To address the challenges of low efficiency, high miss rate, and insufficient imaging stability associated with manual visual inspection in traditional automotive Body-In-White (BIW) joining processes, an intelligent inspection system based on computer vision and deep learning technologies is developed. An industrial camera imaging system is constructed with optimized optical parameters, and image preprocessing is realized using automatic masking techniques based on interactive image segmentation. Object detection is performed by incorporating an end-to-end object detection model (DETR). A full-stack data management architecture encompassing data acquisition, processing, storage, and visualization is established. Experimental results demonstrate that the system achieves a detection accuracy of over 99%, reduces task completion time by 80%, and lowers the miss rate by 67%. Both inspection efficiency and result consistency are significantly improved, satisfying the requirements for batch inspection of BIWs.

The welding quality of the positive electrode in lithium-ion batteries directly affects internal resistance, safety, and cycle life. To address issues such as insufficient strength, overwelding, and poor consistency caused by overly broad welding parameter windows (amplitude, energy, pressure) in current production, a Design of Experiments (DOE) method is introduced for process optimization. Initially, through a full factorial experiment with three factors and two levels, it is found that the initial parameter range (amplitude 30~60 μm, energy 40~100 J, pressure 30~60 MPa) is generally in an "over-welded" state, with amplitude identified amplitude identified as the most critical influencing factor. Based on this, the study further adopts the Box-Behnken response surface design to construct quantitative models for tensile force, peel force, and welding effectiveness within a narrowed parameter space. The results indicate that within lower parameter intervals, the contribution of energy and amplitude to welding quality shifts from negative to positive. Through multi-response variable optimization, the optimal process parameter combination is determined as amplitude 36 μm, energy 50 J, and pressure 40 MPa. Verification experiments confirms that under this parameter combination, the welded joints exhibit excellent mechanical properties, ideal foil adhesion rates, and significantly improved process stability. This provides a reliable basis for achieving refined control and mass production consistency in positive electrode welding.

To analyze the effect of light transmittance on the display performance of In-Mold Labeling (IML) films with hidden woodgrain patterns, a series of hidden woodgrain IML films with different light transmittance levels are prepared. Combined with subjective visual evaluation experiments, the influence of transmittance variation on the "hidden nature" of woodgrain and display clarity is systematically investigated. The experimental results show that when the light transmittance of the hidden woodgrain IML film ranges from 25% to 35%, visual interference from the woodgrain pattern is effectively reduced, while the clarity and color reproduction accuracy of the displayed content are significantly improved. Furthermore, the interaction patterns between light transmittance and factors such as background light intensity are revealed.

In response to the urgent demand for high-performance and cost-effective titanium alloys in the rail transit sector, this paper focuses on the recycling and utilization of TC4-DT titanium alloy returned scrap. A self-developed purification line is employed to process the turning scrap from ingot peeling. The purified scrap is blended with sponge titanium at a 30% ratio, followed by melting via a dual Electron Beam Cold Hearth Melting (EBCHM) and Vacuum Arc Remelting (VAR) process. Typical forgings are then prepared through open-die forging. To evaluate the removal capability of High-Density Inclusions (HDI) during EBCHM melting, a simulated test is designed. Results demonstrate that HDIs larger than 0.5 mm in diameter can be effectively captured by the cold hearth, while those smaller than 0.5 mm are dissolved under high temperature. High-precision industrial computed tomography is applied to conduct non-destructive inspection on three forgings. The results reveal a dense micro-structure, free from defects such as inclusions, pores, and cracks, confirming the reliability of the proposed purification and dual melting process.

To study the effects of a 200 ℃/1~10 h aging treatment on the mechanical properties, microstructure and corrosion resistance of 6082 aluminum alloy, tensile tests, intergranular corrosion tests are conducted, and SEM examination is performed on the tensile fracture surfaces. The results indicate that at 200 ℃ , the number of precipitated phases in the alloy matrix gradually increases with prolonged aging time, while the alloy strength first increases and then decreases. Additionally, the fracture morphology transitions from a ductile fracture dominated by numerous equiaxed dimples to a mixed fracture characterized by fine and shallow dimples along with tear ridges. As the aging time increases, the number of pitting corrosion pits and cracks on the alloy surface gradually increases and they interconnect. After peak aging, the number of corrosion pits and cracks significantly decreases, and the intergranular corrosion susceptibility of the alloy shows a trend of first increasing and then decreasing. Therefore, the under-aged state of 6082 aluminum alloy has both high strength and intergranular corrosion resistance, making it suitable for large-scale mass production applications in automotive parts.

