Journal of Manufacturing Processes最新文献

The autobody closures have high requirements on the appearance accuracy of A-class surfaces, smooth contours, and continuous edges, so the forming quality of the autobody closures has long been the center of attention in the roller hemming process. To facilitate weight reduction in automotive manufacturing, lightweight materials such as aluminum alloy and hemming adhesive are commonly used. However, the heterogeneous coupling effect between the adhesive and aluminum alloy panel during roller hemming can significantly influence the forming quality of the panel. Additionally, the precision of the roller posture and trajectory plays a crucial role in determining the final quality of the panels, given the complex geometry of the autobody closures. Therefore, in order to continuously improve the forming quality of the autobody closures, this paper investigates the roller hemming process applied to variable curvature panel with adhesive on autobody doors. Firstly, the kinematic model for the roller posture and trajectory during roller hemming of the curved surface-curved edge panel was developed based on differential geometry theory. Secondly, a simulation model for roller hemming of the panel with adhesive was established using the finite element method and the smoothed particle hydrodynamics method (FEM-SPH). The validity of the simulation was confirmed by comparing the simulated results with experimental outcomes. In the experiment, the algorithm for solving the posture and trajectory of the roller was applied, and the forming quality of the panel was evaluated by using the two indexes of roll-in/out coefficient and surface wave coefficient. Thirdly, the impact of the hemming factors on surface wave and roll-in/out was analyzed using the response surface methodology, leading to the development of a mapping relationship between the hemming factors and forming quality. This study provides valuable support for predicting the forming quality of variable curvature panels with adhesive and continuously improving the forming quality of autobody closures in the roller hemming manufacturing process.

In this work, a numerical model has been developed to determine the stresses and deformations involved in the under-tension-bending-unbending processes of metallic sheet strips. The presented procedure allows us to evaluate the behavior in the die radius of a typical deep-drawing process. The procedure is based on a flexible numerical method that can be adapted to many other processes. Experimental results have been obtained from TRIP 690 + EBT steel sheets under different pure shear deformation states. The forces involved as well as the final deformations, or spring-back, after each forming process analyzed (bending, unbending over-unbending and stretching), were determined by introducing these experimental data into the ad-hoc created numerical method. The results obtained by the proposed model have been compared with finite element simulations (FEM) and contrasted with the experimental results. This allows the proposed procedure to be validated as a general method with more accuracy than FEM as permits the thickness of the sheet to be divided into a great number of points or elements.

The measurement and control of the heat transfer of sheet alloys in successive non-isothermal forming cycles is crucial to achieve the desired post-form properties and microstructure, which could not as of yet be realized by using traditional test facilities. In the present research, a novel heat transfer measurement facility was designed to generate and subsequently measure the in-situ heat transfer from a sheet alloy to multi-mediums such as forming tools, air, lubricant and coating. More importantly, the facility was able to use a single sheet alloy sample to perform successive non-isothermal forming cycles, and subsequently obtain high throughput experimental results including the temperature evolution, cooling rate, mechanical properties and microstructures of the alloy. The high throughput in-situ heat transfer measurement facility identified that the cooling rate of AA7075 was 152 °C/s and the mechanical strength was over 530 MPa in the 1st forming cycle. However, it decreased to less than the critical value of 100 °C/s in the successive 10th forming cycle, leading to a low mechanical strength of only 487 MPa. The identified variations that occur in the successive non-isothermal forming cycles would improve the consistency and accuracy of part performance in large-scale manufacturing.

Prediction of 2D cross-section and full 3D geometry for stacked weld beads is critical for the outcome of wire-arc directed energy deposition (DED) parts; however, most additive path planning software packages model beads as extrusions of a rectangle. Weld beads are not rectangular, and the resulting shape is dependent upon physics effects at the moment of deposition. Physics phenomena such as the geometry of the underlying surface, the heat input of the welding mode, and the direction of gravity contribute to bead shape. This paper presents a novel implicit modeling method that discretizes a 2D area or 3D volume of space into pixels or voxels and constructs fields based on these physics phenomena. The fields are combined using a weighting scheme trained on 3D scan measurements of welds and wire-arc DED prints. Pixels or voxels are added until the known amount of deposited volume has been achieved. Thereby, a strong conservation of mass principle is applied to the process. Utilizing machine learning techniques, the present model can be trained on a database of scans allowing for the representation of a wide variety of prints. Results show that this method can produce predictions with realistic bead morphology and sub-millimeter form error.

Cladding of the aluminum (Al) layer on steel was successfully implemented via additive friction stir deposition (AFSD). We revealed the relationship between the overlapping deposition strategy of AFSD and the resultant microstructure and mechanical properties of Al-clad steel for the first time. Overlapping deposition strategies efficiently improved the adhesion of the Al layer on steel in the boundary region owing to the sufficient material flow and large plastic deformation. This is in contrast to the sample without overlapping where the Al/steel interface in the boundary region is characterized by holes and weak bonding. In particular, the maximum shear strength (109.0 MPa) was obtained for the sample with an overlap of 8 mm, even higher than that of the single-pass sample. This study provided a novel approach to the fabrication of large-scaled clad layers on hard substrates, and this strategy is expected to greatly contribute to the adoption of AFSD in the fields of cladding, joining, and coating.

