Papers by Author: Mathias Liewald

Abstract: The production of tailored hollow shafts usually requires multiple manufacturing processes such as multi-stage forming processes and subsequently several machining operations, resulting into high costs and high manufacturing times. To address these challenges, a novel cold forging process featuring an adjustable forming zone was developed by the authors. This new approach enables the production of tailored hollow shafts with varying cross-sections in their length direction as well as internal undercuts within one stroke of the ram. In order to achieve the desired target geometry of a hollow shaft, a specific tool kinematic is required to precisely adjust the cross-section of the forming zone during the process. Currently, determining geometry-specific tool kinematics requires a time consuming iterative numerical procedure. In this paper, a machine learning approach for the prediction of the tool kinematics for a given target geometry of a tailored hollow shaft with variable wall thickness in its length direction is presented.

Abstract: This study investigates the structural response of blank-holders (BHs) equipped with spatially distributed magnetorheological (MR) actuators for adaptive deep drawing. While MR actuators provide fast, independent, and high-resolution force modulation, their effectiveness depends critically on the BH’s ability to transmit spatially differentiated loads without excessive diffusion or unrealistic stress localization. The relationships between BH stiffness, actuator spacing, and pressure localization at the sheet interface remain only partially understood, limiting the implementation of distributed blank-holding strategies. To address this gap, a comprehensive finite element (FE) framework is developed, combining a full closed-cup deep-drawing model with a complementary simplified configuration that isolates local deformation mechanisms under single-actuator loading. Parametric analyses examine the influence of BH thickness, local actuator force, and actuator spacing on stress distribution, localization radius, and overlap between adjacent load paths. Results show that BH thickness is the dominant factor governing spatial resolution: thinner BHs enable sharp pressure localization, whereas thicker ones diffuse local loads and suppress stress peaks. The spacing between actuators must therefore be selected as a function of BH stiffness to avoid stress-free regions while preserving distinct pressure footprints. For the reference industrial configuration (60 mm BH thickness), an actuator spacing of approximately 150 mm achieves the optimal compromise between localization capability and continuous sheet support. The proposed framework establishes quantitative design criteria for BH geometries compatible with MR-based adaptive forming and supports the development of next-generation blank-holding systems offering enhanced process stability, reduced scrap, and improved material-flow control.

Abstract: Lubrication plays a crucial role in cold forging, influencing key factors such as material flow, surface quality and tool wear. The current state of the art presents conventional mineral-oil-based lubricants as one of a range of effective solutions; however, they generate residues, require cleaning and pose environmental concerns. This work explores CO₂ snow as a potential residue-free, sustainable alternative for cold forming of mild steels. Miniature spike tests were conducted to characterise friction behaviour under varying lubrication and surface conditions. The study demonstrates that CO₂ snow can effectively reduce friction, promote favourable material flow and achieve surface finishes comparable to conventional oils, while eliminating residue and post-processing requirements. These findings suggest that CO₂ snow represents a promising eco-friendly lubrication strategy, offering both technical performance and environmental benefits for sustainable cold forging operations.

Abstract: The Guided Material Flow (GMF) process is an advanced variant of the Samanta process designed for the net shape cold extrusion of gears. The GMF process employs a modified die geometry to control material flow and significantly reduce maximum tool loads, effectively overcoming traditional process limitations. Key advantages include enhanced tooth tip strength and a reduction in face end deformations, which are characteristic defects in the conventional Samanta process. Minimising these deformations reduces the requirement for subsequent machining and enhances overall material efficiency. A numerical dataset was generated to train and validate data driven surrogate models, facilitating rapid process analysis without the computational cost of continuous Finite Element Analysis (FEA). The models developed in this paper enable the precise prediction of critical process outputs, including maximum punch force, die filling behaviour, material utilisation and strain hardening at the tooth tip. This paper details the numerical data acquisition, the specific training and validation methodologies of the machine learning models and demonstrates their capability to accurately predict complex process outcomes when varying the geometry of the die active surface in the GMF process.

Abstract: Aluminium matrix composites (AMCs) offer improved mechanical and tribological properties compared to monolithic materials and therefore provide great potential for various applications. This particularly applies to particle-reinforced AMCs revealing comparatively high contents of reinforcement particles. However, these types of composites are difficult to manufacture due to their abrasive characteristics as well as their complex rheological material behaviour. An approach to produce such AMCs is semi-solid powder processing, combining powder pressing and sintering in one step in order to produce fully dense composites with currently only cylindrical shapes. Therefore, the tools as well as the powder mixture are first heated into the semi-solid temperature range of the aluminium powder and subsequently formed using low pressures under 200 MPa. Due to the shear thinning behaviour of the semi-solid aluminium matrix the porous structure of the pressed powder is filled during compaction, resulting in homogenous particle distributions in the component. However, this process results in high process times as well as energy costs, due to the heating inside of the die. In contrast to the semi-solid powder processing in one step, in this paper, a novel process route combining cold uniaxial compaction of particle reinforced aluminium powders having up to 50 vol.% SiC with subsequent semi-solid forming is presented. Here, a particle reinforced and cylindrically shaped green body is utilized as raw material, in order to produce complex components through semi-solid forming. The parts produced in this way are featuring varying wall thicknesses and are used in order to determine the process limits for manufacturing particle reinforced components having up to 50 vol.% SiC. Thereby, the influence of reinforcement particle size as well as particle loading on the homogeneity of the resulting particle distribution of an academic component is investigated. Future main objective of the process route is the manufacturing of complex parts with homogenously distributed particles.

