Journal of Manufacturing and Materials Processing

Encapsulation for wireless dairy-cattle implants must resist acidic, moisture-rich gastrointestinal conditions while remaining transparent to radio-frequency (RF) signals. This study evaluated vulcanized natural rubber (NR) latex as an intraruminal encapsulant, examining how total solid content (TSC; 30, 40, 50 wt%), stirring duration (24–72 h), and TiO₂ loading affect tensile and tear strength, acidic swelling, dip-coating thickness, and received signal strength indicator (RSSI) at 433 MHz. Multilayer dip-coating produced films 0.25–0.38 mm thick. Tensile strength rose with TSC and stirring (26.6 → 32.2 MPa), whereas tear strength peaked at 40 wt% (31.97 N mm⁻¹). Adding 5 phr (parts per hundred rubber) TiO₂ cut pH-4 swelling ~four-fold (21.1 → 5.25%) with a negligible RSSI penalty, and 3–5 coating layers kept the link well above the −120 dBm sensitivity floor over 5–55 m. The optimum—40 wt% TSC, 72 h stirring, 5 phr TiO₂—best balanced mechanical integrity, swelling resistance, thickness, and wireless performance. Vulcanized NR is therefore a promising bio-based encapsulant under simulated conditions; dielectric characterization, long-term aging, and in vivo validation remain future work. Full article

Bird strikes cause aircraft damage, create serious risks to human safety and can contribute to catastrophic incidents, while continuing to impose substantial economic costs on airlines. The impact combines high kinetic energy with discontinuous, strongly nonlinear contact over a short duration, producing large structural deformations; appropriate nonlinear simulation techniques are therefore required to capture this complex interaction. For this purpose, the present study applies established Smoothed Particle Hydrodynamics (SPH)–finite element modelling ingredients to a controlled matrix of aerospace material systems and target geometries. The approach is first benchmarked against a published aluminium flat-plate bird-impact test using a raster-digitised force-history comparison, after which monolithic metallic and composite structures and source-described honeycomb-sandwich alternatives are assessed in flat-panel and curved leading-edge configurations. The results show that contact-force and local-displacement rankings depend strongly on target geometry and response metric, with the curved leading edge changing the ordering observed for the flat panel. More compliant systems generally permit greater local displacement, whereas stiffer systems restrict displacement but can sustain higher short-duration force peaks; consequently, no universal material ranking follows from a single response measure, and the results are most suitable for preliminary design screening. Full article

The performance of Peltier-driven atmospheric water generation (AWG) systems depends strongly on the surface geometry and wetting behavior of the condensation structure. Triply periodic minimal surfaces (TPMS) provide high surface area-to-volume ratio and geometric tunability, but their effectiveness as three-dimensional condensation structures requires experimental evaluation. In this study, five additively manufactured TPMS geometries, Gyroid, Diamond, Lidinoid, SplitP, and Schwarz, were evaluated in a Peltier-driven AWG setup under controlled laboratory conditions. The measured water collection response varied among the tested TPMS geometries, which showed different condensation, retention, and collection trends. Water collection was measured with and without surface treatment, while the monitored surface temperature remained below the calculated dew point during testing. Without surface treatment, total water collection ranged from approximately 0.9 to 1.4 g, whereas surface-treated specimens collected approximately 0.6 to 1.2 g. The specimens with surface treatment exhibited predominantly discrete droplets rather than the film-wise morphology observed without surface treatment, but the total water collection did not increase consistently. Gyroid and Lidinoid showed slight increases with surface treatment, while SplitP, Diamond, and Schwarz showed reductions. Water collection also did not scale directly with calculated TPMS surface area, which suggests that effective air exposure, droplet retention, drainage, and coating uniformity contributed strongly to the observed performance. These findings provide experimental insights into additively manufactured TPMS geometry and surface treatment conditions for Peltier-driven AWG. Full article

