Material Removal Research Articles

Selective removal of variable thickness multilayer materials based on photoelectric detection

An ultrafast laser processing system with near-axis monochromatic photoelectric detection for selective removal of variable thickness multilayer materials is proposed. The correlation between signal evolution and ablation progress of silver layer with the variable thickness is established, and a signal attenuation threshold is determined to ensure non-removal of the substrate, providing criteria for the processing strategy combining high and low energies. The proposed strategy is experimentally validated, which balances the quality of low-energy removal and the efficiency of high-energy removal.

Parametric Study of Electrical Discharge Turning Process of Al7075/ZrO2-MMC

The mechanical properties of Aluminum metal matrix composites (AMMCs) have made them a popular choice in various industries such as automotive, aerospace, and marine. However, their composition, which includes abrasive reinforcements, makes them difficult to machine using conventional techniques. So, unconventional machining processes play a vital role in the machining of these materials. Electrical discharge turning (EDT) is one of the configurations of electrical discharge machining (EDM) that is utilized to machine cylindrical-shaped workpieces. In this study, AMMC Al 7075/ZrO2 was fabricated using the stir casting method. Further, investigated the effect of machining parameters of EDT, namely pulse Current (I), pulse on time (T-ON), and rotating speed (RPM), on Al 7075/ZrO2 in terms of material removal rate (MRR), tool wear rate (TWR), and overcut (OC) using one parameter at a time (OPAT) method. The outcome of the experiment reveals that MRR, TWR, and OC are more impacted by pulse current than by rotational speed. A decrease in TWR was also found with an increase in pulse on time for all rotational speeds. The size of the craters and globules observed lower with 1400 RPM in the micrograph image.

An experimental investigation of process parameters on material removal and surface roughness improvement in abrasive flow machining

Abstract Today, there is huge demand for mechanical components with long life cycles, and superior surface finishes as a result of the industrial revolution. New methods for nano-finishing complex structures, including abrasive flow machining (AFM), have been developed in response to the need for superior surface finish. This is a relatively new technique in non-conventional machining techniques. Because abrasion only happens in locations where flow is restricted, this approach is utilized to polish metallic parts as well as interior, inaccessible cavities, and recesses using a semi-liquid paste. It has evolved to flow of abrasives with a viscoelastic polymer (referred to as abrasive media) over complex geometries, and edges to deburr, and radius those surfaces. This paper focuses on investigating the impact of process parameters on material removal, and percentage improvement in surface roughness on cylindrical brass workpieces using Taguchi L9 orthogonal array, the number of cycles, extrusion pressure, and grit size of abrasives have been selected. The abrasive medium employed in this investigation is composed of a blend of polymer, hydrocarbon gel, and aluminium oxide abrasive particles with varying grit sizes. The outcome shows which process parameters to optimize for material removal, and improvement in percentage improvement in surface roughness. The number of cycles that have the largest percentage contribution to material removal was 83.74%. For the response material removal, the percentage contributions of the abrasive particle grit size, and extrusion pressure are 2.03%, and 14.16%, respectively. N2P2G3 has the optimal level used for material removal. The largest percentage contribution to improvement in surface roughness, or 83.48%, was the result of the number of cycles. Extrusion pressure, and abrasive particle grit size account for 7.38%, and 8.88% of the total percentage contribution, respectively. N3P2G3 has the optimal level obtained for percentage improvement in surface roughness improvement.

Study on electrochemical polishing mechanism of TC4 titanium alloy

Abstract To achieve a high-quality and precise surface on TC4 titanium alloy for demanding engineering applications, electrochemical polishing (ECP) technology was employed to investigate the polishing process of TC4 titanium alloy in an ethylene glycol-sodium chloride green electrolyte. The macro and micro morphology, surface roughness, material removal rate, surface elements, surface corrosion resistance, and surface hardness of TC4 titanium alloy were measured before and after polishing. Single-factor experiments were conducted to explore the effects of processing gap, electrolyte temperature, polishing voltage, and polishing time on TC4 titanium alloy surface quality. Optimal polishing parameters were determined to be an electrode gap of 12 mm, a voltage of 20 V, a temperature of 40 °C, and a polishing time of 10 minutes. The experimental results indicated that after electrochemical polishing, the workpiece surface roughness Ra decreased from 256 nm to 25 nm, achieving a roughness reduction rate of 90.23%, the material removal rate was 3.348 μm/min. The self-corrosion potential of the polished surface increased from -0.416 V to -0.375 V and the self-corrosion current density decreased from 4.447×10-7 A·cm-2 to 1.873×10-7 A·cm-2, the surface indentation hardness of the workpiece decreased from 5.8669 GPa to 4.6726 GPa. Based on the characterization of polished surface, the mechanism of electrochemical polishing of TC4 titanium alloy was proposed. The results demonstrate that electrochemical polishing of TC4 titanium alloy is highly efficient, involves no mechanical action, and causes no subsurface damage, making it a promising technology to meet medical requirements.

