Influence of process parameters on glass fibre-reinforced polymers manufactured through high pressure resin transfer moulding

Influence of processing parameters on the electrical conductivity of 8YSZ electrolytes fabricated via tape casting

Ceramic Matrix Composites (CMCs) are materials in which ceramics are reinforced with fibers or other materials, providing enhanced functionalities, such as damage tolerance, in addition to their inherent heat resistance. This study investigates a manufacturing method for continuous alumina-mullite fiber-reinforced alumina CMCs using a commercial Fused Deposition Modeling (FDM) 3D printer, demonstrating a flexible and practical route for continuous fiber-reinforced CMC fabrication. The process utilizes a pre-impregnated filament, which serves as the fundamental component for depositing both the ceramic matrix and continuous reinforcement. The 3D printing filament was fabricated by melting a mixture of alumina, serving as the matrix material, and a thermoplastic resin to impregnate the alumina-mullite mixed fibers. Filaments with a diameter of 0.4 mm exhibited fewer cracks compared to those with a diameter of 0.6 mm. Moreover, a filament with fewer voids was produced when the heating temperature during impregnation was 230 °C. Using the fabricated filament, simple three-layered rectangular test specimens, with a length of 110 mm and a width of 10 mm, were successfully printed. A tensile strength of approximately 250 MPa was achieved along the fiber direction. The observed fracture behavior indicates that improving the interlaminar strength would likely further enhance the tensile strength. The impact of this research is introducing a new manufacturing method that will expand the design freedom and accessibility of complex-shaped CMCs. This pioneering achievement provides a foundational baseline for researchers and engineers to transition 3D printed continuous fiber-reinforced CMCs from laboratory-scale prototypes to structural components.

Agricultural waste accumulation presents significant environmental challenges, including greenhouse gas emissions and ecological degradation. Microwave-assisted pyrolysis (MAP) has emerged as a superior thermochemical strategy to valorise these residues into high-value biochar-based materials. Compared to conventional pyrolysis (CP), MAP provides unique advantages such as volumetric heating and precise structural control, enabling the synthesis of advanced carbon forms including biochar-derived graphene oxide (GO). This review systematically evaluates the fundamental mechanisms of MAP, emphasizing the influence of biomass composition and process parameters on the physicochemical properties of the resulting carbon. We highlight how MAP facilitates the fine-tuning of porosity, graphitization, and surface functionality, which are critical for high-end applications. Specifically, the review discusses the integration of these materials into additive manufacturing and their role as high-performance electrode modifiers in electrochemical sensors. A significant focus is placed on the emerging application of biochar-based coatings in providing anti-biofouling properties, which enhance the durability and efficiency of surfaces in marine and biomedical environments. Furthermore, we address technical bottlenecks in upscaling MAP and propose future research directions, such as optimizing process atmospheres to support a circular bioeconomy. This review provides a comprehensive roadmap for transforming agricultural waste into functional carbon materials with diverse industrial applications. ● MAP offers fast, low-energy routes to value-added carbon materials. ● MAP conditions tune biochar porosity, graphitization, and surface functionality. ● Biochar and derived carbons enable composites, coatings, and sensing applications. ● Upscaling challenges and process limitations of MAP are critically assessed. ● Future directions include atmosphere control and underexplored MAP parameters.

Fundamental analysis of the effects of tool and process parameter variations in shear-clinching of multi-layer sheet metal joints

This study investigates the influence of process parameters on the mechanical and thermal behaviour of dissimilar AA6061-T6, and AA5083-H12 aluminium alloy joints fabricated by conventional friction stir welding (CFSW) and underwater friction stir welding (UFSW). The combined effects of tool rotational speed and welding speed were analyzed using the response surface methodology (RSM), and the developed quadratic models showed excellent agreement with the experimental results ( R 2 at 95%). The response surfaces for tensile strength (TS) and percentage elongation (PE) exhibited clear parabolic trends, with both responses increasing up to an optimum combination of 1120 rpm and 63 mm/min, beyond which they decreased due to excessive heat input and softening. Under these optimal parameters, the UFSW joint achieved a maximum TS of 196 MPa and PE of 9.8%, which were approximately 11.4% and 6.5% higher, respectively, than those of the corresponding CFSW joint. The underwater environment reduced the peak temperature by about 15–20% and increased nugget hardness by 6 to 8%, indicating improved heat management and microstructural refinement. The integrated RSM analysis confirmed a strong thermal mechanical correlation between process parameters, temperature control, hardness distribution, and weld performance.

