International Journal of Material Forming最新文献

In the injection molding process, cooling efficiency and uniformity significantly influence product quality and cycle time. This paper presents a multi-objective optimization study aiming to minimize both molding time and maximum warpage through process parameter tuning, while comparing the performance of traditional and conformal cooling systems. Using Latin Hypercube Sampling, 15 process parameter sets were simulated in Moldflow. A radial basis function neural network was trained to model the relationship between process parameters and quality objectives, followed by particle swarm optimization to obtain Pareto fronts for both cooling systems. Experimental validation confirmed simulation accuracy with errors below 5%. The results show that through optimized process parameters, conformal cooling achieved a trade-off between warpage and molding time in the ranges of approximately 0.25 ~ 0.51 mm and 12.9 ~ 15.8 s, respectively. Compared to traditional cooling, the conformal system reduced maximum warpage by about 25% and molding time by 30% on average, thereby shortening the molding cycle and improving efficiency while enhancing product quality.

Complex sheet metal parts are manufactured through multi-stage plastic deformation processes. The geometric configuration design, feature recognition, and segmentation of these forming stages constitute a core challenge in intelligent die design. This demands systematic planning integrating material behavior, process constraints, and tool structure, thus necessitating precise geometric understanding of the part. To address this, we propose a spectral-graph-theory-based approach for analyzing forming-feature attributes. A topological model of geometric features is established to support optimal forming-stage geometry design. Beginning with the 3D surface model, elementary geometric features are extracted, and their mean curvatures are adopted as primary graph signals. A weighted Laplacian matrix is constructed using Gaussian kernel weights, with its eigen decomposition yielding the spectral graph representation of the part. Spectral clustering then partitions this graph into distinct subgraphs, each corresponding to an individual geometric forming feature. This facilitates the establishment of a topological structure graph for forming features, enabling robust feature recognition. Validation via recognition and design case studies demonstrate that the method efficiently translates geometric features into frequency-domain signals through mathematical modeling. This achieves effective feature extraction and classification, confirming its significant potential for advancing process design and manufacturing in sheet-metal forming.

This study reveals the fundamental microstructural and textural transformations that occur in high-purity copper after a single pass of Equal Channel Angular Pressing (ECAP). The main issue addressed is the lack of understanding regarding the onset of grain refinement and texture development during the early stage of severe plastic deformation (SPD) in face-centered cubic (FCC) metals. Contrary to the common focus on multi-pass processing, this work demonstrates that even a single ECAP pass induces significant microstructural reorganization. Transmission Electron Microscopy (TEM) and Electron Backscatter Diffraction (EBSD) analyses show the formation of dense dislocation networks, subgrains, and a notable increase in high-angle grain boundaries (HAGBs), indicating the transition from a coarse-grained to an ultrafine-grained (UFG) structure. X-ray diffraction pole figure analysis reveals a pronounced shear texture characterized by {111}<110 > and {112}<110 > components. These findings highlight that substantial structural and crystallographic changes can be initiated through minimal deformation. The innovation of this work lies in its demonstration that meaningful grain refinement and texture evolution begin at the very first stage of ECAP, offering valuable insights for designing SPD strategies to tailor material properties. This contribution forms a critical basis for optimizing ECAP-based processing routes in copper and similar FCC metals, even at the initial deformation step.

Low-alloy steel drill bits are commonly used in the mining industry for boring holes into rocks. They are characterized by high hardenability and a good combination of mechanical properties, with minimal additions of alloying elements. As product quality improves, the market becomes more competitive. Significant growth in the use of engineering development tools has also occurred, leading to improved performance in rock drilling, oil and mineral exploration, and the search for gemstones. Due to the constant cyclical mechanical stresses applied, the expected life of drill bits is often reduced by fatigue or mechanical wear, indicating that the market consistently requires the availability of new drill bits. This work aimed to demonstrate the suitability of hot forging as a substitute for machining to manufacture the specific profile of the drill bit preform used in rock drilling. A mining-industry partner selected AISI 8640 steel, as it is widely used for drilling applications. Tests were performed with AISI 8640 as a modeling material, and the results from the forging process were used to evaluate the punch movement and consequent metal flow, as well as the filling of the part’s cavity within the forging dies. The results obtained using Elementary Plasticity Theory (EPT) allowed verification of the physical experiment with AISI 8640 steel forged parts. Following this evaluation, numerical modeling was performed and compared with the hot forging process. Formation of the hollow cavity(sigma_b) within the part and the head of the preform in the same step was assessed. As a result of this optimized process, the reduction in the initial height of the billet and the preform formation were analyzed, with the finishing of the drill bit contingent upon the machining process. This hot forging demonstrated improved material utilization compared to the machining process, highlighting the benefits of deformation through simulations.

