Study On The Single Point Incremental Sheet Forming of AISI 321 Variable Wall Angle Geometry

For rapid prototyping, design validation and small batch productions process with low tooling cost is preferred. Single Point Incremental Forming (SPIF) is a die-less sheet metal forming process which requires only low cost forming tool driven by CNC machine in a toolpath to form required geometry at room temperature from sheet blank clamped in a low cost and low stiffness clamping system. In this study, effect of process parameters such as tool radius, feed rate and lubrication are considered on the formability of the truncated profile of AISI 321 Variable Wall Geometry (VWA). Set parameters conditions with 2 level layers are optimized using numerical and statistical approach. Experimentation on the same setup is carried out by selecting the most, least and mid favorable solutions optimized on the basis of forming forces and stresses in the sheet. Geometrical accuracy, sheet thinning, and forming forces are compared analytically, numerically and experimentally addressing the inadequacy of analytically models for Variable Wall Angle Geometries.

Effect of Geometrical Factors on Torsion in Cold Roll Forming of the Lower Side Beam of a Car

Cold roll forming is a continuous metal forming process used to produce a large variety of profiles. A significant product of cold roll forming is asymmetric profiles, whose application is expanding in the construction of cars, houses, bridges, etc. Torsion is one of the common defects in the cold roll forming process of asymmetric section steel and sometimes seriously affects cold roll forming products. With the development of the economy and technology, many asymmetric cold roll-formed parts are being gradually applied to automobiles. Three-dimensional finite element analysis models of 12 stands with 700L sheet material were carried out using the professional COPRA RF and MSC MARC software, taking the lower beam of an automobile as the research object. Five geometric factors of the lower side beam were researched, and the influence rules of different geometric elements on the forming torsion were analyzed. We found that with the increase of web width, flange width, and vertical edge height and the decrease of the corner radius and strip thickness, the torsion defects of cold roll forming were improved to different degrees. The results also showed that the width of the flange has the most significant effect on torsion.

Plastic Instability in Medium-Carbon Tempered Martensite Steel

Inhomogeneous plastic deformation damages the surface quality of a product in the metal forming process. Therefore, it is necessary to investigate the plastic instability of a metal. Tempered martensite is a common microstructure of medium-carbon steel. Plastic instability (Lüders phenomenon, Portevin-Le Châtelier phenomenon) in this phase was investigated by a uniaxial tension test performed at room temperature. The formation and propagation of a plastic band were analyzed via two-dimensional digital image correlation, and the strain and strain-rate fields were experimentally evaluated. The results obtained are as follows: (1) there was no clear yield plateau on the stress–strain curve; (2) Lüders phenomenon was present, but the Portevin-Le Châtelier phenomenon was not found; (3) in the Lüders deformation process, local strain distribution in tempered martensite is more complicated than that in ferrite.

A Novel Machine-Learning-Based Procedure to Determine the Surface Finish Quality of Titanium Alloy Parts Obtained by Heat Assisted Single Point Incremental Forming

Single point incremental forming (SPIF) is a cheap and flexible sheet metal forming process for rapid manufacturing of complex geometries. Additionally, it is important for engineers to measure the surface finish of work pieces to assess their quality and performance. In this paper, a predictive model based on machine learning and computer vision was developed to estimate arithmetic mean surface roughness (Ra) and maximum peak to valley height (Rz) of Ti6Al4V parts obtained by SPIF. An image database was prepared to train different classification algorithms in accordance with a supervised learning approach. A speeded up robust feature (SURF) detector was used to obtain visual vocabulary so that the classifiers are able to group the photographs into classes. The experimental results indicated that the proposed predictive method shows great potential to determine the surface quality, as classifiers based on a support vector machine with a polynomial kernel are suitable for this purpose.

Regression Approach to a Novel Lateral Flatness Leveling System for Smart Manufacturing

Sheet metal coils are widely used in the steel, automotive, and electronics industries. Many of these coils are processed through metal stamping or laser cutting to form different types of shapes. Sheet metal coil leveling is an essential procedure before any metal forming process. In practice, this leveling procedure is now executed by operators and primarily relies on their experience, resulting in many trials and errors before settling on the correct machine parameters. In smart manufacturing, it is required to digitize the machine’s parameters to achieve such a leveling process. Although smart manufacturing has been adopted in the manufacturing industry in recent years, it has not been implemented in steel leveling. In this paper, a novel leveling method for flatness leveling is proposed and validated with data collected by flatness sensors for measuring each roll adjustment position, which is later processed through the multi-regression method. The regression results and experienced machine operator results are compared. From this research, not only can the experience of the machine operators be digitized, but the results also indicate the feasibility of the proposed method to offer more efficient and accurate machine settings for metal leveling operations.

A novel method to improve the critical damage parameter of powder metallurgical components during the cold upsetting

In the metal forming process, the understanding of metal flows and the fracture strains are most significant to the failure/damage of the components. Usually, in metalworking, damage occurs because of nucleation, growth and coalescence of the void into a small fracture. These small fractures increased in the circumferential path due to the existence of stresses and the pores which leads to failure at the equatorial position during the upsetting of porous samples. Hence, the fracture of the workpieces strongly depends on the stresses and the pores. Such form of stresses and pores if relieved will give a better damage limit of the material. Therefore, in this research, a novel scheme of localised heating is adopted at the equatorial position of the compressed samples to enhance the critical damage parameter. The powder metallurgy route was used to prepare the required compacts with different relative densities (80%–90%) and 1 aspect ratio by applying suitable powder forming pressures. The upsetting test was performed on the obtained porous samples for various weight percentages of titanium (2%–6%) in the aluminium at the stable strain rate (0.1 s−1) and the damage location was noticed for various components. After the identification of damage position, various temperatures (100 °C–250 °C) of localised heating were attempted on the failure site of the specimens after some incremental stages of upsetting tests. The experimental results were analysed using various damage criteria and it was found that the initiation of failure is delayed and increased the critical damage value by selectively heating the samples because of relieving the stresses, reduction in porosity and changes in microstructure.