Influence of Process Parameters on Mechanical and Tribological Behavior of Direct Metal Laser Sintering-Fabricated SS316L Using Taguchi–Grey Relational Approach

Conventional fusion welding of aluminum pipes often leads to defects such as root cracking, thermal distortion, and lack of proper fusion. To address these issues, a dedicated friction stirs welding (FSW) setup along with a specially designed tool was developed for joining aluminum pipes. In this study, the influence of key process parameters, including tool rotational speed, traverse speed, and axial force, on weld quality and mechanical performance was investigated. The welded joints were evaluated using tensile testing, micro-Vickers hardness measurements, and visual inspection techniques. The results show that both tool design and process parameters play a significant role in determining weld quality. With properly selected parameters, improved mechanical properties and better weld integrity can be achieved.

Influence of process parameters on microstructure–property relationships in additive friction stir deposition of Ti-6Al-4V

Purifying ⁶⁰Co-containing low-level radioactive wastewater via electro-deionization with zirconium phosphate ion-exchange resins.

Research on the influence of low-frequency vibration-assisted bone drilling process parameters on surface quality and screw stability

Abstract In recent years, laser powder bed fusion (L-PBF) has become an interesting method for producing metal components with complex shapes. However, L-PBF can lead to defects like porosity, affecting the quality and reliability of the final components. This study investigates the structural defects and relative density of AISI 316L stainless steel with 2.5 wt.% Cu fabricated via L-PBF under varying processing parameters. The relative density of the samples was evaluated using a combination of optical microscopy (OM), Archimedes density method, and x-ray computed tomography (XCT), allowing for a comprehensive analysis of defect morphology, including pore size, shape, and distribution. The primary objective of this research is to compare the accuracy and effectiveness of these three density measurement methods, which have not been widely compared for this specific alloy. The results show differences between the methods, with XCT providing a 3D perspective of porosity, OM providing detailed 2D surface analysis, and the Archimedes method being sensitive to surface defects and cracks. These findings highlight the importance of selecting appropriate measurement techniques for evaluating the quality of additive manufacturing parts and highlight the influence of processing parameters on defect formation and density.

The article focuses on the application of additive technologies in the design and manufacturing of aviation structural elements under modern requirements for strength, weight reduction, reliability, and economic efficiency. The goal of the study is to develop and substantiate an integrated analytical approach to optimizing additive manufacturing processes in aircraft production. The tasks addressed include: analyzing of current additive technologies in aerospace engineering; developing mathematical models of thermomechanical processes and porosity formation; optimizing of printing parameters and material composition; and conducting a comparative evaluation of traditional and additive manufacturing methods. The methods employed comprise the finite element method, thermomechanical and porosity modeling, multi-criteria optimization, and experimental investigation of the mechanical properties of metallic and polymer materials. The following results were obtained: mathematical models for predicting thermal deformation, structural heterogeneity, and strength characteristics were developed; the influence of process parameters on microstructure formation and defect minimization was determined; it was established that the optimization of printing parameters reduces material consumption by up to 30%, decreases product weight by 10–25%, reduces production time by a factor of 2–3, and lowers costs by up to 40%. A tensile strength of up to 1260 MPa was achieved for SLM-manufactured titanium components. In addition, the proposed integrated modeling approach enabled quantitative prediction of porosity levels and residual stress distribution, improving dimensional accuracy and structural reliability of critical aviation components. Comparative analysis confirmed that additive technologies demonstrate the highest efficiency in manufacturing geometrically complex and weight-critical parts, where traditional methods are limited in design flexibility and material utilization efficiency. Conclusions. The scientific novelty lies in the development of an integrated modeling and optimization framework for the additive manufacturing of aviation components, ensuring improved structural integrity, reduced defect levels, enhanced production efficiency, and increased competitiveness in aviation manufacturing.

