Advances in Manufacturing最新文献

The health states of sensing devices have a long-reaching influence on many smart application scenarios, such as smart energy and intelligent manufacturing. This paper proposes an ensemble methodology of the health-state evaluation of sensing devices, based on artificial intelligence (AI) technologies, which firstly takes into the operational characteristics, then designs a method of scenario identification to extract the typical scenarios, and subsequently puts forth a specific health-state evaluation. This method could infer the causalities of faulty devices effectively, which provides the interpretable basis for the health-state evaluation and enhances the evaluation accuracy of the health states. The suggested method has the promising potential to support the efficiently fine management of sensing devices in smart age.

In high-velocity impact welding (HVIW), vaporizing foil actuator welding (VFAW) can be utilized to join dissimilar metals. In comparison with conventional welding processes, the VFAW process minimizes energy loss, enhances weld strength, and effectively mitigates issues of overheating or material deformation associated with traditional welding methods. In this study, VFAW was utilized to successfully weld three different metal materials (Cu, Al6061-T6, Q235). An accurate smoothed particle hydrodynamics (SPH) model was established based on the experimental results. The impacts of collision angle and velocity of the flyer on the interface morphology of Cu/Al6061-T6 weld were investigated using the SPH method. The experimental results show that with an increase in the collision angle from 0° to 20°, both the wavelength and amplitude of the welding interface significantly increase. The tail vortex phenomenon also becomes more pronounced with the angle of tail rotation caused by particle motion gradually increasing. But when the collision angle exceeds 20°, the wavelength and amplitude of the welding interface tend to stabilize while its influence on tail vortex phenomenon decreases. The tail rotation angle induced by particle motion continues to increase, although at a decreasing rate. When the initial collision angle is kept constant, both the wavelength and amplitude of the welding interface continue to rise with increasing collision velocity up to 900 m/s. The wake vortex phenomenon becomes more pronounced as the number of particles in the jet gradually increases.

In order to increase the sales and profitability, it is essential to classify the pears according to the external morphology (including shape, color and luster) and internal defects that can be quantitatively detected by various approaches. However, the existing classification methods concentrate mainly on the external quality rather than the internal defects. Therefore, this investigation develops an efficient and accurate classification method that can identify the internal sclerosis and bruises by combining the X-ray non-destructive testing and the convolutional neural network. Initially, the relations between the characteristics of the internal defects, i.e., internal sclerosis and bruises, and the grayscale features of the X-ray images are analyzed to provide the experimental data and demonstrate the theoretical foundations. Then, the X-ray images are processed by resolution reduction, feature enhancement and gradient reconstruction to improve the training efficiency and classification precision. Finally, the 18-layer residual network (ResNet-18) is optimized and trained to identify the internal bruises and sclerosis and classify the pears based on the identification results. It is found that the overall accuracy can reach 96.67% for identifying the bruised and sclerotic pears. The proposed method could also be applied to other fruits for defects identification and quality classification.

In the traditional machining field, the addition of cutting fluid can appropriately reduce cutting forces, dissipate cutting heat, and facilitate the machining process. However, the use of cutting fluids has environmental implications. Recently, a phenomenon known as organic monolayer embrittlement (OME) has been proposed, which could address this issue. OME can reduce cutting forces, enhance surface quality, and improve machining performance without the need for cutting fluids, particularly noticeable in ductile metals like pure copper. This study conducted micro-cutting experiments on pure copper to investigate the microstructural features, cutting performance, chip flow patterns, and the effectiveness of OME. The results indicate that OME alters chip flow patterns from sinuous flow to segmented quasi-periodic micro-fracture flow, resulting in a 42% and 63% reduction in cutting forces for copper materials with different initial hardness. This phenomenon significantly improves surface quality, diminishes surface defects caused by adhesion, and effectively reduces work hardening layers. The study also demonstrates that OME is a physical phenomenon closely related to the adsorption properties of organic catalytic agents and van der Waals interactions. Materials with higher initial hardness exhibit less pronounced OME due to a sufficiently high grain boundary density, impeding dislocation movement during shear deformation and causing a local stress increase at the free surface of the chip. This leads to a change in chip flow patterns, improving machining performance, analogous to the adsorption effect of organic catalytic agents.

