Search Results (132)

The article presents a comprehensive review of key issues and challenges related to enhancing the durability of hot forging tools. It discusses modern strategies aimed at increasing tool life, including modifications to tool materials, heat treatment, surface engineering, tool and die design, die geometry, tribological conditions, and lubrication. The review is based on extensive literature data, including recent publications and the authors’ own research, which has been implemented under industrial conditions at the modern forging facility in Forge Plant “Glinik” (Poland). The study introduces original design and technological solutions, such as an innovative concept for manufacturing forging dies from alloy structural steels with welded impressions, replacing traditional hot-work tool steel dies. It also proposes a zonal hardfacing approach, which involves applying welds with different chemical compositions to specific surface zones of the die impressions, selected according to the dominant wear mechanisms in each zone. General guidelines for selecting hardfacing material compositions are also provided. Additionally, the article presents technological processes for die production and regeneration. The importance and application of computer simulations of forging processes are emphasized, particularly in predicting wear mechanisms and intensity, as well as in optimizing tool and forging geometry. Full article

This study investigates the influence of die design parameters on forging forces and thermomechanical responses during near-solidus forging (NSF) of complex steel components. Finite element simulations using Forge NxT analyzed six die configurations varying geometry orientation, gating system design (conical, cylindrical, curvilinear), and draft angles (20° and 30°), with 42CrMo4E steel modeled at 1360 °C. Key responses including punch and lateral forces, temperature distribution, strain localization, and die stress were evaluated to assess design effects. Results showed that the gating system geometry critically controls material flow and load requirements. The conical gating design with a 30° draft angle yielded the lowest punch (141.54 t) and lateral (149.44 t) forces, alongside uniform temperature and strain distributions, which improve product quality by minimizing defects and incomplete filling. Lower lateral forces also reduce die opening risk, enhancing die life. In contrast, the base case with a 20° draft angle exhibited higher forces and uneven strain, increasing die stress and compromising part quality. These findings highlight the importance of selecting appropriate gating systems and draft angles to reduce forming loads, increase die life, and improve uniform material flow, contributing to better understanding of die design in NSF of complex steel components. Full article

Innovative approaches in hot forging, such as the use of floating dies, which aim to minimise burr formation by controlling material flow, require precise management of die geometry distortions. These distortions, primarily caused by thermal gradients, must be tightly controlled to prevent malfunctions during production. This study introduces a comprehensive thermal analysis framework that captures the complete forging cycle—from billet transfer and die closure to forging, spray-cooling, and lubrication. Two advanced heat transfer models were developed: a pressure- and lubrication-dependent contact heat transfer model and a spray-cooling model that simulates fluid dispersion over die surfaces. These models were implemented within the finite element software FORGE-NxT to evaluate the thermal behaviour of dies under realistic operating conditions. These two new models, contact and spray-cooling, implemented within a full-cycle thermal simulation and validated with industrial thermal imaging data, represent a novel contribution. The simulation results showed an average temperature deviation of just 5.8%, demonstrating the predictive reliability of this approach. This validated framework enables accurate estimation of thermal fields in the dies, and offers a practical tool for optimising process parameters, reducing burr formation, and extending die life. Moreover, its structure and methodology can be adapted to various hot forging applications where thermal control is critical to ensuring part quality and process efficiency. Full article

During the service life of automotive panel stamping dies, the surface is often subjected to high loads and repeated friction, resulting in excessive wear. This leads to die failure, reduced machining accuracy, and decreased production efficiency. To enhance the anti-friction and wear-resistant performance of die steel surfaces, this study introduces the concept of biomimetic engineering in surface science. By mimicking microstructural configurations found in nature with outstanding wear resistance, biomimetic functional surfaces were designed and fabricated. Specifically, quadrilateral dimples inspired by the back of dung beetles, pentagonal scales from armadillo skin, and hexagonal scales from the belly of desert vipers were selected as biological prototypes. These surface textures were fabricated on Cr12MoV die steel using high-speed ball-end milling. Finite element simulations and dry sliding wear tests were conducted to systematically investigate the tribological behavior of surfaces with different dimple geometries. The results showed that the quadrilateral dimple surface derived from the dung beetle exhibited the best performance in reducing friction and wear. Furthermore, the milling parameters for this surface were optimized using response surface methodology. After optimization, the friction coefficient was reduced by 21.3%, and the wear volume decreased by 38.6% compared to a smooth surface. This study confirms the feasibility of fabricating biomimetic functional surfaces via high-speed ball-end milling and establishes an integrated surface engineering approach combining biomimetic design, efficient manufacturing, and parameter optimization. The results provide both theoretical and methodological support for improving the service life and surface performance of large automotive panel dies. Full article