An energy concisions analytical modelling approach with experimental verification for cutting performance assessment in EDM of Ti-based superalloy

Abstract Electric discharge machining (EDM) is a stochastic process which is commonly engaged for cutting of Ti-based difficult-to-cut alloys. Experimental investigation in EDM is costly and requires significant amount of time due to the complex nature of the process. Moreover, the energy intensive nature is another criticism associated to this technique. Therefore, this research is focused on developing an energy conscious mathematical model of the process while considering the categorical parameters like type of dielectric, electrode and nano-powder along with pulse time ratio. Taguchi design of experiment (DOE) has been executed for the experimentation. The comprehensive analysis of the findings depicts transformer oil (TO) delivers a remarkable improvement in MRR and SEC in comparison to other dielectric choices. Furthermore, brass electrode stands out for achieving the best surface finish. When it comes to micro-additives, SiC exhibits substantial potential in increasing MRR, and graphite gives a better surface finish. The process has also been effectively modeled which helps to predict material removal rate (MRR), surface roughness (SR) and specific energy consumption with decent precision which is the key contribution of this study. 3D simulation for EDM illustrates that the features of the crater are defined by the liquefied region, whilst the dynamics of the mushy zone play a crucial role in controlling and characterizing the microstructure size progression. The confirmatory experimental results revealed that the use of optimized parametric combinations demonstrate 90.87% improvement in MRR, 52.07% reduction in SR and 96.19% decrease in SEC in contest to the responses’ values obtained at non-optimal settings.

Multi-Step Two-Dimensional Ultrasonic-Assisted Grinding of Silicon Carbide: An Experimental Study on Surface Topography and Roughness

Two-dimensional ultrasonic-assisted grinding (2D-UAG) has exhibited advantages in improving the machining quality of hard and brittle materials. However, the grinding mechanism in this process has not been thoroughly revealed due to the complicated material removal behaviors. In this study, multi-step 2D-UAG experiments of silicon carbide are conducted to investigate the effects of machining parameters on surface quality. The experimental results demonstrate that the tool amplitude and the workpiece amplitude have similar effects on surface roughness. In the rough grinding stage, the surface roughness decreases continuously with increasing ultrasonic amplitudes and the material is mainly removed by brittle fracture with different surface defects. Under semi-finishing and finishing grinding steps, the surface roughness first declines and then increases as the tool amplitude or workpiece amplitude grows from 0 μm to 8 μm and the inflection point appears around 4 μm. The surface damage contains small-sized pits with band-like distribution and localized grooves. Furthermore, the influences of cutting parameters on surface quality are similar to those in conventional grinding. Discussions of the underlying mechanisms for the experimental phenomena are also provided based on kinematic analysis. The conclusions gained in this study can provide references for the optimization of machining parameters in 2D-UAG of hard and brittle materials.

Atomic Depth Image Transfer of Large-Area Optical Quartz Materials Based on Pulsed Ion Beam

The high-efficiency preparation of large-area microstructures of optical materials and precision graphic etching technology is one of the most important application directions in the atomic and near-atomic-scale manufacturing industry. Traditional focused ion beam (FIB) and reactive ion etching (RIE) methods have limitations in precision and efficiency, hindering their application in automated mass production. The pulsed ion beam (PIB) method addresses these issues by enhancing ion beam deflection to achieve high-resolution material removal on a macro scale, which can reach the equivalent removal resolution of 6.4 × 10−4 nm. Experiments were conducted on a quartz sample (10 × 10 × 1 mm) with a specific pattern mask using the custom PIB processing device. The surface morphology, etching depth, and roughness were measured post-process. The results demonstrated that precise control over cumulative sputtering time yielded well-defined patterns with expected average etching depths and surface roughness. This confirms the PIB technique’s potential for precise atomic depth image transfer and its suitability for industrial automation, offering a significant advancement in microfabrication technology.