Thermoplastic filament winding is a flexible manufacturing method typically used in the production of cylindrical composite structures, allowing for in-situ consolidation without the need for a second consolidation step. The objective of this study is to produce non-cylindrical geometries, typically manufactured using thermoset matrix composites according to the literature, using the thermoplastic filament winding process. For this purpose, glass fiber (GF) reinforced polypropylene (PP) prepreg tapes were used to produce hexagonal cross-section thermoplastic composite parts. The critical process parameters; hot-air heater nozzle temperature, compression roller pressure, the linear speed of mandrel rotation, and corner radius of the mandrel, were determined using the Taguchi experimental design method. The interlaminar shear strength (ILSS) and maximum compressive strength (σmax) values were obtained as 211 MPa and 49.40 MPa as maximum, respectively. ANOVA analysis showed that the corner radius had the most significant impact on ILSS, while mandrel rotation speed and temperature were critical for σmax.

Manufacturing industrially profitable high solid-loading ceramic materials with finely designed complex shapes is an exciting yet challenging in sustainable additive manufacturing. Here, we propose a resin strategy to achieve a high solid-loading content of 62 vol% alumina slurry for 3D printing high-quality complex shapes using digital light processing (DLP) technology. Remarkably, both high solid-loading content and tuned sintering temperature emerge as key factors in ensuring optimal print quality and mechanical performance. With this strategy, the ceramic slurry containing 62 vol% exhibits lower shear rate and improved layer adhesion. The burnout treatment was designed based on the DSC-TGA results, followed by sintering in an air atmosphere. Comprehensive physical measurements were achieved, alongside precise structural characterization at multilength scales in situ. In depth exploration of post-sintering analysis revealed no changes in phase composition or chemical bonding. The optimum overall performance of sintered specimen exhibited shrinkage of 8.3 %, 8.8 %, and 11.5 % in the X, Y, and Z directions, with a bulk density of 3.76 g/cm³. Mechanical testing demonstrated superior flexural strength of 247.23 MPa, nanoindentation hardness of 30.9 GPa, and modulus of 428.35 GPa. This high-precision printing strategy may significantly contribute to understanding the structure-property relationship of DLP-3D printed Al₂O₃ ceramic and opening avenue for the applications of high-strength parts in demanding environments.

Incoloy825/X65 composite plate had good application in the submarine transporting pipelines due to combination of the high resistance to Cl⁻ corrosion and preferred mechanical properties. But the enrollment of Fe into Ni layer deteriorated the corrosion resistance in welding the transition layer of composite plate. In view of this, the paper respectively adopted the laser welding on the Ni layer without filler metal and then the swing arc CMT welding with steel filler metal as a transition in order to inhibit the Fe into Ni layer. The results showed the laser welding bead on Ni layer with uniform and fine γ microstructure ensured the better corrosion resistance. The CMT welding controlled the dilution rate under 6 % through optimizing the welding speed and swing frequency of arc. Finally, the tensile strength of transition weld was up to 500 MPa surpassing the base metal of 490 MPa. The clad bead with charge transfer resistance of 756 kΩ·cm² satisfied general submarine pipeline anti-corrosion requirement.

The present study examined the effects of laser shock peening (LSP) and low-temperature annealing after LSP (LSPA) on the corrosion resistance of the Ti6Al4V alloy. The high density of dislocations in the LSP samples contributes to the rapid formation of a TiO₂ passive film during the electrochemical corrosion process. In this study, low temperature annealing was employed to further improve the corrosion resistance. The results indicated that the corrosion resistance of the LSPA samples was significantly improved compared to that of the LSP-treated samples. The LSPA treatment facilitated the pre-generation of a dense TiO₂ passive film on the alloy surface via oxidation, reduced corrosion rate, inhibited the penetration of dissolved oxygen and ions present in the sodium chloride solution into the alloy surface. Meanwhile, low-temperature annealing could rearrange and annihilate dislocations, creating subgrains and relaxing non-equilibrium grain boundaries induced by deformation. This process reduced active sites and grain boundary energy, ultimately improving the corrosion resistance of the Ti6Al4V alloy.

Electrohydrodynamic jet printing technology has garnered significant interest in additive manufacturing due to its advantages in higher resolution printing and greater viscosity material applicability. Nonetheless, the challenges associated with femtoliter-level droplets and the micrometer-scale printing space have rendered traditional optical observation methods for volume calculation impractical for integration into the printing systems. Obtaining the droplet volume accurately has become a formidable challenge in electrohydrodynamic printing. While existing research utilizes machine learning for the end-to-end prediction of process parameters to droplet volume, traditional prediction methods cannot achieve online prediction due to the complex spray states characteristic of electrohydrodynamic jet printing and pose integration difficulties within printing systems. This paper introduces a multi-source data fusion model suitable for electrohydrodynamic printing droplet volume prediction. The model employs the VGG network to extract features from Taylor cone images in the jetting state and synchronously fuse these with process parameter features. The fused features are then correlated with droplet volume labels through the MLP network for comprehensive model training. The performance of the proposed model has improved by 10% in prediction accuracy compared to single modal data. We integrated the prediction method into an electrohydrodynamic jet printing system and experimented with printing pixel-pit substrates. The results indicate that the prediction accuracy of the volume prediction system is over 92%. The printing efficiency has improved approximately 3 times compared to the traditional method, significantly enhancing overall performance.