIS method as a proficient solution for this endeavor, offering a straightforward approach to this intricate calculation process.

Material Removal and Surface Modification of Copper under Ultrasonic-Assisted Electrochemical Polishing

Material Removal and Surface Modification of Copper under Ultrasonic-Assisted Electrochemical Polishing

Cortical and Trabecular Bone Modeling and Implications for Bone Functional Adaptation in the Mammalian Tibia.

Bone modeling involves the addition of bone material through osteoblast-mediated deposition or the removal of bone material via osteoclast-mediated resorption in response to perceived changes in loads by osteocytes. This process is characterized by the independent occurrence of deposition and resorption, which can take place simultaneously at different locations within the bone due to variations in stress levels across its different regions. The principle of bone functional adaptation states that cortical and trabecular bone tissues will respond to mechanical stimuli by adjusting (i.e., bone modeling) their morphology and architecture to mechanically improve their mechanical function in line with the habitual in vivo loading direction. This principle is relevant to various research areas, such as the development of improved orthopedic implants, preventative medicine for osteopenic elderly patients, and the investigation of locomotion behavior in extinct species. In the present review, the mammalian tibia is used as an example to explore cortical and trabecular bone modeling and to examine its implications for the functional adaptation of bones. Following a short introduction and an exposition on characteristics of mechanical stimuli that influence bone modeling, a detailed critical appraisal of the literature on cortical and trabecular bone modeling and bone functional adaptation is given. By synthesizing key findings from studies involving small mammals (rodents), large mammals, and humans, it is shown that examining both cortical and trabecular bone structures is essential for understanding bone functional adaptation. A combined approach can provide a more comprehensive understanding of this significant physiological phenomenon, as each structure contributes uniquely to the phenomenon.

Investigation of white layer thickness, material removal rate, and tool wear rate of Inconel 718 by nano-Al2O3-mixed electrical discharge machining

Investigation of white layer thickness, material removal rate, and tool wear rate of Inconel 718 by nano-Al2O3-mixed electrical discharge machining

Micro-Grinding Parameter Control of Hard and Brittle Materials Based on Kinematic Analysis of Material Removal

This article explores the intricacies of micro-grinding parameter control for hard and brittle materials, with a specific focus on Zirconia ceramics (ZrO2) and Optical Glass (BK7). Given the increasing demand and application of these materials in various high-precision industries, this study aims to provide a comprehensive kinematic analysis of material removal during the micro-grinding process. According to the grinding parameters selected to be analyzed in this study, the ac-max values are between (9.55 nm ~ 67.58 nm). Theoretical modeling of the grinding force considering the brittle and ductile removal phase, frictional effects, the possibility of grit to cut materials, and grinding conditions is very important in order to control and optimize the surface grinding process. This research introduces novel models for predicting and optimizing micro-grinding forces effectively. The primary objective is to establish a micro-grinding force model that facilitates the easy manipulation of micro-grinding parameters, thereby optimizing the machining process for these challenging materials. Through experimental investigations conducted on Zirconia ceramics, the paper evaluates a mathematical model of the grinding force, highlighting its significance in predicting and controlling the forces involved in micro-grinding. The suggested model underwent thorough testing to assess its validity, revealing an accuracy with average variances of 6.616% for the normal force and 5.752% for the tangential force. Additionally, the study delves into the coefficient of friction within the grinding process, suggesting a novel frictional force model. This model is assessed through a series of experiments on Optical Glass BK7, aiming to accurately characterize the frictional forces at play during grinding. The empirical results obtained from both sets of experiments—on Zirconia ceramics and Optical Glass BK7—substantiate the efficacy of the proposed models. These findings confirm the models’ capability to accurately describe the force dynamics in the micro-grinding of hard and brittle materials. The research not only contributes to the theoretical understanding of micro-grinding processes but also offers practical insights for enhancing the efficiency and effectiveness of machining operations involving hard and brittle materials.