Experimental investigation of Aluminum Nitride ceramics based on compliant finishing process

Aluminum Nitride (AlN), as a type of advanced functional ceramic material, has found wide applications in many fields, owing to its advantageous properties such as excellent thermal conductivity, high hardness and strength, etc. Nevertheless, these beneficial features bring great challenges to its machinability using current existing methods that commonly result in unsatisfactory surface qualities. In this paper, we investigated the processing performance of AlN by introducing the compliant bonnet finishing approach based on different tool bonding materials and abrasive sizes. The distinctive finishing qualities, material removal rates, tool wear behavior, etc., were studied and compared under various process conditions. Unlike other ceramics, resin bonded diamond tools with a 3 μm abrasive size exhibit significant wear when used on AlN ceramics. The curves for tool wear amount and wear rate are investigated. Meanwhile, compliant tool with the smaller abrasive can obtain the sub-50 nm surface roughness. The comparison with traditional rigid pellet finishing further demonstrates the advantageous finishing performances by using compliant tools on the AlN ceramics.

Removal efficiency of a fast setting pozzalan-based bioactive cement: a micro CT study

AimThe aim of this study was to evaluate the removal efficiency of PRMTA and ECMPremixed applied to the coronal third according to the RET by UI and to examine the effect of different solutions on material removal.Materials and methods40 permanent upper central teeth were used to simulate immature teeth. The samples were irrigated with 1.5% NaOCl and calcium hydroxide was placed. Samples were incubated in PBS. Then irrigation was done with 17% EDTA, the samples were randomly divided into 2 groups (n = 20):Group 1: PRMTA, Group 2: ECM Premixed. The materials were placed in the samples. Then the samples were scanned with micro-CT. Materials were removed by UI. Micro-CT scan of the samples was performed. Each material group was divided into 2 subgroups (n = 10): Group1 was MTAD, group2 was irrigated with 10% CA; then micro-CT was performed. Obtained images were positioned in DataViewer and analyzed with CTAn. The obtained data were statistically analyzed in IBM SPSS 25. The significance level was determined as 5%.ResultsThere was no significant difference between the initial volumes of the materials (p > 0.05). The amount of the remaining material after UI was significantly higher in the PRMTA (0.7471%) group compared to the ECM Premixed (0.0093%). There was no significant difference in terms of remaining material after irrigation with MTAD and CA in both groups (p > 0.05).ConclusionA great deal of the materials were removed by UI under the operation microscope. ECM Premixed was removed more effectively compared to the PRMTA. And, acidic solutions did not provide any additional benefit in material removal.

A CFD simulation platform for surface finishing processes in advanced manufacturing

Products created by additive manufacturing often have surface imperfections that require post-processing operations to remove extraneous material in order to meet design specifications. The usage of computational fluid dynamics (CFD) simulations to predict material removal rates of components, allows practitioners to optimize the setup and usage of post-processing equipment. However, those without in-depth knowledge of CFD or the related specialized software, require an easy-to-use and cost-effective application to manage the computational workflow. The two specific surface finishing applications investigated here, are, abrasive flow machining (AFM) and robotic stream finishing (RSF). In order to satisfy user requirements, a modular, threaded, fault-tolerant and object-oriented project management application, written with the Python programming language and PyQt6 framework, has been developed to conduct surface finishing-related CFD simulations using OpenFOAM®. The advantages of the proposed software are: 1) the modern PyQt6 framework is used to develop a cross-platform and user-friendly application which employs the model-view class architectural paradigm for data management and its display, 2) step-by-step interactive project workflows have been tailored specifically for AFM and RSF simulations, 3) the developed steady-state viscoelastic flow solver for AFM and continuum-based steady-state dense granular flow solver for RSF, offer advantages over those provided by OpenFOAM® and 4) simulation results have been corroborated by experimental data to assess the improved accuracy of material removal prediction of the current software when compared to other commercial applications.

Molecular dynamics simulation and experimental study of the material machinability characteristics and crack propagation mechanisms for fused silica double nanoscratches

Fused silica is a high-purity, hard and brittle, difficult-to-machine amorphous material that is widely used in the aerospace, optical instruments, semiconductors, microelectronics and other important fields. However, the influence of adjacent scratches on material deformation and subsurface damage during ultraprecision machining by abrasive particles is not well understood. This study aims to investigate the influence of micron-spaced double scratches on the deformation and damage for fused silica through molecular dynamics simulations and double nanoscratch experiments. An amorphous model of fused silica is created using a two-step simulated annealing method with three-directional periodic boundary conditions. Variable loaded double scratches with different nanometer distances are simulated on the surface of the model, and variable loaded double scratch experiments with varying micron-sized distances between scratches are conducted for fused silica wafers. The simulation and experimental results reveal that the deformation of fused silica during nanoscale double scratching involves both elastic and plastic deformation, and the surface and subsurface damage primarily consists of radial, lateral, Hertzian, and median cracks. The distance between the double scratches affects the load variation, surface and subsurface crack propagation, extent of material damage and removal rate, and surface roughness. Examination of the material subsurfaces using the FIB-TEM sample preparation and testing technique shows that the distance between the double scratches also influences the subsurface damage to the material.

Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics

Nature has long inspired scientific and engineering advancements, particularly in the development of bioinspired ceramics. However, replicating nature's intricate structures through subtractive manufacturing techniques remains a significant challenge due to the limitations of precise and controlled material removal while maintaining structural integrity and complexity. This perspective article explores the transformative potential of machine learning (ML), particularly advancements in generative artificial intelligence (generative adversarial networks, transformer models) and multimodal learning, in accelerating the discovery of high‐performance bioinspired ceramics. ML offers an avenue to optimize material behavior beyond the constraints of traditional experimental methods. Recent advancements have shown ML's effectiveness in predicting mechanical properties and refining material designs, often surpassing conventional approaches. ML excels at identifying complex relationships even with incomplete data during training. The integration of cutting‐edge experimental data, cross‐scale simulations, and ML facilitates high‐fidelity multiscale modeling for predicting intricate phenomena like crack propagation paths in bioinspired ceramic structures. This article emphasizes the significant potential of ML to propel the field of bioinspired ceramics forward, paving the way for the discovery of ceramics with superior and tailored properties.

Synergetic Effect of Chemical Components in a Tungsten CMP Slurry and the Evolution of Tungsten Surface Species

Abstract A novel slurry containing 50 ppm Fe3+, 2 wt.% H2O2, 75 ppm oxalic acid, and abrasive nano-silica particles were utilized in a W chemical mechanical planarization process. Using this slurry, a W material removal rate of 710 Å/min and surface roughness of 1 nm were achieved. According to X-ray photoelectron spectroscopy data, surface W was first transformed to WO2 via its dissolution in H2O2, and then Fe3+ ions serving as a catalyst promoted the conversion of tungsten to WO3 through the WO2 intermediate in the presence of H2O2. Oxalic acid was added to coordinate with H2O2 and thus improve the slurry stability through a “wrapping” mechanism without decreasing the W material removal rate. Scanning electron microscopy and atomic force microscopy observations revealed that the W surface morphology changed first from coarse elongated grains to a discontinuous structure after the uneven oxidation by H2O2 and then to a wrinkled soft surface by Fe3+ and H2O2. Finally, it was ground with abrasive nano-silica particles to achieve a high degree of flatness.

Triple Effects of the Physicochemical Interaction between Water and Copper and Their Influence on Microcutting.

Water has been recognized in promoting material removal, traditionally ascribed to friction reduction and thermal dissipation. However, the physicochemical interactions between water and the workpiece have often been overlooked. This work sheds light on how the physicochemical interactions that occur between water (H2O) and copper (Cu) workpiece influence material deformations during the cutting process. ReaxFF molecular dynamics simulations were employed as the primary method to study the atomistic physical and chemical interactions between the applied medium and the workpiece. Upon contact with the Cu surface, H2O dissociated into OH- ions, H+ ions, and traces of O2- ions. The OH- and O2- ions chemically reacted with Cu to form bonds that weakened the Cu-Cu bonds by elongation, while the H+ ions gained electrons and diffused into the Cu lattice as H- ions. The weakening of surface Cu bonds promoted plastic deformation and reduced the difficulty of material removal. Meanwhile, further addition of H2O molecules saw a plateau in hydrolysis and more dominance of H2O physical adsorption on Cu, which weakens the elongation of Cu-Cu bonds. While the ideal case for atomic-scale material removal was found with an optimal number of 240 H2O molecules, the presented Cu material state with more H2O molecules could account for the observations in microcutting. The constricted nature of physical adsorption and hydrogen ion diffusion in the surface layer prevented the propagation of dislocations through the surface, which subsequently caused pinning points to be closer together during chip formation as observed by smaller chip fold widths on the microscale. Theoretical and experimental analysis identified the importance of accounting for physicochemical interactions between surface media and the workpiece when considering material deformations at micronanoscale.