Metal additive manufacturing faces challenges in directly fabricating end-use components due to the poor surface quality. Plasma electrolytic polishing (PEP) is an efficient and environmentally friendly surface treatment technology, demonstrating significant potential to enhance the surface quality of additively manufactured metal components. In this study, the surface characteristics of additively manufactured 316L stainless steel polished by PEP, including surface morphology, chemical composition, and wettability, are systematically investigated. First, the influence of key processing parameters, such as polishing time, voltage, electrolyte temperature, and concentration, on surface roughness was comprehensively examined through a series of experiments. The surface roughness was significantly reduced from 10.479 μm to 2.195 μm by using an optimized parameter combination: a polishing voltage of 300 V, an electrolyte concentration of 3%, an electrolyte temperature of 75°C, and a polishing time of 30 min. Then, surface characteristics of specimens treated with optimized PEP process parameters were studied and compared with those of as-fabricated specimens. Results showed that defects on the surface of as-fabricated specimens, such as adhered powders and oxides, were effectively removed by PEP. In addition, PEP can significantly improve the wettability of the specimens, with the contact angle decreasing from 80.9° to 39.4°. This study provides a comprehensive analysis of the characteristics of PEP of additively manufactured 316L stainless steel, indicating its potential for post-processing applications.

This study investigates the influence of design factors and key process parameters—including explosive welding (EXW), rolling, and laser processing—on the formation, microstructure, and tribological properties of Ti–Cu–Ni intermetallic coatings. A combined manufacturing approach was employed, starting with the EXW of an MN19 cupronickel alloy to a VT1-0 titanium substrate, followed by multi-pass rolling to achieve a cladding thickness of approximately 0.3 mm. Subsequently, laser surface remelting was performed to facilitate controlled mass transfer and homogenization within the reaction zone. Numerical simulation using COMSOL Multiphysics v. 5.4 was utilized to optimize the thermal cycles and determine the ideal energy density (42 J/mm2) for phase formation. The results demonstrate that the primary structural components of the coatings produced under optimal conditions are solid solutions based on the ternary-modified titanium cuprides Ti2Cu(Ni) and TiCu(Ni). The transition from a layered bimetal to a finely dispersed intermetallic structure significantly enhances the surface characteristics. This specific phase composition provides a sustained microhardness of ~5 GPa across the coating cross-section. Comparative wear tests against fixed abrasive revealed that the wear resistance of the Ti–Cu–Ni coatings is 2.5 times higher at room temperature and 1.5 times higher at 600 °C than that of the base VT1-0 titanium.

ABSTRACT Radio-frequency coaxial connectors, widely used in communication base stations and radars, are assembled from precision components with perforated structures. During hole machining, burrs will form at the inlet and outlet, which can affect assembly performance. However, traditional deburring is time-consuming and urgently requires efficient technology. This article focuses on an efficient electrochemical process for removing burrs at the edges of small-sized holes in precision workpieces, with emphasis on the design of the process device and parameter optimization. The design of an array-type process device has enabled synchronous, efficient deburring of multiple workpieces. The parameters of the flow distribution chamber and interelectrode gap were determined through flow field and electric field simulations, and a back pressure plate was designed to improve the uniformity of electrolyte flow in the machining zone. Subsequently, the influence of process parameters on deburring was analyzed, and the optimal parameter combination was determined using response surface methodology. The rationality of the process device and the effectiveness of the process parameters were ultimately verified through experiments.

