Advances in Manufacturing最新文献

In this study, the entire process of entry-drilling cutting and steady-state cutting of indexable insert drills was investigated to address challenges, such as vibration, chipping, and poor machining quality, during the cutting process. The research involved the utilization of theoretical analysis and simulation to examine the three-stage force of entry drilling and steady-state force of drilling bodies with various lap structures. Different parameters of the lap structure were analyzed to understand their impact on the direction of the cutting force, emphasizing that the force direction was influenced more by lap structure than the size of the cutting force. Data on radial force, axial force, hole diameter, hole wall roughness, and drill scraping were obtained from experimental cutting of carbon and stainless steel. The performance of different lap structures was evaluated based on these parameters. The experimental results revealed that the radial force in the given environment was most significantly impacted by the height difference between the central and peripheral insert. This was followed by the central insert deflection angle α₂ and peripheral insert deflection angle α₁. A larger deflection angle β resulted in a skewed radial force direction toward the outermost end of the peripheral insert, minimizing drill body scraping and increasing radial force. Furthermore, a substantial increase in radial force and axial force was observed with an increase in feed, while these forces were not significantly affected by the increase in cutting speed. Additionally, the hole diameter and hole wall roughness after cutting increased with the rise in feed.

Serving as a proof of concept, additive manufacturing and electrophoretic deposition are leveraged in this work to enable structural lithium-ion batteries with load-bearing and energy storage dual functionality. The preparation steps of a complex 3D printed copper current collector, involving the formulation of a photocurable resin formulation, as well as the vat photopolymerization process followed by a precursors-based solution soaking step and thermal post-processing are presented. Compression and microhardness testing onto the resulting 3D printed copper current collector are shown to demonstrate adequate mechanical performance. Electrophoretic deposition of graphite as a negative electrode active material and other additives was then performed onto the 3D printed copper collector, with the intention to demonstrate energy storage functionality. Half-cell electrochemical cycling of the 3D multi-material current collector/negative electrode versus lithium metal finally demonstrates that structural battery components can be successfully obtained through this approach.

Vibration finishing can effectively reduce the surface roughness of blisks and change blade shape accuracy. This study investigates the influence of vibration finishing on the shape accuracy of the blade part of the blisk. The influence of the fixed attitude of the blisk on the position accuracy and profile accuracy of different measuring sections of the blade is analyzed. The changes in the blade geometry before and after vibration finishing are analyzed. The adjustment method of blade disc attitude in the machining process is developed, and the tooling used to fix the blade disc in the vibration finishing is improved. By controlling the deformation in different time periods to offset each other, the contact between the abrasive and the blade edge is reduced, effectively reducing the displacement of the blade section and the excessive wear of the edge.

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).