Enhancement of acoustic cavitation streaming: A study on surface finishing of additively manufactured components

Due to the poor surface characteristics of additively manufactured parts, the necessity for post-process surface enhancement is crucial. Among the prevalent post-processing techniques, the acoustic cavitation-based surface finishing technique has recently emerged. Despite a considerable amount of focused research on the material removal mechanisms of this technique, less attention has been devoted to addressing its limitations associated with enhancing the process capability towards achieving a better surface finish. The driving force behind the acoustic cavitation technique is the bubble implosion through cavitation streaming, and the cessation of the acoustic cavitation streaming beyond a certain length is the main limitation. It has restrained the process capability towards finishing both external and internal surfaces. Hence, this research aims to unravel novel ways of employing the acoustic cavitation-generating parameters and achieving better-quality surface finishing of additively manufactured (AM) components. A study has been conducted on different AM materials, including Inconel 625 and aluminum alloy, by introducing various methods associated with acoustic amplitude, working mediums, temperature, and external vibration. The results reveal a significant reduction in average surface roughness for both materials. The topographical and morphological observations confirm the qualitative improvement on the surfaces. In addition, the conical bubble structures that frame the acoustic cavitation streaming are elucidated by implementing high-speed imaging techniques, and their enhancement at different parametric conditions is delineated. Henceforth, the findings suggest a notable insight into the potential of the employed approaches in enhancing the acoustic cavitation streaming for achieving a better surface finish of AM components.

Quartzites of the Khobeinskaya suite of the Subpolar Urals: Material composition, age limitations and possible sources of terrigenous material

Research subject. Quartzites that make up the ridge part of the ridge Rosomaha in the northern part of the Lyapinsky meganticlinorium in the Subpolar Urals. Material and methods. Detrital zircons were isolated from quartzites and their optical and isotope-geochronological U-Pb (LA-SF-ICP-MS) studies were performed. On the basis of chemical analyzes of rocks using indicator ratios and coefficients, the conditions for the formation of deposits were established. Results. The stratigraphic position of the quartzite ridge Rosomaha was determined. The time and conditions for the formation of the Khobeinskaya formation were specified. The role of polymetamorphic complexes of the Subpolar Urals as possible sources of terrigenous material removal during the formation of the Upper Precambrian section of the Subpolar Urals was estimated. Conclusions. It was established that the quartzites belong to the ridge Rosomaha to the Khobeinskaya formation, whose age is limited to the interval of 850–800 Ma (Inzersky level). It is shown that the crystalline complexes of Fennoscandia and the Central Russian orogen, as well as polymetamorphic complexes of the crystalline basement of the Timan-Severoural margin of the East European Platform, could be sources of terrigenous material.

SURFACE MORPHOLOGY OF SILICON NITRIDE (Si3N4)-TITANIUM NITRIDE (TiN) COMPOSITES USING GRA-RSM STRATEGY ENCOMPASSED WITH EDMed PARAMETERS

This investigation explores the application of electrical discharge machining (EDM) to ceramic composites constructed from Si3N4–TiN (Syalon 501) by testing both square and cylindrical electrodes. Various experimental methods have been employed, including design-of-experiments (DoE), Grey relational analysis (GRA), analysis of variance (ANOVA), confirmation testing, and scanning electron microscopy (SEM), in an effort to optimize machining settings and comprehend their effect on performance. While ANOVA revealed crucial parameter levels influencing overall machining conditions as measured by the grey relational grade (GRG), the sophisticated method of GRA considerably improved the machining characteristics. Significant improvements in the EDM process were shown experimentally, resulting in outstanding results for material removal rate (MRR), surface roughness (SR), and electrode wear rate (EWR). In particular, numerous benefits of the square electrode layout over the more common cylindrical arrangement stood out. All of the aforementioned resulted in an impressively high MRR (measured at 0.0281[Formula: see text]gm/min), a low EWR (at 0.0020[Formula: see text]gm/min), and a significant improvement in SR (at 0.3150[Formula: see text][Formula: see text]m). The GRG value was 0.0163 for the square electrode design, which was excellent, and 0.0025 for the cylindrical electrode, which was significantly better. The optimized parameters were successfully used, especially with the square electrode arrangement, leading to significant improvements in MRR and decreases in EWR. On the other hand, surface quality was negatively affected by larger parameter values, which increased the development of microfractures, particularly when using the square electrode design. In any case, our study provides strong proof that adjusted settings can greatly improve EDM performance, allowing for accurate machining of Si3N4–TiN composites with increased MRR, great surface texture, and reduced electrode wear. In conclusion, our study provides useful information to improve EDM procedures for Si3N4–TiN ceramic composites, as well as practical insights into increasing the efficiency and quality of EDM operations in a variety of industrial sectors.

