International Journal of Advanced Manufacturing Technology最新文献

Abstract

Exciting ternary-mechanism model considers the effects of flank shearing, flank ploughing and bottom ploughing and suits for the calibration of cutting force coefficients with a relatively lower axial depth of cuts in which the cutting force proportion of bottom edge gradually increases. Since the vibration velocities are not formulated in the empirical rubbing formulae, the process damping effect in chatter stability can not be modelled. In order to simultaneously guarantee the calibration accuracy of the cutting force coefficients and solve the chatter stability with process damping, a unified ternary-mechanism model is established in this article. First, the ploughing forces corresponding to the flank edge and bottom edge are formulated as the function of the indented area and the corresponding proportion factors based on Hertz contact theory. And the static and dynamic ternary cutting forces are explicitly formulated. Second, with the aid of the static equilibrium equation together with the expression of small disturbance, the dynamic model including ploughing-based process damping is established. Third, a fast procedure to calibrate the real-time cutting force coefficients is also derived based on the inverse process of static cutting force modelling. A series of test platforms are built to verify the correctness of the calibration method and the ploughing-based process damping model. Good consistency between the predicted and experimental results in both static cutting forces and dynamic chatter tests proves that above models have better accuracy.

A high pulsed fiber laser was utilized to drill square microholes in Si₃N₄ sheets in an atmospheric environment. Various processing parameters including scan spacing, number of scan passes, and number of multi-ring paths with a multi-ring strategy were adjusted to laser-drill Si₃N₄ sheets. The geometric characteristics of laser-drilled square microholes with shoulder height, taper angle, and corner radius were measured using a laser scanning microscope. X-ray diffraction was applied to examine the residual stress of the Si₃N₄ sheets before and after laser drilling. Moreover, the heat-affected zone and element content were examined using a scanning electron microscope. The experimental results exhibited that the optimal shoulder height of the square microhole drilled with the multi-ring strategy was 6.67 ± 0.21 μm, which was approximately 77% lower than that of 29.05 ± 10.95 μm for the square microhole drilled with the single-ring strategy. Moreover, the residual stresses of the original Si₃N₄ sheet and the square microholes laser-drilled by single-ring and multi-ring strategies were − 181.2 ± 41, 164.5 ± 31.9, and 104.6 ± 7.8 MPa, respectively. The proposed laser drilling technology with the multi-ring strategy can be widely used in the semiconductor industry for probe cards.

Abstract

Laser powder bed fusion is a key technology of additive manufacturing that enables the fabrication of metal parts with complex geometry through a multilayer process. Despite its great promise in design flexibility, wide application of this technology is hindered by a lack of quality assurance in fabrication parts. Melt-pool morphological characteristics are eminent indicators for manufacturing process stability and part quality. However, existing studies on melt-pool morphology focused on key geometric properties (e.g., length, width, size) extracted from melt-pool images for characterizing its variations, and tend to overlook 3D morphological variations of melt pools and ejected spatters. In this paper, we develop a multiscale modeling framework to represent, characterize, and monitor melt-pool variations through 3D morphological features, including multiscale basis function modeling of 3D melt-pool morphology and an iterative search of predominant components for sparse representation of morphological variations in melt-pool images. A case study with real-world experimental data shows that the proposed framework effectively characterizes 3D melt-pool morphological variations and provides salient features for tracking process variations, predicting melt-pool sizes, and detecting spatters. This framework is generally flexible for a wide variety of additive manufacturing (AM)applications such as melt-pool simulation, process monitoring, and anomaly detection.

With the continuous evolution of additive manufacturing technology, the production of spherical powders has become increasingly vital. Various studies suggest that factors such as the preparation process, powder materials, and sphericity are crucial in determining product performance. This paper provides a comprehensive review of the principles, advantages, and disadvantages of three widely used preparation technologies for spherical powders: gas atomization (GA), plasma rotating electrode process (PREP), and radio frequency plasma (RFP). Next, we identify the current research gaps in the preparation process for spherical powders and analyze the techniques for controlling particle size, sphericity, and purity during powder production. Finally, we proposed the development trend of spherical powder preparation technology, which provides crucial insights for optimizing the preparation process.