PERFORMANCE ENHANCEMENT OF BRASS EDM ELECTRODES WITH CRYOGENIC TREATMENT WHILE MACHINING THE COLD WORK STEEL AISI D2

This study investigates the performance of deep cryogenically treated brass (CuZn25Al5) electrodes in the die-sink EDM process. Two different cryogenic treatment durations, 6 h and 12 h, were applied to 8 mm diameter electrodes, and their effects were compared to untreated electrodes. The machining tests were conducted under moderate and aggressive conditions. In the machining tests, the 6-h cryo-treated electrode exhibited a 16.8% increase in material removal rate (MRR) under moderate conditions and a 19.7% increase under aggressive conditions compared to the reference electrode. The 12-h cryo-treated electrode showed similar MRR values to the reference electrode but improved tool wear resistance by 9.4% under moderate conditions. The kerf angle was minimized, indicating better hole verticality, in the 6-h cryo-treated electrode group. The improvement in machining performance was attributed to the enhancement in electrical conductivity of the electrodes, which increased by 28% for the 6-h cryo-treated electrode and 20% for the 12-h cryo-treated electrode. X-ray diffraction (XRD) analysis revealed shifts in peak positions and possible phase transformations due to cryogenic treatment. Surface roughness measurements showed improved surface conditions in the cryo-treated electrodes under aggressive conditions. The results indicate that cryogenic treatment enhances MRR, reduces tool wear, and improves surface quality in die-sink EDM. These improvements are attributed to increased electrical conductivity and changes in the internal structure of the brass electrode.

Study on the impact of ultrasonic vibration-assisted grinding of glass-ceramics on surface/subsurface damage mechanism

PurposeAn investigation was conducted into the impact of various process parameters on the surface and subsurface quality of glass-ceramic materials, as well as the mechanism of material removal and crack formation, through the use of ultrasonic-assisted grinding.Design/methodology/approachA mathematical model of crack propagation in ultrasonic-assisted grinding was established, and the mechanism of crack formation was described through the model. A series of simulations and experiments were conducted to investigate the impact of process parameters on crack depth, surface roughness, and surface topography during ultrasonic-assisted surface and axial grinding. Additionally, the mechanism of crack formation was explored.FindingsDuring ultrasonic-assisted grinding, the average grinding forces are between 0.4–1.0 N, which is much smaller than that of ordinary grinding (1.0–3.5 N). In surface grinding, the maximum surface stresses between the workpiece and the tool gradually decrease with the tool speed. The surface stresses of the workpiece increase with the grinding depth, and the depth of subsurface cracks increases with the grinding depth. With the increase of the axial grinding speed, the subsurface damage depth increases. The roughness increases from 0.780um/1.433um.Originality/valueA mathematical model of crack propagation in ultrasonic-assisted grinding was established, and the mechanism of crack formation was described through the model. The deformation involved in the grinding process is large, and the FEM-SPH modeling method is used to solve the problem that the results of the traditional finite element method are not convergent and the calculation efficiency is low.

Optimization of femtosecond laser processing parameters of SiC using ANN-NSGA-II

In the field of femtosecond laser machining, it is essential to select the appropriate process parameters to obtain near thermal damage-free and high efficient machining of SiC wafer. In this work, a method of process parameter optimization for femtosecond laser machining of 4H–SiC was proposed by using the predictive ability of the Artificial Neural Network (ANN) and the optimization algorithm of the non-dominated sorting genetic algorithm (NSGA-II). Firstly, the femtosecond laser was used to fabricate microgrooves on SiC wafers, and the effects of process parameters (laser average power, scanning speed and repetition rate) on groove depth, width, heat affected zone and material removal rate were investigated. Secondly, the ANN model is established based on experimental data. Other experiments verify the accuracy of the model, and the average error in the model’s predictions is around 5%. Thirdly, Pareto optimal solutions are obtained by global optimization of the ANN model using the NSGA-II. The experimental results show that the Pareto optimal solutions are effective and reliable. This proposed method offers dependable guidance for the selecting and optimizing process parameters of high hardness and brittle materials in the field of femtosecond laser processing, and reduces the cost of selecting the appropriate processing parameters in the production process. The method can also be extended to other machining means, such as turning and milling.

