Search Results (559)

The seeding technique is the only way to precisely control the crystal orientation of single-crystal superalloy castings. However, an inevitable assembly gap exists between the seed and the mold cavity in practice, whose role in defect formation remains insufficiently understood. To elucidate the mechanism and impact of this gap, superalloy seeds were machined to different extents, aiming to create varying gaps with the mold. After the seeding experiment, the chilled layers formed on the perimeter of the pre-processed seeds were detected, exhibiting two distinct microstructural zones: a eutectic aggregation region at the bottom and an equiaxed grain at the top. The thicker the layer, the more pronounced the differences in microstructure between these two regions. This can be explained by the fact that during preheating, the γ/γ′ eutectic-rich interdendritic region (enriched with Al + Ti + Ta) in the original seed melted first due to its lower melting point. The molten fluid flowed downward into the gap, solidifying rapidly into the chilled layer. The leading portion of the fluid, melting from the interdendritic zone, formed the eutectic zone in the lower part of the chilled layer. The subsequently poured charge alloy melt (non-enriched with Al + Ti + Ta) generated the upper equiaxed zone with only a little γ/γ′ eutectic. These equiaxed grains in the chilled layer subsequently grew upward and potentially developed into stray grains of the casting. Full article

In order to determine the causes of crack defects in Mn18Cr2 high-manganese wear-resistant steel plates, this paper conducted a systematic analysis of the steel plates’ microstructure, chemical composition, and hardness via metallographic microscopy, field-emission scanning electron microscopy, and Vickers hardness tester. The results indicated that there were folded cracks on the surface of the steel plate. The interior of the cracks was oxidized, and inclusions were observed in the crack gaps. A significant difference in the contents of Mn and Cr elements was detected at the defect locations, indicating that very obvious long-range diffusion of Mn and Cr elements had occurred during long-term high-temperature oxidation. The crack defects on the surface of the steel plate were related to the inheritance of the original cracks on the surface of the cast billet before rolling. There were cracks on the surface of the cast billet; the oxide scale and inclusions inside the cracks had not been completely removed. Multiple passes of rolling led to the cracks and oxide scale being pressed into the steel surface, thereby forming folding defects. The fine grain strengthening and deformation twinning generated by rolling deformation formed the hardened layer on the surface, resulting in higher surface hardness than core hardness. The austenite grain size inside the steel plate was in the range of 23–30 μm, and the hardness was around 275 HV. The grain size near the surface of the steel plate was around 10 μm. The surface hardness was 351 HV, which was higher than the core hardness of the steel plate. Full article

Porosity formation due to solidification shrinkage and inadequate liquid metal feeding during the casting of Sn-0.3Ag-0.7Cu (SAC0307) is a critical issue that impairs quality and subsequent processing. However, the opacity of the casting process often obscures the quantitative relationships between process parameters and defect formation, creating a significant barrier to science-based optimization. To address this, the present study utilizes finite element method (FEM) analysis to systematically investigate the influence of pouring temperature (PCT, 290–390 °C) and interfacial heat transfer coefficient (HTC, 900–5000 W/(m²·K)) on this phenomenon. The results reveal that PCT exerts a non-monotonic effect on porosity by modulating the solidification mode, which governs the accumulation of dispersed microporosity. In contrast, HTC plays a critical role in determining porosity morphology by controlling both the solidification rate and mode. Consequently, an optimal processing window was identified at 350 °C PCT and 3000 W/(m²·K) HTC, which significantly enhances interdendritic feeding and improves the ingot’s internal soundness. The efficacy of these optimized parameters was experimentally validated through macro- and microstructural characterization. This work not only elucidates the governing mechanisms of solidification quality but also demonstrates the value of numerical simulation for process optimization, offering a reliable scientific basis for the industrial production of high-quality SAC0307 alloys. Full article

This work focused on the development of eco-friendly bio-composites based on polylactic acid (PLA) and sugarcane bagasse (SCB) as a natural fiber from Moroccan vegetable waste. First, the fiber surface was treated with an alkaline solution to remove non-cellulosic components. Then, the composite materials with various amounts of treated sugarcane bagasse (TSCB) were fabricated using two routes, melt processing and solvent casting. The primary objective was to achieve high fiber dispersion/distribution and homogeneous bio-composites. The dispersion properties were analyzed using scanning electron microscopy (SEM). Subsequently, the thermal, mechanical, and melt shear rheological properties of the obtained PLA-based bio-composites were investigated. Through a comparative approach between the dispersion state of fillers with extrusion/injection molding and solvent casting method, the work aimed to identify the most suitable processing route for producing PLA-based composites with optimal dispersion, improved thermal stability, and mechanical reinforcement. The results support the potential of TSCB fibers as an effective bio-based additive for PLA filament production, paving the way for the development of eco-friendly and high-performance materials designed for 3D printing applications. Since the solvent-based route did not allow further improvement and presents clear limitations for large-scale or industrial implementation, the transition toward 3D printing became a natural progression in this work. Material extrusion offers several decisive advantages, notably the ability to preserve the original morphology of the fibers due to the moderate thermo-mechanical stresses involved, and the possibility of manufacturing complex geometries that cannot be obtained through conventional injection molding. Although some printing defects may occur during layer deposition, the mechanical properties obtained through 3D printing remain promising and demonstrate the relevance of this approach. Full article

