Papers by Keyword: Forming Process

Abstract: This work deals with Robust design optimization (RDO) under interval uncertainty and the resolution of such problems using a Bayesian optimization algorithm. In metal forming, process parameters such as tool radius, step size, or forming toolpath introduce variability that directly affects the final geometry and quality ofthe formed parts. In this context we aim at finding a design minimizing the amplitude of the performance interval but such a formulation does not account for the nominal performance. In this work, we introduce a scalarized objective adapted to the proposed algorithm allowing it to identify a Pareto optimum of both stability and nominal behavior. We propose an efficient expected improvement (EI) estimator for this objective based on an extreme-value approximation of surrogate extrema. The approach is illustrated on an analytical test problem and on a forming simulation with spring-back, where the new objective yields more practically relevant solutions than a variation-only robustness criterion.

Abstract: Air bending is a critical operation in the metalworking industry, where dimensional accuracy and process efficiency are essential to ensure product quality and economic viability. This work proposes an AI-driven design and optimization strategy which couples artificial intelligence, specifically artificial neural networks, with a quasi-random search algorithm for the metamodeling and optimization of the air bending process. An extensive simulation database was generated by varying geometrical, material, and process parameters, and neural-network-based metamodels were trained to predict the maximum punch force, maximum thickness reduction, and final bending angle, achieving high predictive accuracy with R² values exceeding 0.96. The metamodel was subsequently used to optimize process configurations by simultaneously minimizing the maximum punch force and the maximum thickness reduction while ensuring the target bending angle, leading on average to reductions of 46.7% in maximum force and 31.5% in thickness reduction compared to non-optimized cases. The results demonstrate that artificial intelligence provides an efficient and effective tool for the design and optimization of the bending process, significantly accelerating parameter selection while improving process quality and reducing manufacturing costs.

Abstract: The quality and dimensional accuracy of sheet metal components are strongly influenced by various sources of uncertainty, including variations in material properties, tool geometry and process parameters. Determining the specific source responsible for deviations in bending outcomes is usually costly and time-consuming, especially in industrial settings where numerous factors interact. In this study, a machine learning framework that can detect and quantify the impact of uncertainties in both air and bottom bending processes is presented. A dataset comprising forming results such as bending angles, final thickness and measured deviations, is used to train two neural networks metamodels (one for each process) that link input uncertainties to process outcomes. The predictive performance of these models was evaluated using different metrics achieving high predictive accuracy, with coefficients of determination close to 1 for most uncertainty sources in air bending and values above 0.95 for the majority of parameters in bottom bending. These results demonstrate the capability of the methodology to reliably identify dominant sources of uncertainty and support robust process optimization.

Abstract: Inherent limitations restrict the application of automated fibre placement (AFP) for manufacturing small components with complex geometries. As an alternative, flat, tailored preforms composed of fibre tows are first created and then formed into desired 3D geometries. However, the fibre orientation deviations between the as-manufactured and as-designed parts are inevitably introduced during forming. To address this issue, this study presents an iterative numerical forming/un-forming framework for the manufacture of highly aligned discontinuous preforms. At first, the as-designed preforms are “un-formed,” i.e., a reverse forming simulation, to achieve the corresponding flat preforms using the finite element modelling (FEM) method. To mitigate the deviations during forming, a pre-compensation strategy is then introduced by adjusting the initial fibre orientations derived from the un-forming analysis based on the calculated deviations through iterative re-forming simulations. A hypo-viscoelastic constitutive model implemented through a user-defined material subroutine captures the rate-dependent and orthotropic behaviour of the preforms during un-forming and re-forming. The FEM simulation results demonstrate significant reductions in fibre orientation deviation of formed 3D preforms through the iterative forming/un-forming framework, validating its applicability to a discontinuous fibre material on complex geometries.

Abstract: The 10 vol% SiC_p/Mg composites were prepared by external addition and stirring-casting method, and the hybrid reinforced (10 vol% SiC_p+10 vol% Mg₂Si)/Mg composites were prepared by combining in-situ method. The effects of melt ultrasonic treatment (UT) and forming processes on the thermophysical properties of the two composites were studied. The results show that UT can effectively disperse SiC particles in molten magnesium and reduce the casting porosity, while squeeze casting can significantly reduce the porosity of the composites, which can also significantly improve the thermal conductivity. The thermal conductivity (λ) of 10 vol.% SiC_p/Mg composites squeeze casted after UT is 135.3 W/(mK) and the average coefficient of thermal expansion (CTE) is 19.95×10^-6 K^-1 at 293-373 K. Compared with gravity casting, the λ is increased by 17% and the CTE is reduced by 0.8%. The λ of (SiC_p+Mg₂Si)/Mg composite squeeze casted after UT is 132.4 W/(mK), and the CTE is 18.95×10^-6 K^-1, which is 27% lower than the CTE of pure magnesium.