Laser powder bed fusion (LPBF) is a disruptive additive manufacturing process for producing high-performance Inconel superalloy parts with complex shapes for the aerospace, energy, and other demanding industries. However, uniform part quality remains a persistent challenge, as process parameters, melt-pool dynamics, microstructural evolution, defect formation, and mechanical performance are closely coupled across a wide range of spatial and temporal scales. In previous reviews, these dimensions have been considered in isolation with limited insight into their interactions and implications for predictive process control. The present review aims to address this lacuna by proposing a unified Process–Structure–Property–Control (PSPC) framework for LPBF-produced Inconel 625, 718, and 738. The discussion begins with material attributes governing alloy processability, and then synthesises the melt-pool physics governing thermal behaviour, solidification, and energy transfer. Attention then turns to a critical assessment of grain evolution, defect formation, and process stability, showing how the thermal history governs microstructural development and, in turn, mechanical performance via linked process–structure–property relationships. Progress in multiscale numerical modelling, such as finite-element analysis, computational fluid dynamics, phase-field modelling, cellular automata, and phase-diagram calculation (CALPHAD), is reviewed to establish a comprehensive modelling ecosystem for predictive LPBF. The review also discusses the potential of emerging technologies, such as beam shaping, multi-laser processing, in situ monitoring, artificial intelligence, and powder recyclability, to increase the robustness and productivity of the process. Building on these advances, a digital-twin-enabled predictive-manufacturing framework that integrates physics-based models, data-driven algorithms, and real-time monitoring is introduced to enable closed-loop process optimisation. The review ends with a scientific synthesis and future research roadmap for intelligent, reliable, and autonomous LPBF of next-generation Inconel superalloys. Full article

Injection molding is a plastic material processing technique used in the polymer industry. Because it is a complex process that requires injection cycles to achieve the desired aesthetic quality in the molded parts, it is essential to evaluate and configure all process parameters to predict and reduce defects, thereby decreasing the processing time and energy consumption. This study presents the results of tests performed on molded HDPE parts, including modeling and simulation using ANSYS^® (2025 R1), a design of experiments (DOE), and 3D scanning of the molded parts. The study compares the behavior of defects (warpages and sink-marks) in molded parts using 3D scanning with the results obtained from coupled thermal-structural field finite element simulations. These simulations were performed using software to assess the residual thermal stress of the ejection phase. The results visually display information that helps designers and engineers in the polymer processing sector evaluate molding-process failures using different software. Full article

The environmental impact of technical systems is becoming increasingly important. Particularly in mechanical engineering, with its high demands on process stability and product quality, environmentally beneficial materials such as wood, with its heterogeneous and anisotropic structure, present challenges. Therefore, understanding the cutting process and the cutting forces is of great importance. This publication builds upon an established cutting force model and presents experiments to determine the specific cutting force (k_c0.5) and normal cutting force (k_cN0.5) for birch plywood. Furthermore, the influence of the rake angle (K_{γ_c} and K_{γ_cN}) and the cutting speed (K_vc and K_vc) on the cutting forces is investigated. These correction factors are integrated into the established cutting model and verified under the assumption of no relevant directional dependence of the cutting forces due to the fibers of the plywood under investigation at the macroscopic level. The correction factors were determined based on the experiments and show a high degree of agreement with experimentally measured values. The correction factors lead to an increase in accuracy of predicting cutting forces during the peripheral milling of birch plywood. The model enables the prediction of cutting force with an average 30% increase in accuracy compared to the reference model. The results thus allow for a more accurate description of the cutting forces, from which important insights can be derived in the future for optimizing the cutting process and the tool, as well as for addressing tool wear and process quality. Full article

Wafer-edge uniformity is a critical issue in plasma etching because local variations in ion bombardment can directly affect the etch profile and process yield. Ion transport near the wafer-edge is strongly influenced by the sheath formed around the boundary between the wafer and the focus ring. Although focus ring geometry, dielectric properties, and applied voltage conditions can all modify this local sheath, their respective roles in controlling ion incidence angle and energy have not been clearly distinguished. In this study, two-dimensional particle-in-cell Monte Carlo collision simulations were performed for an argon capacitively coupled plasma to compare the effects of focus-ring height, electrode-to-focus-ring gap width, dielectric permittivity, and applied voltage conditions. The electrical conditions included a single-frequency waveform and a pulsed dual-frequency waveform with a variation in the low-frequency (LF) voltage amplitude. Geometric changes in focus-ring height and gap width modify the local sheath contour and ion acceleration direction, leading to more pronounced changes in the ion incidence angle than those caused by dielectric permittivity. The ion energy, however, is more strongly influenced by the applied voltage condition, particularly the LF voltage amplitude. These findings provide fundamental insights into wafer-edge ion control, although their quantitative applicability to reactive and electronegative etching remains to be verified. Full article