The Southwire Continuous Rod (SCR) process is widely used for producing low-oxygen copper rods, yet pore defects remain a significant challenge, affecting the performance and drawability of copper wire. In this study, the influence of casting speed on solidification behavior and porosity formation in low-oxygen copper casting rods was investigated by combining numerical simulation and plant trials. The simulation results indicate that increasing the casting speed elevates the flow velocity and impact depth of molten copper in the casting wheel. Simultaneously, higher casting speeds could raise the temperature of the casting rod and extend the liquid phase region, which suppresses the precipitation of dissolved gases from the melt. However, when the casting speed exceeds 26 t/h, the center temperature of the casting rod at the outlet remains close to the melting point of copper, retaining 10–20% liquid fraction. This predisposes the rod to remelting and the formation of remelt holes, and thus it fails to meet the design requirement for complete solidification of the SCR technology. Further industrial trials confirm that a casting speed of 23 t/h is optimal under current process conditions, yielding the lowest size and number of porosity defects in the casting rod. Full article

Obtaining a good casting surface without defects requires proper preparation of the mould for the given metal alloy. It is important to select the appropriate moulding sand, which consists of a grain matrix and a binder. Due to the temperature and dynamics of the poured alloy, it is also important to apply a suitably selected protective coating to the surface of the mould. Depending on its chemical composition, the carrier used (water or alcohol), and the method of application, it is possible to create the most favourable conditions for obtaining a flawless casting. This article presents the impact of various protective coatings applied to moulding sand on a chromite matrix, comparing their technological parameters and selecting the best one for the given application conditions. During commonly used tests on moulding sand with a protective coating, its permeability, abrasion, and adhesion were determined. To verify the results obtained, microscopic photographs of the prepared surface layers of the moulding sand with a protective coating were also taken. It was found that, despite the same viscosity, the same carrier, and the same application method, the quality of the protective coating is determined by its appropriate composition developed by the manufacturers. The permeability of P^u moulding blocks after coating was found to be significantly reduced, from 255 to 37 [×10⁻⁸ m²/Pa × s]. The use of protective coatings significantly increased the moulding sand’s abrasion resistance, reducing the loss value from 0.826% to 0.330% for the weakest coating. In the group of protective coatings tested, the coating marked PC1M in the tests had the highest adhesion N_p and its value, depending on the application method, ranged from 0.30 MPa to 0.37 MPa. Full article

Improved plasticity in superalloy castings minimizes processing defects, reduces stress concentration, and enhances mechanical performance. To obtain the microstructure–plasticity relationship, GH4065A ingots were homogenized at 1140–1200 °C for 5–80 h. Microstructural analysis tracked the evolution of dendritic crystals and precipitates (including η phase, carbides, and borides). Tensile tests were conducted to assess plasticity in terms of elongation and reduction in area. Results show that increasing temperature accelerated dendritic dissolution. While 1140 °C was ineffective for short-term dendrite elimination, temperatures of 1160–1200 °C achieved near-complete dissolution within 30–60 h. Precipitates evolution was also observed: the η phase dissolved preferentially, while the sizes of carbides and borides gradually decreased, especially at 1200 °C. Electron probe microanalysis confirmed Nb as the most segregated element. With higher temperatures, Nb diffused from microsegregated zones toward homogeneity. Plasticity improved notably when the Nb segregation coefficient was ~1.5 but decreased at ~1. The optimal homogenization parameters were determined as 1180 °C for 15–60 h. This study provides key processing guidelines for GH4065A ingots, supporting enhanced service performance and operational safety of related components. Full article