Optimizing Machining Efficiency in High-Speed Milling of Super Duplex Stainless Steel with SiAlON Ceramic Inserts

Super duplex stainless steels (SDSSs) are widely utilized across industries owing to their remarkable mechanical properties and corrosion resistance. However, machining SDSS presents considerable challenges, particularly at high speeds. This study investigates the machinability of SDSS grade SAF 2507 (UNS S32750) under high-speed milling conditions using SiAlON insert tools. Comprehensive analysis of key machinability indicators, including chip compression ratio, chip analysis, shear angle, tool wear, and friction conditions, reveals that lower cutting speeds optimize machining performance, reducing cutting forces and improving chip formation. Finite element analysis (FEA) corroborates the efficacy of lower speeds and moderate feed rates. Furthermore, insights into friction dynamics at the tool–chip interface are offered, alongside strategies for enhancing SDSS machining. This study revealed the critical impact of cutting speed on cutting forces, with a significant reduction in forces at cutting speeds of 950 and 1350 m/min, but a substantial increase at 1750 m/min, particularly when tool wear is severe. Furthermore, the combination of 950 and 1350 m/min cutting speeds with a 0.2 mm/tooth feed rate led to smoother chip surfaces and decreased friction coefficients, thus enhancing machining efficiency. The presence of stick–slip phenomena at 1750 m/min indicated thermoplastic instability. Optimizing machining parameters for super duplex stainless steel necessitates balancing material removal rate and surface integrity, as the latter plays an important role in ensuring long-term performance and reliability in critical applications.

Removal of Organic Materials from Mytilus Shells and Their Morphological and Chemical-Physical Characterisation

A simple and effective method to eliminate the organic component from mussel shells is presented. It is based on the use of hot hydrogen peroxide. Mollusc shells are composite materials made of a calcium carbonate matrix with different polymorphs and numerous biomacromolecules. The described method was used on mussel shells, but it is generalisable and allows the complete removal of these organic components, without altering the inorganic part. Specimens were kept in a H2O2 40% bath for few hours at 70 °C. The organic layers found on the faces of the shells were peeled away in this way, and biomacromolecules were degraded and removed. Their fragments are soluble in aqueous solution. This easily permits the chemical-physical characterisation and the study of the microstructure. The quality of calcite and aragonite microcrystals of biogenic origin is very high, superior to that of materials of geological or synthetic origin. This may suggest various industrial applications for them. Calcium carbonate is a useful precursor for cements and other building materials, and the one obtained in this way is of excellent quality and high purity.

Mathematical Analysis for Optimizing Electro Discharge Machining Parameters and Enhancing Hastelloy Machining Efficiency

This study investigates the process parameter optimisation for Hastelloy electro discharge machining (EDM). The goal of the research is to increase machining accuracy and efficiency by precisely changing the EDM process factors. The most important variables affecting tool wear, surface quality, and material removal rate are identified. In order to improve the machining performance for Hastelloy components, the research highlights the importance of factors including discharge current, pulse duration, electrode material, and dielectric fluid properties. The study's conclusions give important information about how to improve EDM procedures for this tough, corrosion-resistant hastealloy. Extensive research is conducted into the features of tool wear and their connection to process parameters in an effort to increase tool life and reduce manufacturing costs. The findings of this research offer useful data for optimising the efficiency of the Hastelloy EDM process in terms of both money and time. The growing need for high-performance components in industries including aerospace, chemical, and nuclear engineering is being addressed by this study, which intends to lay the groundwork for the development of efficient and environmentally friendly machining practises for Hastelloy. To do this, one must get a thorough comprehension of the interrelationships between the various process parameters.

