A Review on Part Geometric Precision Improvement Strategies in Double-Sided Incremental Forming

Low geometric accuracy is one of the main limitations in double-sided incremental forming (DSIF) with a rough surface finish, long forming time, and excessive sheet thinning. The lost contact between the support tool and the sheet is considered the main reason for the geometric error. Researchers presented different solutions for geometric accuracy improvement, such as toolpath compensation, adaptation, material redistribution, and heat-assisted processes. Toolpath compensations strategies improve geometric precision without adding extra tooling to the setup. It relies on formulas, simulation, and algorithm-based studies to enhance the part accuracy. Toolpath adaptation improves the part accuracy by adding additional equipment such as pneumatically or spring-loaded support tools or changing the conventional toolpath sequence such as accumulative-DSIF (ADSIF) and its variants. It also includes forming multi-region parts with various arrangements. Toolpath adaptation mostly requires experimental trial-and-error experiments to adjust parameters to obtain the desired shape with precision. Material redistribution strategies are effective for high-wall-angle parts. It is the less studied area in the geometric precision context in the DSIF. The heat-assisted process mainly concentrates on hard-to-form material. It can align itself to any toolpath compensation or adaptation strategy. This work aims to provide DSIF variants and studies, which focus on improving geometric accuracy using various methodologies. It includes a brief survey of tool force requirements for different strategies, sheet thickness variation in DSIF, and support tool role on deformation and fracture mechanism. Finally, a brief discussion and future work are suggested based on the insights from several articles.

Numerical and Experimental Studies on Hydro-Forming of a Thin Metallic Disc

This paper deals with the hydro-forming of a flat thin metallic disc to achieve a forward domed disc which will be subsequently adopted to manufacture a rupture disc. The plastic deformation induced by the hydraulic energy is numerically simulated through an isotropic hardening plasticity model using a non-linear explicit finite element analysis (FEA). The variation in disc’s central deformation, thickness, equivalent plastic stress and equivalent plastic strain with respect to the applied hydraulic pressure are determined from FEA simulations. The hydro-forming setup is then designed and manufactured, and the metallic disc is experimented under hydro-forming process. The reduction in thickness due to stretching of the thin disc is evaluated from experiment and simulation and a close agreement is found. This research attempt helped in finalizing the hydro-forming fluid pressure, the feasibility and the accuracy of practically achieving the desired geometry of the metallic disc. The near-fixidity effects on abrupt variation in sheet thickness and plastic strain are well captured through simulations which are very difficult to be studied through hydro-forming experiments.

Investigation of the influence of varying tumbling strategies on a tumbling self-piercing riveting process

The increasing demands for the reduction of carbon dioxide emission require intensified efforts to increase resource efficiency. Especially in the mobility sector with large moving masses, resource savings can contribute enormously to the reduction of emissions. One possibility is to reduce the weight of the vehicles by using lightweight technologies. A frequently used method is the implementation of multi-material systems. These consist of dissimilar materials such as steel, aluminium or plastics. In the production of these systems, the joining of the different materials and geometries is a central challenge. Due to the increasing demands on the joints, the challenges for the joining processes itself are also increasing. Since conventional joining processes are rather rigid and can only react to a limited extent to disturbance variables or changing process variables, new methods and technologies are required. A widely used conventional joining method with these properties is self-piercing riveting. Because of the rigid tool combination and the fact that the rivet geometry that can be used is related to the tools, the joining of multi-material systems requires tool and rivet changes during the process. In order to extend the process window of joining with self-piercing rivet elements, the process is enhanced with a tumbling kinematic of the punch. The integration of tumbling results in a significant increase in the adjustable process parameters. This enables a higher material flow control in the joining process through a specific tumbling strategy. The materials investigated are a steel and an aluminium alloy, which differ significantly in their mechanical properties and have many applications in automotive engineering, especially for structural car body components. The steel material is a galvanized HCT590X+Z dual-phase steel, which is characterised by a low yield strength, combined with high tensile strength and a good hardening behaviour. The aluminium alloy is an EN AW-6014. The precipitation-hardening alloy consists of aluminium, magnesium and silicon with a high strength and energy absorption capability. The objective of this work is to obtain a fundamental knowledge of the new tumbling self-piercing riveting process. With different mechanical properties and different sheet thicknesses of the joining partners, the influences of these parameters on the tumbling strategy of the riveting process are analysed. Such a tumbling strategy is based on the tumbling angle, the tumbling onset and the tumbling kinematics. These parameters are investigated in the context of the work for selected combinations of multi-material systems consisting of HCT590X+Z and EN AW-6014. With the variation of the parameters, the versatility of the process can be investigated and influences of the tumbling on the self-piercing riveting process can be identified. To illustrate the results, force–displacement curves from the joining process of the individual joints are compared and the geometry of the rivet undercut and rivet heads are geometrically measured. Furthermore, micrographs allow the analysis of the characteristic joint parameters interlock, residual sheet thickness and end position of the rivet head.