Anisotropy Dependence of Material Deformation Mechanisms in Nanoscratching Monocrystalline BaF2: Experiments and Atomic Simulations.

Monocrystalline barium fluoride (BaF2), known for its exceptional optical properties in the infrared spectrum, exhibits anisotropy that influences surface quality and material removal efficiency during ultraprecision machining. This research explores the impact of anisotropy on the deformation and removal mechanisms of monocrystalline BaF2 by integrating nanoscratch tests with molecular dynamics (MD) simulations. Nanoscratch tests conducted on variously oriented monocrystalline BaF2 surfaces using a ramp loading mode facilitated the identification of surface cracks and a systematic description of material removal behaviors. This study elucidates the effect of crystal orientation on the ductile-brittle transition (DBT) of monocrystalline BaF2, further developing a critical depth prediction model for DBT on the (111) crystal plane to reveal the underlying anisotropy mechanisms. Moreover, nanofriction and wear behaviors in monocrystalline BaF2 are found to be predominantly influenced by scratch direction, crystal surface, and applied load, with the (110) and (100) planes showing pronounced frictional and wear anisotropy. A coefficient of friction model, accounting for the material's elastic recovery, establishes the intrinsic relationship between anisotropic friction and wear behaviors, the size effect, and scratch direction. Lastly, MD modeling of nanoscratched monocrystalline BaF2 reveals the diversity of dislocations and strain distributions along the (111) [-110] and [-1-12] crystal directions, offering atomic scale insights into the origins of BaF2 anisotropy. Thus, this study provides a theoretical foundation for the efficient processing of fluorine-based infrared optic materials exhibiting anisotropy.

Removal mechanism of double-diamond-abrasive-grinding GaN single crystals under graphene lubrication

Gallium nitride (GaN) is an advanced material used to manufacture chip wafers and high-power devices. Recently, grinding processing, has been applied in the fields of machinery manufacturing, aerospace, and medical devices as a highly efficient machining method. An in-depth understanding of the material removal mechanism produced by the double-grinding processes can provide guidance for the design of GaN-based nanodevices. Herein, molecular dynamics simulations were used to investigate the mechanism of removal of double-diamond-abrasive-grinding gallium nitride crystals under graphene lubrication, and a systematic study was performed to investigate the involved surface morphology, grinding force, stress distribution, and subsurface damage behavior. Results reveal that graphene can substantially enhance the wear resistance of GaN substrates by reducing surface wear, atomic displacement., potential energy, and subsurface damage, thereby playing a protective role toward the substrate. As the grinding depth increases, the grinding force and subsurface damage depth also increase. Furthermore, the effects of abrasive grain spacing on subsurface damage depth and phase change atoms were analyzed and found to have limited influence on material removal efficiency. These results deepen our understanding of material removal and protection mechanisms relative to substrates resulting from double-grinding processes as well as offer valuable insights for the rational design of abrasive wheels.

Development of optimum performance model during spark-eroded processing of rheocasted Al6061/Cenosphere MMCs

ABSTRACT In the present study, an improved wettability casting route was used to prepare lightweight structural materials. Using the compo casting process, an Al6061 alloy was created with cenosphere particles at various weight percentages (2, 4, 6, and 8 wt%). The molten aluminium slurry incorporated hollow alumina silicate particulates. X-ray diffraction (XRD) analysis of the aluminium matrix composites (AMCs) confirmed the presence of cenospheres without any intermetallic components. Further processing of the metal matrix composites (MMCs) was conducted using electric discharge machining (EDM) with a circular copper electrode. The EDM process parameters were controlled to measure response variables such as material removal rate (MRR), tool wear rate (TWR), and surface roughness (SR). The effects of different combinations of machining parameters – including pulse current, pulse-on time, reinforcement percentage, and flushing pressure – on these performance characteristics were observed. Experimental trials were designed using the face-centred central composite design (CCD) of the response surface methodology (RSM). Optimal process variable conditions led to significant improvements in surface finish. Additionally, an artificial neural network (ANN) model was used to determine the best conditions for EDM processing. The ANN model demonstrated a strong correlation coefficient of 0.99 between the predicted and experimental values of MRR, TWR, and SR.