Small-scale clay-brick yards require molding equipment that increases output while remaining mobile, locally serviceable, and compatible with intermittent material supply. This article documents the functional architecture and exploratory operational performance of the mobile 12-cavity hydraulic clay-brick molding machine (ML12). Its design contribution is the integration of a dimensioned wheeled steel chassis, seated paired-lever controls, a translating feed hopper/distributor, a 12-cavity mold, two vertical hydraulic actuators, and a water-spray cleaning subsystem in a four-stage operating cycle. A retrospective concept-appraisal matrix compares this architecture with fixed automated and mobile manual concepts; equal weighting and one-at-a-time ±25% weight variations preserve the ML12’s highest internal score, without establishing stakeholder preference or empirical superiority. The evidence base also comprises sequential daily production logs: ten days of traditional manual molding followed by ten days of ML12-assisted molding. Mean gross green-brick output was 720 ± 86 bricks/day in the traditional period and 1495 ± 16 bricks/day in the ML12 period; corresponding descriptive throughputs were 86.5 and 186.9 bricks/h. A rejection-rate sensitivity analysis shows that, if traditional production had no rejects, ML12 conforming output would equal the traditional gross mean at a 51.8% ML12 rejection rate; this quantity boundary is not an estimate of quality or economic break-even. A preliminary linear-static finite-element case for a reconstructed frame returned a maximum von Mises stress of 112.3 MPa, 1.82 mm resultant displacement, and a minimum elastic safety factor of 2.23 on the reported medium mesh; the result is limited to the specified 1.0 kN load case and is not structural certification of the complete machine. Because the operational comparison was non-randomized and did not control staffing, operators, clay batch, moisture, weather, energy use, or rejection rate, the observed difference cannot be attributed exclusively to the machine. The results establish the machine architecture, an operational signal, and a bounded preliminary frame response, but not brick quality, ergonomic benefit, full structural safety, environmental benefit, or commercial return. Full article

Surface topography plays a critical role in the functional performance of machined freeform components, yet its assessment traditionally takes place only after manufacturing. This work presents a simulation-assisted framework for predicting the surface topography generated during freeform ball-end milling and using these predictions to support machining-strategy selection. Three finishing strategies (3-axis square, SQ3, 3-axis spiral, SP3, and 5-axis spiral, SP5) were investigated on a representative freeform benchmark by combining high-resolution UVRMAP simulations with experimental topography measurements. Surface signatures were characterized using ISO 25178 areal parameters together with two- and one-dimensional Fast Fourier Transform (FFT) analyses, enabling quantitative evaluation of surface amplitude, preferential orientations, anisotropy, and characteristic spatial periodicities. The results demonstrate that machining strategy and local surface geometry produce distinctive topographical signatures that cannot be fully described by conventional roughness parameters alone.Theproposed UVRMAP methodology accurately reproduces the primary spatial organization of the geometric texture generated by the programmed toolpath, while the incorporation of a controlled non-ideal cutter-edge representation improves the prediction of experimentally observed fine-scale features. The combined experimental–simulation methodology provides a robust framework for comparing and validating the spatial and morphological characteristics of predicted surface topographies, providing a basis for future machining-strategy selection according to application-specific surface requirements. Full article