Method for Controlling Edge Wave Defects of Parts during Roll Forming of High-Strength Steel

Cold roll forming is suitable for sheet metal processing and can provide a new method for the production and processing of anti-collision beams for commercial vehicles. In order to accurately control the edge wave defects of the parts in the roll forming process, we used the professional roll design software COPRA to design the roll pattern and used the professional finite element analysis software ABAQUS to establish a three-dimensional finite element analysis model of the “b”-shaped cross-section. We analyzed the factors affecting the edge wave by controlling different process parameters (the thickness of the sheet, the height of the flange, and the forming speed), and the best process parameter combination was determined. The results showed that the thickness of the sheet, the height of the flange, and the forming speed all had an effect on the edge wave defects of the “b”-shaped cross-section. The influence of sheet thickness was the greatest, followed by flange height and then forming speed. The final selected parameter combination was a sheet thickness of 3 mm, a flange height of 100 mm, and a forming speed of 150 mm/s. This work provides a theoretical basis for actual production.

A contribution on versatile process chains: joining with adaptive joining elements, formed by friction spinning

Nowadays, manufacturing of multi-material structures requires a variety of mechanical joining techniques. Mechanical joining processes and joining elements are used to meet a wide range of requirements, especially on versatile process chains. Most of these are explicitly adapted to only one, specific application. This leads to a less flexibility process chain due to many different variants and high costs. Changes in the boundary conditions like sheet thickness, or layers, lead to a need of re-design over the process and thus to a loss of time. To overcome this drawback, an innovative approach can be the use of individually manufactured and application-adapted joining elements (JE), the so-called Friction Spun Joint Connectors (FSJC). This new approach is based on defined, friction-induced heat input during the manufacturing and joining of the FSJC. This effect increases the formability of the initial material locally and permits them to be explicitly adapted to its application area. To gain a more detailed insight into the new process design, this paper presents a detailed characterization of the new joining technique with adaptive joining elements. The effects and interactions of relevant process variables onto the course and joining result is presented and described. The joining process comprises two stages: the manufacturing of FSJC from uniform initial material and the adaptive joining process itself. The following contribution presents the results of ongoing research work and includes the process concept, process properties and the results of experimental investigations. New promising concepts are presented and further specified. These approaches utilize the current knowledge and expand it systematically to open new fields of application.

Comparative Analysis of Machine Learning Methods for Predicting Robotized Incremental Metal Sheet Forming Force

This paper proposes a method for extracting information from the parameters of a single point incremental forming (SPIF) process. The measurement of the forming force using this technology helps to avoid failures, identify optimal processes, and to implement routine control. Since forming forces are also dependent on the friction between the tool and the sheet metal, an innovative solution has been proposed to actively control the friction forces by modulating the vibrations that replace the environmentally unfriendly lubrication of contact surfaces. This study focuses on the influence of mechanical properties, process parameters and sheet thickness on the maximum forming force. Artificial Neural Network (ANN) and different machine learning (ML) algorithms have been applied to develop an efficient force prediction model. The predicted forces agreed reasonably well with the experimental results. Assuming that the variability of each input function is characterized by a normal distribution, sampling data were generated. The applicability of the models in an industrial environment is due to their relatively high performance and the ability to balance model bias and variance. The results indicate that ANN and Gaussian process regression (GPR) have been identified as the most efficient methods for developing forming force prediction models.

The effects of punch angle in noise and force formation for sheet metal blanking process

The paper is concerned with the effect of punch angle (0°, 4°, 8°, 16°), sheet thickness (0.8, 2 mm), and punch speed (25, 37.5 mm / min) on the force formation and noise in the blanking of DP600 dual-phase steel sheet. The blanking experiments were carried out in a modular blanking die. The blanking force and noise variables were obtained simultaneously during the blanking using a load cell and noise measuring device, respectively. It was determined that the blanking force significantly decreased with an increasing punch angle, while noise formation decreased. The increase in the punch speed slightly increased the amount of noise while it did not affect the blanking force significantly.