In recent decades, the automotive industry has faced challenges around improving energy efficiency, reducing pollutant emissions, increasing occupant safety, and reducing production costs. To solve these challenges, it is necessary to reduce the weight of vehicle bodies. In this way, the steel industry has developed more efficient metal alloys. To combine vehicle mass reduction with improved performance in deformations in cases of impact, a new family of advanced steels is present, AHSS (Advanced High-Strength Steels). However, this family of steels has lower formability and greater springback compared to conventional steels; if it is not properly controlled, it will directly affect the accuracy of the product and its quality. Different regions of a stamped component, such as the flange, the body wall, and the punch pole, are subjected to different states of stress and deformation, determined by numerous process variables, such as friction/lubrication and tool geometry, in addition to blank holder force and drawbead geometry, which induce the material to different deformation modes. Thus, it is understood that the degree of work hardening in each of these regions can be evaluated by grain morphology and material hardening, defining critical regions of embrittlement that, consequently, will affect the material’s stampability. This work aims to study the formability of the cold-formed DP600 steel sheets in the die radius region using a Modified Nakazima test, varying drawbead geometry, followed by a nanohardness evaluation and material characterization through the electron backscatter diffraction (EBSD). The main objective is to analyze the work hardening in the critical blank regions by applying these techniques. The nanoindentation evaluations were consistent in die radius and demonstrated the hardening influence, proving that the circular drawbead presented the most uniform hardness variation along the profile of the stamped blank and presented lower hardness values in relation to the other geometries, concluding that the drawbead attenuates this variation, contributing to better sheet formability, which corroborates the Forming Limit Curve results. Full article

The forging industry has increasingly emphasised quality and reproducibility, making computer simulations essential for predicting and improving the process. A major challenge in cold upset forging is billet buckling, which leads to defective products. Existing numerical models, such as the Euler and Rankine-Gordon formulas, mainly focus on elastic buckling. This study aimed to develop a numerical model that defined inelastic buckling during forging, particularly in cold upset forging, which could be used to determine the buckled billets and their stresses, identify the deflection point for different billet geometries, and specify the optimum billet geometry for aluminium. A numerical approach was used to model the forging operation and obtain simulation data for stress variation against die strokes. Seven billet geometries (10–40 mm in diameter, each with a length of 120 mm) and three frictional conditions (µ = 0.12, 0.16, and 0.35) were applied. The simulation results showed that the billet geometry and the strain hardening exponent had a crucial impact on the buckling behaviour, while friction seemed to alter the overall billet stresses. Rigorous non-linear regression and iterations showed that the numerical model successfully estimated the buckling stresses but failed to identify the buckling points through stress differences. Full article

This study presents the design and performance evaluation of a custom extrusion die for producing grass-cutting lines from high-density polyethylene (HDPE) with twist angles of 0°, 15°, 30°, and 45°. The mechanical properties, cutting efficiency, and energy consumption of the HDPE lines were compared with those of commercially available nylon lines with round and square profiles. The die successfully produced twisted HDPE lines with consistent geometry. Although the HDPE lines exhibited lower tensile strength than their nylon counterparts, due to inherent material differences and residual stress from twisting, they demonstrated comparable elastic modulus values. Importantly, HDPE lines require significantly less energy during processing, offering a cost-effective and environmentally friendly alternative. Cutting tests showed that the 45° twisted HDPE line achieved cutting performance comparable to the square-profile nylon line and surpassed the round-profile variant. These results highlight the potential of HDPE as a viable, energy-efficient material for grass-cutting applications, particularly when optimized through geometric design. Full article

Accurate preform design in forging processes is critical for improving part quality, conserving material, reducing manufacturing costs, and eliminating secondary operations. This paper presents a finite element (FE) simulation-based methodology for preform design aimed at achieving flashless and near-flashless forging. The approach leverages material point backtracking within FE models to generate physics-informed preform geometries that capture complex material flow, die geometry interactions, and thermal gradients. An iterative scheme combining backtracking, surface reconstruction, and point-cloud solid modeling was developed and applied to several three-dimensional forging case studies, including a cross-joint and a three-lobe drive hub. The methodology demonstrated significant reductions in flash formation, particularly in parts that traditionally exhibit severe flash under conventional forging. Beyond supporting the development of new flashless forging sequences, the method also offers a framework for modifying preforms during production to minimize waste and for diagnosing preform defects linked to variability in frictional conditions, die temperatures, or material properties. Future integration of the proposed method with design of experiments (DOE) and surrogate modeling techniques could further enhance its applicability by optimizing preform designs within a localized design space. The findings suggest that this approach provides a practical and powerful tool for advancing both new and existing forging production lines toward higher efficiency and sustainability. Full article