The Fused Filament Fabrication (FFF) process has established itself as a key technology in prototyping and development and has garnered increasing interest in academic research. A substantial body of research on the FFF process has focused on the influence of process parameters on the resultant material/part properties. The thermal history of the printed part has proven itself as one of the most important factors in the printing process. It influences warping behavior, dimensional accuracy, build plate adhesion, as well as the mechanical properties of the finished part. A key requirement for understanding the influence of thermal history is the knowledge of the thermal properties of the considered material. In this study, the temperature-dependent thermal properties (isobaric heat capacity, thermal conductivity and density) of an unfilled polyamide 6 material for 3D printing are provided. Special attention is given to discussing the challenges associated with measuring these properties, particularly regarding how well the measured values represent the actual conditions during the printing process.

Container machining plays a key role in the finishing of workpieces. The aim of this article was to compare the effectiveness of vibratory and high-speed rotational machining. Mass loss and selected changes in surface geometric structure parameters were assessed. To obtain a porous structure, the samples were prepared by sandblasting. The novelty of this work is the use of high rotational speeds for rotational machining and the use of a planned experiment to limit the number of samples. The innovative nature of the comparison of vibratory and high-speed rotational machining allowed the development of mathematical models of the influence of process parameters on the final results. A two-factor planned experiment with five levels of process variables was used to investigate a wide range of process input variables. Based on the RSM response surface, mathematical models of changes in mass losses MRR, arithmetic mean surface roughness Ra, maximum height of the highest elevation (peak) of the roughness profile Rp, and surface skewness Ssk as a function of input parameters were developed. Working containers with a volume of 25 dm3 were used for the tests, and the test material was samples made of PA38/EN AW 6060 aluminum. Studies have shown that, for similar machining times, greater MRR changes were achieved with rotary machining. Rotary machining using the same machining media and similar machining times was characterized by up to 15% greater MRR than vibratory machining after 75 min of container machining. The reason for this high efficiency is the use of high rotational speeds. Comparing the effectiveness of reducing surface geometric structure parameters between rotational and vibration machining processes depends primarily on the machining time. The work proves that the use of rotational machining and high rotational speeds allows for shorter machining times compared to vibration machining.

Arc-driven powder bed fusion represents a low-cost alternative to beam-based powder bed systems, yet the morphological stability regimes governing single-track formation and the relative influence of process parameters on regime transitions have not been systematically characterised. Manual visual assessment of track morphology is inherently subjective and cannot objectively quantify the parameter hierarchy governing stability boundaries. This study addresses both limitations through two complementary contributions. A deterministic two-stage image-based framework is developed to automatically classify single-track morphology from top-view images of solidified 316L stainless steel tracks, replacing subjective assessment with a reproducible, intervention-free procedure. A gap-based continuity criterion distinguishes discontinuous from continuous melt paths; for continuous tracks, the coefficient of variation in width (CV (coefficient of variation) < 0.15) further separates geometrically stable from transitional morphologies. Building on the image-derived regime labels, two interpretable classifiers—a depth-limited Decision Tree (DT) and a regularised Logistic Regression (LR) —are fitted using applied current, scanning speed, and electrode-to-powder-bed distance as predictors. The classifiers are employed not for predictive generalisation but to extract standardised coefficients and permutation-based feature importance rankings, yielding a model-agnostic, quantitative explanation of which process parameters govern regime transitions. Stable continuous tracks are obtained only within a restricted parameter window. Permutation importance consistently ranks applied current as the dominant predictor, followed by electrode distance and scanning speed, in agreement with the thermophysical interpretation. Logistic Regression coefficients confirm that reduced stand-off distance is a necessary condition for sufficient arc constriction. Supplementary linear regression models indicate that applied current governs melt pool depth, whereas scanning speed is the primary determinant of width variation. The combined framework establishes a reproducible basis for process parameter hierarchy analysis in arc-driven powder bed systems and provides a foundation for regression-based process optimisation.

Forming morphology prediction of self-piercing riveted joints under the influence of complex process parameters based on deep learning