The present research investigates the optimization of ball burnishing (BB) process parameters to create regular lubricating grooves on multilayer connecting rod liners to prevent engine seizure. The study utilized a Taguchi L9 fractional orthogonal array to evaluate the impact of ball diameter, deforming force, and feed rate on the resulting groove widths. Statistical analysis (ANOVA) revealed that ball diameter is the primary driver of groove width variation, exhibiting a non-linear parabolic relationship where the diameter serves as a stabilizing threshold. While deformation force showed a steady linear progression in widening traces, higher feed rates were found to restrict localized plastic flow, resulting in narrower groove widths. For the bimetallic structure (steel back with AlSn20Cu coating), the research recommends tailoring forces to the specific layer—forces for the anti-friction layer and for the substrate to avoid structural destruction. Profilometry confirmed that the height of edge inflows directly correlates with groove depth, ranging from 6 to 30 μm. The optimized non-linear regression model developed in this study achieved an exceptionally high coefficient of determination (R² = 99.84%), ensuring precise predictive accuracy. Overall, these findings provide a robust framework for researchers to enhance the durability of heavy-duty engine components through controlled surface topography. Full article

Optical surface deviations in ophthalmic optics arise from fast tool servo errors, the tool footprint, freeform surface residuals, and the freeform surface curvature responses across processing stages. In this paper, a PAM-Net physics–AI dual-driven compensation control method is presented for addressing the issues in dynamically accurate positioning of a diamond cutting tool via the fast tool servo using existing methods, e.g., struggling to characterize micrometer-scale CNC following-up errors, spatial surface-form perturbations, and S/C optical quality simultaneously. PAM-Net maps Z-axis position, velocity, acceleration, jerk, and A/B-axis phases to surface-form residuals and S/C deviations through tool-lens projection and curvature-mediated optical-response operators, while jointly estimating uncertainty and safety risk for constrained NC compensation. The framework also preserves an interpretable mediation chain from servo dynamics to final optical quality. On holdout-35, removing acceleration/jerk increased RMSE from 0.512 to 5.395 μm, indicating strong predictive dependence on high-order servo dynamics. Closed-loop validation increased the strict ±0.12 D pass rate from 72.5% to 87.5%, alongside reduced surface-form and curvature residuals. These results indicate that learning-based compensation control for high-precision freeform-optics manufacturing requires joint consideration of prediction accuracy, physical interpretability, executable NC write-back, and manufacturing constraints. Full article

Dissimilar friction stir welding (FSW) of titanium alloys offers a route to spatially optimized aerospace structures, but the asymmetric thermomechanical environment produces heterogeneous microstructures and textures whose interaction with mechanical performance is not well characterized. A near-α/α+β combination of titanium alloys, Ti–6242 SG (advancing side, ADV) and Ti–54M (retreating side, RET), was welded across a matrix of rotation speeds (225–325 rpm) and traverse speeds (100–150 mm·min⁻¹), spanning rotation-to-traverse-speed ratios N/v of 1.80–2.75, which was used throughout as an empirical processing index that orders the conditions of this matrix rather than as a measure of specific heat input. Microstructure, phase identification, relative diffracted-intensity trends, and crystallographic textures were characterized by 2D-XRD at three cross-section locations (ADV, weld nugget center [CEN], RET) and correlated with transverse tensile properties and fracture locations. Partial pole figures were plotted in the simple-shear reference frame with ideal-orientation overlays, intensities in multiples of a random distribution (m.r.d.). The CEN develops the strongest textures, dominated by a basal {002}_α component (20–31 m.r.d.) with poles near the normal direction; this concentration lies away from the ideal shear fiber loci and is more readily explained by orientation inheritance during the β→α transformation on cooling than by direct shear, although unambiguous identification of variant selection would require orientation-resolved measurements. The RET develops {101}_α and {100}_α pole concentrations clustering near the ideal P-fiber loci, consistent with deformation-related texture development, intensifying with both rotation and traverse speed. The ADV shows mixed textures varying non-monotonically with parameters. Two conditions of nearly identical N/v obtained from different parameter combinations (225 rpm/125 mm·min⁻¹ and 275 rpm/150 mm·min⁻¹) nevertheless develop measurably different streak morphologies, microstructures, textures, and tensile responses, showing directly that N/v orders but does not determine the thermomechanical state. Yield strength is uniform (≈900–940 MPa) across the full matrix, consistent with a Schmid-factor estimate in which the basal-near-ND CEN texture gives a very low resolved shear stress on basal systems under transverse loading; joint efficiencies reach ≈90–96%. Ductility, in contrast, tracks consolidation quality rather than texture severity: fracture strain rises almost monotonically with N/v, from ≈0.6–1.4% at N/v ≈ 1.8 (defect-driven, erratic failure) to ≈5.4–6.0% at N/v = 2.60, despite the latter condition carrying the strongest RET pyramidal texture. Full-field strain measurement shows the weld nugget to carry the lowest strain and the highest apparent stiffness of any zone in every condition for which the load record is reliable, with strain accumulating on the advancing side. Consolidated conditions fracture on the advancing side where deformation concentrates, whereas the lowest N/v and longest-exposure conditions fracture in the nugget center; all fracture surfaces are ductile, with the crack path following continuous α layers at prior-β grain boundaries. A favorable processing range within the investigated parameter matrix is N/v ≈ 2.2–2.6, with the best overall combination at 325 rpm and 125 mm·min⁻¹ (N/v = 2.60: UTS ≈ 1010 MPa, ≈5.4–6.0% elongation). Within the parameter range examined here, consolidation quality is the first-order design variable for this dissimilar system, with the zonal texture architecture setting the yield strength level. Full article