Abstract: Today, aluminium matrix composites (AMC) are widely used for the manufacturing of lightweight, yet highly stressed components in automotive, aeronautic and electrical engineering. In order to achieve particle distributions as homogeneous as possible within these component’s volumes and thus ensure optimum component properties, efforts are being made to simulate the manufacturing process prior to production. In this paper, AMC with extremely high particle fractions of more than 25 vol.% are considered in particular, as their processing still poses significant technological challenges. To model the particle motion in a computational fluid dynamics (CFD) simulation of the semi-solid forming process of this type of materials, a Lagrangian multiphase approach combining CFD and discrete element method (DEM) was used. Here, the DEM allowed all particle-particle interactions to be considered. Thus, different parameters influencing particle agglomeration, particle distribution as well as particle interaction with the cavity can be investigated during a numerical study. More specifically, the influence particle parameters such as cohesion forces and the influence of the forming speed onto the particle distribution in the final component ́s volume was analysed. The simulations were performed for a symmetric disc geometry. A forming tool was already available for this geometry, with which components could be manufactured to validate the simulation results. In the end, the study shows that by using four-way CFD-DEM coupling, simulation predictability for the semi-solid forming process of AMC could be significantly improved.

Abstract: Manufacturing of hollow components with local functional internal surfaces often requires complex process routes with several individual operations. By using a special hollow cold forging process with an adjustable deformation zone it is possible to manufacture hollow shafts with varying wall thickness over its axial length parts just within a single stroke of the press. Combining this principle with a splined mandrel allows manufacturing of tailored hollow shafts with local internal splines. However, the impact of geometry of mandrel and other process parameters on the shape of the cold forged internal splines have not been investigated yet. Furthermore, an underfilling phenomenon can occur on the outer surface of shaft during specific process states. In this contribution, several mandrel geometries and their impact on the part shape and filling / underfilling phenomenon in the mentioned process are investigated. To determine those effects, a numerical investigation has been conducted. Besides the geometry of the splined mandrel, also other parameters such as die geometry and tool kinematics were considered. The numerically calculated workpiece geometries are compared to the ideal geometries using a deviation analysis.

Abstract: The ongoing digitization of production processes provides new possibilities and potentials for process monitoring of forming and stamping processes. The component quality achievable by these processes is strongly dependent on the properties of the sheet metal material, so that a permanent digital recording of material data offers high potential for monitoring each component produced. In this context, presented paper deals with a novel AI-based method for the direct determination of ma-terial parameters from measured punching force curves. Using software systems Python and Tensor-Flow, an artificial neural network was first set up to determine mechanical material parameters (out-put data) from punching force curves (input data). As data basis for the adopted neural network, force curves were measured during punching of various sheet metal materials using a punching tool equipped with a direct force measurement device. Punching force curves were experimentally deter-mined for the sheet metal materials DP1200, DP1000, DP800, DP600, HX380LA, DC03 and DX54. Additionally, tensile tests were performed for these sheet metal materials to determine ultimate tensile strengths (Rm), yield strengths (Rp0.2, Re), uniform strains (Ag), elongations at break (At) and strain hardening exponents (n). The presented paper reveals that neural networks can accurately quantify the relationship between characteristic parameters of punching force curves and the mentioned me-chanical material properties.

Abstract: Cold formed sheet metal parts made of advanced high-strength steels (AHSS) offer a high potential for a lightweight, durable and economic design. However, manufacturing dedicated, high-strength parts with cold forming technologies such as conventional deep-drawing often results in unacceptable shape deviations due to elastic springback after unloading the part from the forming tools. Therefore, various springback compensation methods have been established to ensure dimensional quality of such sheet metal parts. At the Institute for Metal Forming Technology (IFU Stuttgart), deep-drawing with alternating blank draw-in was developed in this context as a new approach to reduce springback and enhance cold forming of AHSS sheet metal parts. Presented work provides numerical sensitivity analysis as well as experimental studies about this new forming method. The asymmetric and alternating blank draw-in, which is changed within a multistage forming process sequence, results in an alternated bending over tool radii and leads to a beneficial stress superposition in the part wall area with reduced springback phenomena. Compared to conventional deep-drawn sheet metal components, springback of a benchmark part geometry could thus be reduced over 75 % by a three-stage forming process with an optimized blank draw-in kinematic.

Abstract: Commonly used lubricants in sheet metal forming usually base on mineral or synthetic oils, water based emulsions, drawing films or hotmelts (waxes). However, these conventional lubricants often contain harmful substances to human health and the environment. For this reason, a novel tribological system for dry metal forming has been developed. Basic principle of this new tribological system comprises the use of volatile media such as CO_{2 (liquid)} and N_{2 (gaseous)}, which are injected into the contact interface under high pressure via injectors integrated into the tool. The volatile media used, lead to a significant reduction in friction and ensure robust friction behavior in deep-drawing processes. The investigations reported about in this contribution particularly focus on the friction behavior occurring in this tribological system at highly loaded radii. The friction investigations were carried out by using a modified stretch-bending-test and showed the effects of the main process-influencing parameters. In the present paper, these results are compared to already published results of the friction behavior investigated by means of flat strip drawing investigations. The findings obtained in this way allow a better understanding and prediction of the tribological system´s properties, thus making it usable for sheet metal forming applications.