X-ray-based non-destructive testing technology plays a crucial role in the quality monitoring of aluminum alloy wheel hubs. Due to the characteristics of the casting process, wheel hub images often exhibit low contrast and a discrete distribution of defect edges. Existing methods often face problems such as poor feature extraction capability, low efficiency of cross-scale information fusion, and susceptibility to interference from complex backgrounds when detecting such defects. Therefore, this study proposes an innovative detection framework for defects in aluminum alloy wheel hubs. The model employs data preprocessing to enhance the quality of original images; integrates an asymmetric pinwheel-shaped convolution (PConv) with an efficient receptive field, enabling efficient focus on the edge feature information of discrete defects; innovatively constructs a Mamba-based two-stage feature pyramid network (MFDPN), which improves the network’s defect localization capability in complex scenarios via a secondary focusing-diffusion mechanism; and incorporates a channel and spatial attention block (CASAB), strengthening the model’s ability to resist interference from complex backgrounds. On our self-built wheel hub defect dataset, the proposed model outperforms the baseline by 7.2% in mAP50 and 5% in Recall at 39 FPS inference speed, thus validating its high practical utility for automated aluminum alloy wheel hub defect detection. Full article

Multi-material Directed Energy Deposition (DED) Additive Manufacturing (AM) processes enable the integration of different material properties into a single structure, addressing the requirements of various applications and working environments. Laser-based Directed Energy Deposition (DED-LB) has been employed in the past for surface coatings as well as for the repair and repurposing of high-value industrial components, with the goal of extending product lifetime without relying on expensive and time-consuming manufacturing from scratch. While powder DED-LB has traditionally been used for multi-material AM, the more resource-efficient and cost-effective wire DED-LB process is now being explored as a solution for creating hybrid materials. This work focuses on the critical aspects of implementing multi-material DED-LB, specifically defining an optimal operating process window that ensures the best quality and performance of the final parts. By investigating the possibility of combining stainless steel and nickel-based alloys, this study seeks to unlock new possibilities for the repair and optimization of naval components, ultimately improving operational efficiency and reducing downtime for critical naval equipment. The analysis of the experimental results has revealed strong compatibility of stainless steel 316 with Inconel 718 and stainless steel 17-4PH, while the gray cast iron forms acceptable fusion only with stainless steel 17-4PH. Finally, during the experimental phase, substrate pre-heating and process monitoring with thermocouples will be employed to manage and assess heat distribution in the working area, ensuring defect-free material joining. Full article

Continuous casting is a key core link in steel production with characteristics of strong nonlinearity, multi-parameter coupling and dynamic fluctuations under working conditions. Traditional experience-dependent or mechanism-driven models are no longer suitable for the high-quality and high-efficiency production demands of modern steel industries. Machine learning provides an effective technical path for solving the complex control problems in the continuous casting process through its powerful data mining and pattern recognition capabilities. This paper systematically reviews the research progress of machine learning applications in the field of continuous casting, focusing on three core scenarios: abnormal prediction, quality defect detection and process parameter optimization. It sorts out the evolution from single models to feature optimization and integration, deep learning hybrid models, and mechanism-data dual-driven models. It summarizes the significant achievements of this technology in reducing production risks and improving the stability of cast billet quality, and it analyzes the prominent challenges currently faced such as data distortion and distribution imbalance, insufficient model interpretability and limited cross-scenario generalization ability. Finally, it looks forward to future technological innovation and application expansion directions, providing theoretical support and technical references for the digital and intelligent transformation of the steel industry. Full article

Flexible packaging often consists of multilayer films that combine different materials to achieve high barrier performance, but these structures are incompatible with current recycling technologies. Polyolefins such as polypropylene (PP) offer more recyclable alternatives but require additional oxygen-barrier materials that do not compromise recyclability. This study investigates the influence of ethylene vinyl alcohol (EVOH), Ormocer^® barrier coating, and PP labels with different adhesives on PP recyclability. Recyclates were produced using twin-screw extruder to simulate the recycling process and then injection-molding to make tensile test specimens. Mechanical properties, melt flow rate (MFR), oxygen induction time (OIT), and odor were evaluated. Findings showed that low label content (5–12.5%) has minimal impact on recyclate quality. The addition of 10% EVOH increased the elastic modulus of PP granulate and cast-PP (cPP) film by 26% and 14%, respectively, and improved oxidation stability by 9%, while reducing cPP film impact strength by 77%. Ormocer^® decreased mechanical performance, particularly elongation at break (−18%), likely due to defect-inducing particles, but had limited influence on MFR. Labels and Ormocer^® also introduced odor variations. Overall, the findings indicate that EVOH up to 10% and labels up to 12.5% yield promising results, providing guidance for designing recyclable, monomaterial packaging. Full article