Multi-objective optimization has become an indispensable tool for solving engineering design and manufacturing problems involving multiple conflicting objectives. This paper presents a novel parameter-less multi-objective optimization (MOO) framework that combines the strengths of evolutionary MOO techniques with the parameter-free search philosophy of the Jaya and Rao algorithms. The proposed framework incorporates non-dominated sorting, elite archiving, and crowding-distance mechanisms to achieve an effective balance between convergence and diversity while eliminating the need for algorithm-specific control parameters. The proposed framework is first validated on sixteen widely used unconstrained benchmark problems comprising five ZDT, seven DTLZ, two IDTLZ, and two SDTLZ test suites using the maximum number of function evaluations reported in the literature. Its performance is evaluated using five widely accepted quality indicators, namely Generational Distance (GD), Inverted Generational Distance (IGD), Hypervolume (HV), Spacing (SP), and Spread (SD). The benchmark results demonstrate that the proposed framework produces competitive Pareto-optimal fronts and exhibits excellent convergence, diversity, and solution distribution compared with several state-of-the-art evolutionary multi-objective optimization algorithms. The practical applicability of the proposed framework is demonstrated through five representative manufacturing optimization problems involving Selective Laser Melting, Microwave Hybrid Heating, Sustainable Machining, Wire Electrical Discharge Machining, and Wire Arc Additive Manufacturing. These case studies encompass additive, thermal, subtractive, and many-objective manufacturing optimization problems with conflicting performance measures. The generated Pareto-optimal solutions are subsequently ranked using the recently developed BHARAT (Best Holistic Adaptable Ranking of Attributes Technique) multi-attribute decision-making method to identify the most suitable compromise solutions. The obtained results demonstrate that the proposed parameter-less MOO framework provides a simple approach with competitive convergence, diversity, and decision-support capabilities for complex manufacturing optimization problems. Full article

An active vibration-based methodology for structural health monitoring of polymer-matrix composites is presented, in which piezoelectric actuators excite resonant vibrations and the diagnostic information is carried by two nonlinear characteristics: the backbone curve and the amplitude-dependent logarithmic decrement. Both are described by a single elastoplastic model of the Iwan (microplasticity) type with a power-law distribution of yield thresholds. The two characteristics share a common power-law exponent, and the model predicts a parameter-free ratio between the modulus defect and the hysteretic intensity. The four parameters are identified by a joint Bayesian fit. The methodology is applied to two carbon-fiber-reinforced polymer objects: a cantilever beam with a symmetric stacking sequence (three modes, 87 to 1431 Hz) and a plate strip with an unsymmetric one (two modes near 34 and 203 Hz), each tested intact and after controlled local damage. The measured ratio reproduces the prediction within 4 to 12%; whereas, the fundamental plate mode reveals a non-frictional, matrix-dominated dissipation. Local damage increases the hysteretic intensity 1.4 to 2.3 times and the modulus defect up to 2.7 times, while the resonant frequency changes by less than 0.8% and the background decrement remains nearly unchanged, giving a compact damage signature with minimal baseline requirements. Full article