Correlation between Cutting Clearance, Deformation Texture, and Magnetic Loss Prediction in Non-Oriented Electrical Steels

Manufacturing the magnetic cores in electrical machines impacts the magnetic performance of the electrical steel by inducing stresses near the cutting edge. In this paper, energy loss behaviour in non-oriented electrical steels punched with different cutting clearances before and after annealing is investigated. An experimental shear cutting tool was employed to punch the ring-shaped parts from electrical steels in a finished state with four different values of cutting clearance corresponding to 1%, 3%, 5%, and 7% of the sheet thickness. The effect of cutting clearance on the magnetic losses is derived and analysed by the statistical theory of losses and associated loss separation concept including the analysis of movable magnetic objects. In this framework, this paper assesses the combined effect of cutting clearance, frequency, and heat treatment on the hysteresis loops and iron losses in non-oriented FeSi electrical steels. Measurements have been performed from quasi-static to 400 Hz at peak induction Bp = 1.0 T. Both states before and after heat treatment have been considered. The excess loss is observed as the most sensitive loss component to cutting clearance and its magneto–structural correlation is quantified.

Integrated Process Simulation of Non-Oriented Electrical Steel

[d=A]A tailor-made microstructure, especially regarding grain size and texture, improves the magnetic properties of non-oriented electrical steels. One way to adjust the microstructure is to control the production and processing in great detail. Simulation and modeling approaches can help to evaluate the impact of different process parameters and finally select them appropriately. We present individual model approaches for hot rolling, cold rolling, annealing and shear cutting and aim to connect the models to account for the complex interrelationships between the process steps. A layer model combined with a microstructure model describes the grain size evolution during hot rolling. The crystal plasticity finite-element method (CPFEM) predicts the cold-rolling texture. Grain size and texture evolution during annealing is captured by the level-set method and the heat treatment model GraGLeS2D+. The impact of different grain sizes across the sheet thickness on residual stress state is evaluated by the surface model. All models take heterogeneous microstructures across the sheet thickness into account. Furthermore, a relationship is established between process and material parameters and magnetic properties. The basic mathematical principles of the models are explained and demonstrated using laboratory experiments on a non-oriented electrical steel with 3.16 wt.% Si as an example. Improving the magnetic properties of non-oriented electrical steels are of high interest. In this context, improvement by a tailor-made microstructure, especially regarding grain size and texture, is one focus. One way to adjust the microstructure is to control the production and processing in great detail. Simulation and modeling approaches, emphasizing grain size and texture development, can help to evaluate and finally set process parameters. Here, we present individual model approaches for hot rolling, cold rolling, annealing and shear cutting and aim to connect the models to account for the complex interrelationships between the process steps. Furthermore, a connection between the process parameters and the magnetic properties is drawn. Grain size, grain size distribution, texture and dislocation density are the main transfer parameters in between the models. All models take heterogeneous microstructures across the sheet thickness into account. The basic mathematical principles of the models are explained, and a case study is presented in each case using FeSi3.2wt%Si as an example material.

Material Design for Low-Loss Non-Oriented Electrical Steel for Energy Efficient Drives

Due to the nonlinear material behavior and contradicting application requirements, the selection of a specific electrical steel grade for a highly efficient electrical machine during its design stage is challenging. With sufficient knowledge of the correlations between material and magnetic properties and capable material models, a material design for specific requirements can be enabled. In this work, the correlations between magnetization behavior, iron loss and the most relevant material parameters for non-oriented electrical steels, i.e., alloying, sheet thickness and grain size, are studied on laboratory-produced iron-based electrical steels of 2.4 and 3.2 wt % silicon. Different final thicknesses and grain sizes for both alloys are obtained by different production parameters to produce a total of 21 final material states, which are characterized by state-of-the-art material characterization methods. The magnetic properties are measured on a single sheet tester, quantified up to 5 kHz and used to parametrize the semi-physical IEM loss model. From the loss parameters, a tailor-made material, marked by its thickness and grain size is deduced. The influence of different steel grades and the chance of tailor-made material design is discussed in the context of an exemplary e-mobility application by performing finite-element electrical machine simulations and post-processing on four of the twenty-one materials and the tailor-made material. It is shown that thicker materials can lead to fewer iron losses if the alloying and grain size are adapted and that the three studied parameters are in fact levers for material design where resources can be saved by a targeted optimization.