Flexible hybrid electronics possess significant potential for applications in biomedical and wearable devices due to their advantageous properties of good ductility, low mass, and portability. However, they often exhibit a substantial disparity in elastic modulus between the flexible substrate and rigid components. This discrepancy can result in damage to the rigid components themselves and detachment from the substrate when subjected to tensile, bending, or other loads. Consequently, it diminishes the lifespan of flexible hybrid electronics and restricts their broader-scale application. Therefore, this paper proposes a polydimethylsiloxane (PDMS)/SiC functionally graded flexible substrate based on variable stiffness properties. Initially, ABAQUS simulation is employed to analyze how variations in stiffness impact the stress-strain behavior of PDMS/SiC functionally graded flexible substrates. Subsequently, we propose a multi-material 3D printing process for fabricating PDMS/SiC functionally graded flexible substrates and develop an advanced multi-material 3D printing equipment to facilitate this process. Tensile specimens with the functional gradient of PDMS/SiC are successfully fabricated and subjected to mechanical testing. The results from the tensile tests demonstrate a significant enhancement in the tensile rate (from 21.6% to 35%) when utilizing the PDMS/SiC functionally graded flexible substrate compared to those employing only PDMS substrate. Furthermore, the application of PDMS/SiC functional gradient flexible substrate exhibits remarkable bending and tensile properties in stretchable electronics and skin electronics domains. The integrated fabrication approach of the PDMS/SiC functionally graded flexible substrate structure presents a novel high-performance solution along with its corresponding 3D printing methodology for stretchable flexible electronics, skin electronics, and other related fields.

Transparent optical elements play a significant role in optical imaging and sensing, and the form qualities of these elements are critical to the functionalities of opto-electrical equipment. Therefore, rapid measurement of advanced transparent optical devices is urgently needed. Deflectometry, as a commonly used measurement method, has broad applications in form measurement. However, there are some challenges in the reflective deflectometric measurement of transparent elements, such as fringe superposition, low reflectivity, and non-uniform backgrounds, which severely affect the measurement accuracy. To address these issues, a single-frame fringe separation method is proposed for the deflectometric measurement of transparent elements. A fast iterative filtering method is utilized for coarse fringe separation and a convolutional neural network is adopted to solve the information leakage and incomplete fringe separation. The construction of the neural network involves improving and refining the filtering method to achieve precise separation of fringes. The proposed method achieves fringe separation and forms reconstruction of the upper and lower surfaces. Through simulations and experiments, the effectiveness and robustness of the proposed method are demonstrated, and the measurement accuracy can achieve 65 nm root-of-mean-squared-error (RMSE).

The growing need for high-performance components in terms of shape and mechanical properties encourages the adoption of integrated technological solutions. In the present work, a novel methodology for affecting the superplastic behaviour and, in turn, the thickness distribution of magnesium alloy components is proposed. Through heat treatments using a CO₂ laser, the grain size was locally changed, thus modifying the superplastic behaviour in a predefined area of the blank. Both the grain coarsening produced by the laser heat treatment and the superplastic forming of the heat treated blank were simulated using a finite element model, which allowed to set the related process parameters for the manufacturing of the investigated case study (a truncated cone). The thermal finite element model of the laser heat treatment, calibrated using the experimental temperature evolutions acquired in specific areas during the heat treatment, was used to evaluate the influence of process parameters on the grain size evolution. The laser heat treatment was able to significantly promote the grain growth, increasing the mean grain size from about 8 µm to twice (about 17 µm). The resulting grain size distributions were implemented in the mechanical finite element model of the superplastic forming process and the combination of laser parameters which allowed to obtain the most uniform thickness distribution on the final component was finally experimentally reproduced and measured for validation purposes. Even in the case of the laboratory scale application, characterised by quite small dimensions, the proposed approach revealed to be effective, to improving the thinning factor (t_MIN/t_AVG) of the formed part from 0.85 to 0.89, and providing an increase in the thickness uniformity of about 4.7%.