Geometric deviations in unsupported overhang features pose one of the most persistent quality challenges in Laser Powder Bed Fusion (LPBF), where even small deviations from the intended geometry can undermine part functionality and reliability. This study presents a geometrically informed conditional Generative Adversarial Network (cGAN), implemented through the Pix2Pix framework, to predict layer-wise geometric deviations in LPBF-printed parts with overhang geometries, using paired two-dimensional Computer-Aided Design (2D CAD) slices and corresponding X-ray Computed Tomography (XCT)-derived ground truth slices. The study investigates how geometric information can be encoded within the conditional input of the Pix2Pix framework to more effectively guide deviation prediction. A total of 18 models were trained and evaluated across multiple overhang geometry groups and batch size configurations, assessed through a combination of perceptual, structural, and boundary-focused metrics, namely Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), Learned Perceptual Image Patch Similarity (LPIPS), Fréchet Inception Distance (FID), and Edge Intersection over Union (Edge IoU). The results demonstrated that color-coded inputs consistently improved prediction fidelity, perceptual similarity, and edge alignment relative to their non-color-coded counterparts. Furthermore, a model trained on a balanced multi-geometry dataset showed improved prediction performance on withheld 30° and 60° overhang configurations within the benchmark geometry family. The proposed framework offers a data-driven, design-stage tool for anticipating geometry-dependent deviations in LPBF overhang structures, supporting design for additive manufacturing. Full article

Auxetic polymers offer a route to deformation-activated sealing by transforming axial deformation into lateral expansion, enabling controlled conformity and retention within perforated structures. This paper presents the design-space-guided optimisation of a multi-material polymeric auxetic plug for mechanically activated sealing of circular perforation surrogates relevant to military ground-vehicle structures using a controlled thin-wall surrogate validation framework. The sealing combines an SLA-printed Elastic 50A photopolymer auxetic body with TPU 95A load-transfer and priming components. A parameterised re-entrant unit cell was optimised using response-surface design of experiments coupled with nonlinear finite-element analysis. The optimised geometry, with a height of 6 mm, length of 5 mm, strut thickness of 1.25 mm, and re-entrant angle of 31°, achieved a predicted negative Poisson’s ratio of −2.66 under 20% axial strain. Experimental validation using additively manufactured unit cells confirmed the intended auxetic deformation response. The optimised structure was then integrated into a multi-material plug and tested against a solid polymer benchmark, achieving sealing to approximately 22 kPa with improved anchoring across the tested 22–25 mm perforation range. The results establish a mechanism-driven pathway from polymer auxetic unit-cell optimisation to plug-level pressure-sealing performance, demonstrating the potential of multi-material auxetic architectures as deformation-activated sealing systems for temporary repair of perforated military ground-vehicle structures. Full article

Titanium alloy thin-walled parts are widely used in the aerospace industry because of their excellent high-temperature performance. However, their low structural stiffness and poor machinability often result in substantial machining deformation and severe tool wear, thereby reducing machining accuracy and surface quality. To address these issues, an accurate method is proposed for predicting cutting force and force-induced deformation in the end milling of titanium alloy thin-walled parts while considering tool wear and material removal. First, a cutting force model incorporating tool wear is established to characterize the influence of tool wear on milling forces during titanium alloy machining. Subsequently, a force-induced deformation model is developed based on small-deflection theory to describe the deformation response of the flexible workpiece under milling loads. Furthermore, an iterative strategy is proposed to predict the coupled evolution of cutting force and force-induced deformation during successive material removal. In this strategy, the element stiffness matrix is updated at different feed positions according to the evolving material removal state, while the effects of workpiece deformation on the actual cutting state are incorporated into the cutting force calculation. This provides a framework for accurately predicting cutting force and force-induced deformation. Multilayer end-milling experiments were conducted for validation. The average peak-value errors of Fy and Fz were 7.8% and 5.5% for the new tool and 5.9% and 6.1% for the tool with VB = 0.05 mm, respectively, while the corresponding average deformation prediction errors were 11.8% and 14.5%. These results demonstrate the accuracy of the proposed method. Full article