Abstract: Electron beam Surfi-Sculpt^TM is a novel surface treatment technique applied to produce high level performance Composite-Metal-Weld (Comeld^TM) joints. Investigation on forming process during electron beam Surfi-Sculpt^TM on Ti-6Al-4V alloy showed protrusions were formed via a layer-by-layer mode like additive manufacturing process. The near-surface region of electron beam Surfi-Sculpted Ti-6Al-4V alloy was occupied by fusion zone, heat-affected zone and base metal from the outermost surface to the underlying bulk alloy. The microstructure of fusion zone was characterized by a high density of fine acicular martensite phase, leading to a higher micro-hardness. A heat-affected zone was sandwiched between fusion zone and the underlying base metal, with different microstructural features compared to both fusion zone and the base metal.

Abstract: Quick superplastic forming is a new technology, which combines hot drawing preforming and superplastic forming. It makes full use of the high speed of hot drawing and good formability of superplasticity. For aluminum alloy complex components, the difficulties of stamping and low speed of superplasticity be perfect solved. In this work, the best forming process of side wall outer panel of metro vehicle was determined by forming experiment using quick superplastic forming technology. The high-speed rail edge skin with a very small fillet shape (R≤4 mm) and the large-size subway door frame part (h≈80 mm) formed by straight wall deep drawing were manufactured, using industrial aluminum alloy sheet with thickness of 4 mm. Meanwhile, the formed parts show the advantages of high dimensional accuracy and uniform wall thickness distribution, and the mechanical properties of formed parts can completely meet the requirements as well, which demonstrates the desirable efficiency, low cost and feasibility of this new technology.

Abstract: This work analyses the learning tasks, related to forming processes, realized by students of a Master degree focused on Manufacturing Engineering. The forming processes include bulk deformation and sheet forming. The objective of these activities is to identify if these practices are linked to research and development or technological innovation. The students must select works from database of international scientific journals and analyze the contents. The results show that the students have identified 62 papers from 21 different journals and of authors from 17 countries; mostly traditional processes (bending, extrusion, deep-drawing, mainly) have been chosen and studied, recognizing important advances in them; moreover the learning tasks have contributed to the acquisition the basic, general and specific competences.

Abstract: High strength AW-7xxx sheet alloys are promising candidates to manufacture crash relevant parts, but their limited formability at room temperature presents a major challenge. Formability is controlled through heating rate, heat treatment temperature and time, quenching rate, forming temperature and strain rate. In the literature retrogression forming, W-temper forming, warm forming and hot stamping processes have been proposed to improve the formability of AW-7xxx alloys. Of these the greatest improvement in formability comes from W-temper forming and hot stamping. Considering the similarity to the conventional forming processes of cold stamping for aluminium and hot stamping for steel, the W-temper forming and hot stamping of aluminium are promising for AW-7xxx alloys.

Abstract: Lightweight solutions and functional integration become more and more important in different fields of industry. In order to achieve a sensor and actuator functionality of shaped sheet metal parts, today a generally manual application step of the piezomodule is necessary. This subsequent process is time consuming and leads to high costs. In earlier studies a method was presented allowing the fabrication of a formable compound with an integrated sensor and actuator functionality. The formability of the compound is achieved using a viscous adhesive, surrounding the piezomodule during the forming operation. The low viscosity of the adhesive allows a relative movement between the piezomodule and the sheet metals and drastically reduces the transfer of critical strains to the piezomodule. Curing of adhesive takes place after the forming operation. To improve the efficiency of the process chain an advanced adhesive system with robust application properties has to be used. Furthermore, the productivity of several fabrication steps and their sequence in the process chain have to be verified and improved. The paper presents the process chain designed for automated production of formable sandwich sheets with integrated piezomodules, including the production steps for the fabrication of the semi-finished part as well as the forming operation. Aiming on a good formability during the shaping operation and on a stiff connection between the piezomodule and the sheet metal in the finished sandwich part, one focus is set on the adhesive properties required during the different process steps.