Currently, significant fluctuations in vehicle models and configurations are observed across various automobile manufacturing plants. These fluctuations lead to operational redundancies within the Set Parts Supply (SPS) system, while newly constructed plants face difficulties in making SPS implementation decisions. Through efficiency and cost analysis, AI-assisted data calculation, and case validation, this study investigates the specific impacts of model and configuration variations on SPS operations. An optimized SPS evaluation model based on lineside space accommodation capacity is proposed. Furthermore, a systematic implementation strategy consisting of four sequential steps, namely data calculation, layout simulation, collaborative assessment, and benefit analysis, is established. The results demonstrate that AI-assisted analysis effectively processes multidimensional data, including lineside space constraints and material dimensions.

This paper takes a certain twin-wire spraying equipment as the object, starting with the mechanical structure, key functional units, and electrical control system, to conduct a systematic technical analysis. Focusing on the whole life cycle maintenance of the equipment, it analyzes the construction principles, failure modes, and improvement methods of core units such as the melting sprayer, temperature tester, wire feeder, driver, flow valve, and network module. It constructs a maintenance application system for preventive maintenance, condition monitoring, fault diagnosis, and system improvement. The research shows that building a "construction analysis-maintenance strategy-closed-loop improvement" trinity maintenance system from principle to principle is the key path to ensure the stable implementation of new processes and improve the comprehensive efficiency of equipment.

This article provides an overview of the current research status and development trends of key technologies for brake discs. It primarily focuses on aspects such as temperature field control, fatigue life prediction, lightweight design, and brake noise control. Research indicates that by optimizing structures such as ventilation holes, heat dissipation rib layout, and surface grooves, combined with geometric parameter control, convective heat transfer efficiency can be significantly enhanced, temperature gradients effectively reduced, thermal stress peaks lowered, thermal deformation suppressed, the risk of thermal cracks reduced, and fatigue life improved. The introduction of optimization algorithms has facilitated the collaborative design of heat dissipation performance and structural strength. Through topological optimization, material distribution and shape optimization can be restructured, leading to significant weight reduction. Optimizing the vibration source or improving the thermodynamic characteristics can effectively suppress brake noise. In the future, the optimization of brake discs needs to consider the effects of dynamic thermal-mechanical coupling, cyclic mechanical vibration, and extreme operating conditions during actual braking processes.

To address the issues of low accuracy and poor robustness in hole detection within 3D scanned point clouds of automotive components, this paper proposes a hole detection method that integrates α-Shapes with geometric-topological dual constraints. First, an improved voxel filter is used to preprocess the point cloud for noise reduction; Subsequently, a multi-scale triangular mesh is constructed via α-Shapes, and potential hole regions are extracted by combining boundary analysis; Finally, curvature features and normal vector consistency constraints are introduced to screen for real holes.Experimental results show that on a dataset containing 30 groups of automotive component point clouds, the proposed method achieves a hole detection accuracy of 97.3%. Its recognition rate and efficiency are both improved compared with the traditional Delaunay algorithm, and it can effectively adapt to scenarios with complex surfaces and multi-scale holes.

To reveal the influence of lubricant parameters on the efficiency of parallel-axis electric drive axle systems and optimize the lubrication matching design, a theoretical model of power loss and efficiency is established using a commercial vehicle parallel-axis electric drive axle as the subject. Theoretical analysis and bench tests are conducted around oil viscosity, operating oil temperature, and lubricant filling volume. The results indicate that using 75W-80 low-viscosity lubricant can improve system efficiency by approximately 0.84%, maintaining oil temperature at (90±5) ℃ enhances efficiency by about 0.99%, and filling 80% of the designed oil volume boosts efficiency by roughly 1.40%.