The production of aluminium strip involves a long sequence of thermomechanical processing steps that significantly influence the material’s mechanical properties and may induce anisotropy. This anisotropy can manifest as earing during deep drawing operations - such as those used in beverage can manufacturing - resulting in increased trimming scrap, process downtimes, and reduced economic viability. To assess formability and quantify earing, the cup drawing test is employed as a standard evaluation method. Understanding and minimizing earing formation requires comprehensive modelling of the entire process chain, which is traditionally performed manually by domain experts - a time-consuming, error-prone, and costly effort. This study presents a novel, scalable, and flexible approach to model a process chain by integrating production data with process models on the Microsoft Azure Databricks platform. The proposed method is validated on an industrial aluminium strip production line, demonstrating its capability to automate data processing, extract actionable insights, and support process optimisation. The approach successfully identifies an optimum processing route that minimises the earing integral, as determined by a dedicated evaluation function.

This paper studied the effect of energy density on the formability of the selective laser melting (SLM) 6063 aluminum alloy, and analyzed the density, surface quality, microstructure and mechanical property. In the SLM 6063 aluminum alloy, there were mainly two kinds of pore defects, i.e. non-fusion and pores. When the energy density was low (< 100 J/mm³), serious solidification crack defects existed in the specimen. With the increase of energy density, the crack defects in the specimen gradually improved. At the same time, the density generally showed a trend of first increasing and then decreasing. The energy density range of 66.67 ~ 100 J/mm³ was more conducive to the forming of high-density specimens (> 97%). The microhardness of the SLM 6063 aluminum alloy in each group was about 40 HV, which was less affected by process parameters. When the scanning speed was constant, with the increase of laser power, the tensile strength of the specimen first increased and then decreased, and the elongation first decreased and then increased. When the laser power was constant, the tensile strength of the specimen decreased sharply with the increase of scanning speed, and the elongation increased first and then decreased. Considering the density, crack defects and mechanical properties of the specimens under different process parameters, the laser power of 360 W, the scanning speed of 1000 mm/s, and the scanning spacing of 0.1 mm were identified as optimal process parameters, which can be used as a theoretical reference for the preparation of high-quality SLM aluminum alloy.

Aluminum alloy sheets are widely used in lightweight industries due to their excellent performance, but the springback defects in complex forming processes are difficult to predict and control precisely. In this paper, S600 high-strength aluminum was taken as the target. A method combining theoretical analysis, finite element simulation, and forming-process tests was adopted to develop the model. The multi-objective improved non-dominated sorting genetic algorithm was used to optimize the anisotropic yield criterion parameters of Yld2000-2D anisotropic yield criterion. Subsequently, a hybrid calibration strategy combining the multi-objective optimization algorithm and the inverse solution method was adopted to collaboratively optimize the parameters of the Chaboche hybrid strengthening model. And the springback simulation and forming test were conducted to verify the accuracy of springback prediction of the established constitutive models. For two-dimensional cylindrical surface and three-dimensional space complex surface, the maximum prediction deviations of the Yld2000-2D-Chaboche model have increased 24.3% and 12.7% respectively. For different stamping amounts (20 mm and 30 mm) of the C-shaped beam, the average errors were 0.2 mm and 0.06 mm respectively. This series of comparative verifications not only confirmed the accuracy of the optimized Yld2000-2D-Chaboche model, but also fully proved its wide applicability in complex forming processes.