Evaluation of cutting parameters during dry turning of AISI 304 stainless steel and optimization through a modified WPCA approach

The main objective of this study is to analyze how input parameters such as cutting speed ( Vc), depth of cut ( ap), feed per revolution ( f), and tool nose radius ( r) influence the performance of dry turning AISI 304 stainless steel. Performance evaluation includes cutting force components ( Fx, Fy, and Fz), surface roughness (SR), material removal rate (MRR), cutting power ( Cp), and cutting temperature ( T). Experiments are planned using the Taguchi L18 experimental design, and a coated carbide tool (GC 2025) is employed. ANOVA revealed that the most influential factors on SR are f and r, contributing 52.40% and 26.54%, respectively. Axial and tangential cutting force components are influenced by ap and f, with contributions of 72.99% and 5.93% for Fx and 81.57% and 13.38% for Fz, respectively. The radial component is influenced by ap (85.74%). Vc, f, and ap all contribute to cutting power, with contributions of 55.13%, 24.35%, and 10.74%, respectively. Finally, ap and the interaction f*ap contribute 45.18% and 8.81%, respectively, to the temperature in the cutting zone. This article introduces a novel multi-objective optimization method based on weighted principal component analysis. This method distinguishes itself by its ability to address challenges related to data matrix normalization, the ambiguity of eigenvector signs, and the issue of negative signs in Taguchi’s philosophy. The results of the new method, the desirability function, and the classical WPCA method are compared. The results show that the new method suggests a compromise solution that is similar to the desirability function and better than the classical WPCA’s suggestion.

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.

Parametric investigation of thermal additive centrifugal abrasive flow machining process for enhancing productivity

Thermal additive centrifugal abrasive flow machining hybrid of abrasive flow machining caters to low material removal issues which enhances the acceptability of the process. The present investigation investigates the different centrifugal force-generating electrode geometry performances in the thermal additive centrifugal abrasive flow machining process. The L27 orthogonal array is used for optimizing the process parameters (electrode type, current supply, and the duty cycle) and their effect on material removal and percentage improvement in surface finish (%Δ Ra) are analyzed. Based on the percentage contribution obtained from Taguchi analysis, electrode type is the prominent parameter for material removal (88.27%) and %Δ Ra (78.54%) followed by current (7.43% for material removal and 13.92% for %Δ Ra) and duty cycle (3.95% for material removal and 6.42% for %Δ Ra). The spline electrode with a curved blade is found optimum with 10 A current and 0.76 duty cycle. The average experimental value based on the design of the experiment and the predicted value for material removal is 10.373 and 10.881 mg, respectively. The average experimental value and the predicted value for percentage improvement in the surface are 42.24% and 43.71%, respectively. The percentage error between the predicted and experimental values for material removal and %Δ Ra is 4.66% and 3.15%, respectively.

Investigation of the influence of different types of electrolytes on the performance of the Electrochemical Discharge Machining process during micromachining of molybdenum

Electrochemical Discharge Machining (ECDM) is a hybrid process that integrates the principles of Electrochemical Machining (ECM) and Electrical Discharge Machining (EDM) to create micro-holes in both conductive and non-conductive materials that are typically difficult to machine. Given the unpredictable nature of this hybrid method, the composition of the electrolyte emerges as a critical factor influencing the accuracy and performance of the machining process. Consequently, the optimization and analysis of electrolytes are pivotal for the efficient utilization of energy during ECDM and for ensuring machining precision. This study aims to experimentally investigate the impact of various types of electrolytes and their concentrations. These are divided into two categories: neutral solutions, which include sodium nitrate (NaNO₃) and sodium chloride (NaCl), and alkaline solutions, comprising sodium hydroxide (NaOH) and potassium hydroxide (KOH), as well as a mixture of both NaOH and KOH. The evaluation metrics considered include the Material Removal Rate (MRR), Tool Wear Rate (TWR), overcut (OC), Heat Affected Zone (HAZ) and surface quality. It was observed that alkaline solutions, particularly the mixed electrolyte, resulted in higher MRR and HAZ, reduced TWR, and the production of micro-holes with minimized overcut compared to using KOH and NaOH separately or neutral solutions, while also enhancing surface quality. Further analysis using Scanning Electron Microscopy (SEM) images and Energy-Dispersive Spectroscopy (EDS) of the brass tools used with different electrolytes revealed that tools used in KOH and mixed electrolytes exhibited less wear and material erosion compared to those used in NaOH and neutral solutions.