The paper presents the results of FEM computer simulations of the drawing process on a cylindrical journal of thin-walled CuSn8 alloy tubes. This study demonstrates through FEM simulations that the drawing angle significantly affects the state of stress, strain and tool wear. Regardless of the geometry of the drawing die, greater wear was noted for the cylindrical plug. Increasing the angle of drawing die 2α from 6° to 38° contributed to a slight 5% increase in wear of the drawing dies and more than 80% increase in plug wear. Accelerated tool wear at high angles is to be associated with higher pipe pressures on the drawing die and plug. Inadequate selection of drawing geometry can cause additional material deformation effort and material fracture in the industrial drawing process of thin-walled tubes. After the drawing process, these tubes may also show non-uniform wall thickness. The optimum drawing angle for thin-walled tubes is 2α = 22°, for which about a 10% decrease in the drawing force was recorded. Full article

An environmentally friendly alternative to phosphate-based lubrication was studied through the lateral cold extrusion forging of internal gears using pulsating motion. A die set with a removable punch enabled a detailed observation of relubrication, forming load, material flow, and gear geometry. Pulsating motion with liquid lubricant significantly reduced the forming load during punch penetration, while no such effect was observed under dry conditions. Even when the number of pulses (n) was set to 1, relubrication occurred, and a comparable load reduction to that of n = 3 was achieved, shortening the forming time. When n = 3, pulsating motion contributed to increased gear height and reduced separated burr formation; however, it also caused slightly incomplete tooth filling, which may be undesirable for precision applications. Varying the pulse start position from 5.50 mm to 13.30 mm influenced forming load and material flow, further affecting gear geometry. During punch extraction, the presence of liquid lubricant reduced the load and suppressed material displacement, while dry conditions led to higher extraction loads and more deformation. Full article

This paper advances the forward extrusion process by integrating sustainable methodologies and optimizing energy efficiency. This research investigates the impact of die geometry and elongation coefficients on energy usage and process efficiency, employing finite element method (FEM) simulations alongside empirical analysis. Artificial neural networks and experimental data were utilized to predict process energy. The experimental study utilized flat, conical, and arc-shaped dies to extrude lead profiles exhibiting different elongation coefficients. The study analyzed the dynamics of material flow, energy requirements, and maximum forces. Patterns of deformation, distribution of tension, and losses of energy were discerned, with finite element models enhancing understanding of these phenomena. The mathematical framework forecasting the peak extrusion force in relation to elongation parameters was substantiated via residual diagnostics and regression analysis. The findings indicate that conical and arc dies can conserve up to 15% of the energy in comparison to flat dies, thereby improving material flow and reducing deformation forces. This comprehensive strategy provides practical solutions to reduce energy consumption and improve metal forming processes, thereby enhancing industrial efficiency and sustainability. The results not only benefit industry but also align with environmental objectives, thereby increasing the efficiency and sustainability of extrusion operations. Full article

Die-sinking Electrical Discharge Machining (EDM) is a manufacturing process for fabricating complex geometries in challenging applications. However, its energy-intensive nature and complex parameter interactions pose challenges in balancing productivity, sustainability, and electrode wear. This study presents a comprehensive analysis of energy consumption and electrode degradation in EDM. Utilizing an advanced experimental setup with real-time energy monitoring, this study investigated the trade-off between machining parameters, energy efficiency, and electrode wear. The study employed a simple and standardized electrode geometry and varied EDM parameters, such as discharge current and pulse duration. The obtained results clearly demonstrated that optimizing EDM machining parameters, particularly discharge current, significantly influenced machining efficiency and electrode wear. Specifically, employing high-current settings of 140 A substantially reduced the total machining time from approximately 33 h (at conservative settings of 40 A) down to around 3.5 h, achieving nearly a tenfold improvement. Moreover, it also led to a reduction in specific energy consumption (SEC), decreasing from 0.81 Wh/mm³ at the low current (40 A) to 0.19 Wh/mm³ at the higher current (140 A), underscoring a definitive inverse relationship between discharge current and energy consumption. The study outcomes provide practical guidelines for enhancing the operational efficiency and sustainability of EDM in advanced manufacturing sectors. Full article