Although extensive studies have been conducted to predict ductile fracture at room temperature, no attempt has been made to use Gurson–Tvergaard–Needleman (GTN) model to capture the effect of temperature due to spindle speed induced friction heat on damage accumulation in incremental sheet forming (ISF). In this work, the temperature effect is incorporated into a shear modified GTN model to characterise ductile fracture behaviour of an aluminium alloy (AA1050) at varying temperatures in ISF processing under different strain states. The correlation between void evolution and damage accumulation at different temperatures is revealed, and the void volume fraction (VVF) at different deformation stages is determined by conducting microscopic in-situ tensile test. By introducing a new temperature-dependent VVF function and determining appropriate GTN damage parameters, ductile fracture under different ISF processing temperatures is evaluated using FE simulation and validated by ISF experimental testing. The results show that the proposed temperature-dependent VVF function in GTN modelling is capable of predicting the ductile fracture of both the set temperatures in in-situ tensile tests and the varying temperature conditions in ISF processes. This study unveils the underlying mechanisms behind material deformation and damage evolution with consideration of temperature variations caused by tool spindle speed at various ISF forming conditions, which provides guidance for process optimisation and formability improvement in ISF process.

Variable wall-thickness tubes are increasingly required for lightweight, functionally optimized structures and heat-transfer components, yet conventional hollow sinking with a constant speed ratio between the feeding and drawing sides produces an almost uniform wall thickness along the tube axis and cannot generate a taper. This study proposes a simple hollow sinking process for fabricating variable wall-thickness microtubes without an inner tool by controlling the speed ratio between the feeding and drawing sides, that is, by increasing the drawing speed during processing while keeping the feeding speed at the die entrance constant. Austenitic stainless-steel (SUS304) tubes with an outer diameter of 2.0 mm, an inner diameter of 1.82 mm, and an initial wall thickness of 0.09 mm were drawn under these conditions, where the drawing speed on the exit side was continuously increased while the feeding speed was fixed. The resulting wall-thickness distributions and surface roughness were evaluated experimentally and by finite-element analysis, which consistently showed that the increasing speed ratio enhances the axial elongation per unit time beneath and just after the die, thereby geometrically introducing a taper slope on the inner wall. Using this method, tubes with a maximum wall-thickness difference of about 40% between thick and thin sections were fabricated while maintaining acceptable outer and inner surface quality. These results demonstrate that variable-thickness microtubes can be intentionally produced in hollow sinking through simple control of the speed ratio between the feeding and drawing sides, extending the conventional geometric framework for straight tubes to tapered tubes.

Zn-based alloys have attracted significant attention as potential candidates for biodegradable implants due to their excellent biocompatibility; however, their inherently low tribological performance continues to restrict practical applications. In the present study, a Zn1AgCuMg alloy was fabricated via induction melting–casting and subsequently processed through cold extrusion and equal channel angular pressing (ECAP) using various routes (A, C, R, Bc) and pass numbers (1–4). The processing resulted in substantial microstructural refinement, reducing the average grain size from 245 μm in the as-cast condition to 72 μm after ECAP Route-Bc with four passes, accompanied by an increase in hardness from 62 HV to 113 HV. The yield strength improved from 150 MPa (as-cast) to 164 MPa after extrusion, and further to 217 MPa following ECAP Route-Bc (four passes). Similarly, the corrosion rate decreased from 294 mpy in the untreated alloy to 232 mpy after extrusion and to 66.16 mpy after ECAP Route-Bc (four passes). Tribological assessment revealed negligible differences between extrusion and 1–2 pass ECAP samples; however, a marked enhancement in wear resistance was observed in the 3–4 pass ECAP conditions, with the lowest friction coefficient (0.083) achieved for ECAP Route-Bc (four passes). These results confirm that controlled severe plastic deformation via ECAP can concurrently improve mechanical strength, wear resistance, and corrosion resistance in Zn-based biodegradable alloys, with multi-pass ECAP Route-Bc offering the most balanced performance for prospective implant applications.