Central segregation, a typical internal defect in continuous casting slabs, significantly deteriorates the mechanical properties of steel products. However, traditional manual defect evaluation methods rely heavily on experience, are highly subjective and inefficient, making it difficult to meet the quality assessment requirements of today’s high-end steel materials. In this study, an approach which combines an unsupervised image enhancement algorithm and Otsu algorithm analysis was proposed to achieve automatic recognition and quantitative features extracting of central segregation in continuous casting slabs. The challenges posed by insufficient brightness and low contrast in central segregation images were addressed using unsupervised image enhancement algorithms. Following this enhancement, batch objective quantification of the segregation images was conducted through Otsu processing. Comparative experimental results showed that the enhanced images yielded an average Dice Similarity Coefficient of 0.965 for segregation recognition, representing a 38% improvement over unprocessed images, with consistent accuracy gains across complex segregation scenarios. This intelligent detection method eliminates the need for manually labeling a training set, substantially improves the consistency of segregation quantification and reduces the time cost significantly. Consequently, multiple parameters can be employed to quantify segregation characteristics, offering a more comprehensive and precise approach than current simplified rating methods. This advancement holds promise for enhancing quality control in steel processing and advancing Artificial Intelligence-driven technological progress within the metallurgical sector. Full article

Quality assurance in aluminum die casting is critical, as internal defects—such as porosity—can compromise structural integrity and significantly reduce component service life. In the cost-sensitive manufacturing environment of Germany, early and automated rejection of defective parts is essential to minimize scrap, rework, and energy waste. This study investigates the feasibility and performance of deep learning for automated defect detection in industrial X-ray images of two series-production aluminum die-cast components. A systematic methodology was employed: first, candidate object-detection frameworks (YOLOv5 vs. Faster R-CNN) were evaluated under real-time constraints (<2 s per image) on standard industrial hardware; subsequently, position-specific and single global models were trained on annotated datasets. A systematic hyperparameter study—focusing on input resolution, learning rate, and loss weights—was conducted to optimize accuracy and robustness. The best-performing models achieved F1-scores up to 0.87, with position-specific models outperforming the single global model on average. The approach was validated under real production conditions at Hengst SE (Nordwalde), demonstrating practical feasibility, strong acceptance among quality professionals, and significant potential to accelerate inspections and standardize decision-making. The results confirm that deep learning is a viable alternative to rule-based image processing and holds substantial promise for automating X-ray inspection workflows in aluminum die casting, contributing to both operational efficiency and sustainability goals. Full article

This study investigates the use of steel and cast iron for producing cast furnace rolls to replace welded rolls, which often fail from cracks and limited durability. Casting had not been previously considered by the manufacturer, but rising demands for durability and quality make it a promising alternative. Material selection focused on mechanical properties, wear resistance, and production costs. To ensure casting quality, Magmasoft 6.0 software was applied for detailed simulation of casting, solidification, and cooling. Results showed that steel alloys (GS-34CrMo4 and GS-20Mn5) are prone to shrinkage and porosity, which cannot be fully avoided even with feeders. In contrast, GJS-500-7 cast iron exhibited low shrinkage tendency and minimal defects, proving suitable for production while reducing costs. It also offers lower weight and efficient metal use, improving cost-effectiveness. Detected defects were concentrated in the central casting area, where they have little impact on functionality. Based on sixteen simulations, GJS-500-7 cast iron emerged as the most suitable material for furnace rolls thanks to its thermal resistance, castability, low porosity, and ability to meet required specifications. This process optimization represents an efficient, cost-effective choice, improving final product quality and creating new opportunities for the manufacturer. Full article

Polysulfone (PSF), despite its excellent thermal and mechanical stability, exhibits moderate gas separation performance and poor compatibility with inorganic fillers, resulting in interfacial voids and structural defects. This study addressed these limitations by incorporating vinyltrimethoxysilane (VTMS)-functionalized TiO₂ nanoparticles into PSF matrix to develop mixed matrix membranes (MMMs) for selective CO₂/N₂ separation. Membranes with 1–5 wt.% VTMS@TiO₂ loadings were fabricated via solution casting, and their gas separation performance was systematically evaluated. VTMS modification enhanced the dispersion and interfacial adhesion of TiO₂ within the PSF matrix, as confirmed by SEM, FTIR, XRD, and TGA analyses. The 4 wt.% VTMS@TiO₂ loaded membrane showed optimal performance, with a CO₂ permeability of 8.48 barrer and a CO₂/N₂ selectivity of 26.50 due to stronger polymer–filler interactions and enhanced CO₂ affinity by VTMS functional groups. This membrane has shown stable transport behavior and favorable CO₂ selectivity as confirmed by pressure- and temperature-dependent permeation studies. Robeson plot analysis showed that the optimized membrane approached the upper bound, demonstrating a significant improvement over pure PSF. The study confirmed that VTMS-functionalized TiO₂ enhanced both permeability and selectivity through improved filler dispersion, interfacial integrity, and CO₂ affinity. Full article