This work presents a novel fully automated computational framework for optimizing profile extrusion dies, aiming to achieve balanced flow at the die flow channel outlet while minimizing total pressure drop. The framework integrates non-isothermal, non-Newtonian flow modeling in OpenFOAM with a geometry parameterization routine in FreeCAD and a Bayesian optimization algorithm from Scikit-Optimize. A custom solver was developed to account for temperature-dependent viscosity using the Bird–Carreau–Arrhenius model, incorporating viscous dissipation and a novel boundary condition to replicate the thermal regulation used in the experimental process. For optimization, the die flow channel outlet cross-section is discretized into elemental sections, enabling localized flow analysis and establishing a convergence criterion based on the total objective function value. A case study on a tire tread die demonstrates the framework’s ability to iteratively refine internal geometry by adjusting key design parameters, resulting in significant improvements in outlet velocity uniformity and reduced pressure drop. Within the searching space, the results showed an optimal objective function of 0.2001 for the best configuration, compared to 0.7333 for the worst configuration, representing an enhancement of 72.7%. The results validate the effectiveness of the proposed framework in navigating complex design spaces with minimal manual input, offering a robust and generalizable approach to extrusion die optimization. This methodology enhances process efficiency, reduces development time, and improves final product quality, particularly for complex and asymmetric die geometries commonly found in the automotive and tire manufacturing industries. Full article

Achieving a uniform thickness and defect-free production in the flat die extrusion of polymer sheets and films is a major challenge. Dies are designed for one extrusion scenario, for a polymer grade with specified rheological behavior, and for a given throughput rate. The extrusion of different polymer grades and at different flow rates requires trial-and-error procedures. This study investigated the application of machine learning (ML) to provide guidance for the extrusion of sheets and films with a reduced thickness, non-uniformities, and without defects. A dataset of 200 cases was generated using computer simulation software for flat die extrusion. The dataset encompassed variations in die geometry by varying the gap under a restrictor, polymer rheological and thermophysical properties, and processing conditions, including throughput rate and temperatures. The dataset was used to train and evaluate the following three powerful machine learning (ML) algorithms: Random Forest (RF), XGBoost, and Support Vector Regression (SVR). The ML models were trained to predict thickness variations, pressure drops, and the lowest wall shear rate (targets). Using the SHapley Additive exPlanations (SHAP) analysis provided valuable insights into the influence of input features, highlighting the critical roles of polymer rheology, throughput rate, and the gap beneath the restrictor in determining targets. This ML-based methodology has the potential to reduce or even eliminate the use of trial and error procedures. Full article

The zygomatic bone area experiences frequent mechanical damage in the middle craniofacial region, including the orbital floor. The orbital floor bone is very thin, ranging from 0.74 mm to 1.5 mm. Enhancing digitization, reconstruction, and CAD modeling procedures is essential to improving the visualization of this structure. Achieving a homogeneous surface with high manufacturing accuracy is crucial for developing precise surgical models and tools for creating titanium mesh implants to reconstruct the orbital floor geometry. This article improved the accuracy of reconstruction and CAD modeling using the example of the development of a prototype implant to replace the zygomatic bone and a tool to form the geometry of the titanium mesh within the geometry of the orbital floor. The masked stereolithography (mSLA) method was used in the model manufacturing process because it is low-cost and highly accurate. Two manufacturing modes (standard and ultra-light) were tested on an Anycubic Photon M3 Premium 3D printer to determine which mode produced a more accurate representation of the geometry. To verify the geometric accuracy of the manufactured models, a GOM Scan1 structured light scanner was used. In the process of evaluating the accuracy of the model preparation, the maximum deviation, mean deviation, range and standard deviation were determined. The maximum deviations for anatomical structures created using the normal mode ranged from ±0.6 mm to ±0.7 mm. In contrast, models produced with the ultra-light mode showed deviations of ±0.5 mm to ±0.6 mm. Furthermore, the results indicate that the ultra-light mode offers better surface accuracy for die and stamp models. More than 70% of the surface of the models is within the deviation range of ±0.3 mm, which is sufficient for planning surgical procedures. However, the guidelines developed in the presented publication need to optimize the CAD process and select 3D-printing parameters to minimize deviations, especially at the edges of manufactured models. Full article