Tools for implementing a systematic quality management are necessary for the use of material extrusion as an additive manufacturing process for products with high quality requirements. Well-defined quality classes are crucial for ensuring that the requirements for a product can be communicated transparently and that the existing properties can be evaluated. Furthermore, there is a lack of capable measurement equipment for the acquisition of process data during the production process. To address these challenges, the present paper introduces an image processing system that determines quality indicators for individual layers in terms of imperfect surface percentages and the number of imperfections. The central element of the hardware is an adaptive darkfield illumination, which leads to high-contrast images. In addition, five types of layer subareas are identified in a segmentation step. Unsupervised machine learning methods are then used to detect imperfections in each layer subarea. In the segmentation, the current layer can be distinguished from irrelevant image background regions with an F-measure of 0.981. For the layer-wise measurement of the quality indicators, relative measurement errors with standard deviations of 25 to 76.1% are found. After evaluating the capabilities of the image processing system, a proposal for limits of quality classes is derived by monitoring several material extrusion processes. For this purpose, three quality classes for each of the five layer subareas are deduced from the process scatter measured by the image processing system. The results are an important contribution to the industrialization of material extrusion in safety–critical areas such as medical technology or the aerospace industry.

Abstract

The thermal error in the spindle unit is substantial and necessitates mitigation. Current models, being predominantly static in nature, have limited efficacy in error control. Integrating digital twin technology for modeling and controlling spindle unit thermal error holds promise in enhancing the machining accuracy of machine tools. Yet, the notion of a digital twin system specifically tailored for spindle unit thermal characteristics remains uncharted territory. To navigate these challenges, this study introduces a novel digital twin system tailored for spindle unit thermal characteristics. This system is poised to revolutionize thermal error modeling and compensation by harnessing the capabilities of digital twin technology. Within this digital twin framework, both the thermal error control model and the analytical thermal characteristic model are seamlessly integrated. The control model is devised as an exponential function, utilizing operational time, inherent time constants, and both initial and equilibrium thermal errors as parameters. Delving deeper, the analytical thermal characteristic model for the spindle system is rooted in a thermal resistance network approach. This leads to a closed-loop thermal characteristic modeling process, culminating in the derivation of a steady-state thermal error. Intricate heat transfer dynamics between spindle components are dissected, and a comprehensive thermal equilibrium equation set is formulated for the spindle unit. This equation set comprehensively accounts for dynamic variations in key parameters such as preload, lubricant viscosity, thermal load intensity, thermal contact resistance, and convective coefficients. To ascertain the time constant, a meticulously designed set of thermal characteristic experiments is executed. Subsequently, the digital twin system embarks on predictive modeling of thermal errors across varied operational conditions. This prediction then forms the foundation for thermal error compensation. With the integration of the present model into the digital twin system, the results are impressive: the absolute average and maximum deviations in thermal elongation, post-error control, stand at approximately 0.40 μm and 1.24 μm, respectively.

This study delves into the grinding-induced microstructural and mechanical evolution in high-entropy nickel-based superalloys GH4169 and DD5, underscoring their distinct behaviors under varying machining conditions. Leveraging “Random Substitution” in Material Studio, the research developed intricate atomic models to accurately depict the complex chemical compositions and microstructures of these superalloys. Neper software was employed for multi-scale modeling, specifically analyzing the unit cells of GH4169. A critical focus was placed on the effects of key grinding parameters—depth, spindle speed, and feed rate—on the crystallographic deformation of GH4169, contrasting it with the response of DD5. The study highlighted a notable transition in GH4169’s material removal mechanism from plastic flow to chip spallation at enhanced grinding depths and feed rates, while maintaining lattice integrity at higher grinding speeds. GH4169 consistently demonstrated greater tangential and normal forces during grinding compared to DD5, reflecting intricate machining complexities. The differential crystal orientations between these superalloys significantly impacted the grinding force distribution and heat dissipation during the process. This comprehensive analysis provides pivotal insights into the micro-level grinding process parameters, enriching both theoretical and practical understanding of material machinability in advanced manufacturing contexts. The study’s novelty lies in its application of detailed atomic models and multi-scale modeling to uncover subtle microstructural and mechanical dynamics during the grinding of superalloys.

Abstract

The integral blisk has been widely used in aerospace, and its structural performance is inextricably linked to the blade surface quality. To improve the surface integrity of polished surface, ultrasonic vibration assisted belt flapwheel flexible polishing (UBFP) is proposed. In this study, the polishing principle of UBFP and the effects of vibration on surface generation are investigated, and kinematic analyses and trajectory simulations are performed. Furthermore, the influences of the main processing parameters on the polishing force and surface roughness in UBFP are explored experimentally, and the sensitivity of the main parameters is distinguished by multi-parameter relative sensitivity analysis based on Monte Carlo simulation. The results show that the ultrasonic vibration contributes to the polishing process primarily through kinematic state changing and trajectories interlacing of abrasives. Compared with conventional belt flapwheel flexible polishing, the polishing force decreases by 15.72% and the surface roughness decreases by 17.39%. The compression depth is the most sensitive parameter in the process of UBFP. This study demonstrates the feasibility of UBFP and provides a theoretical and experimental reference for improving the polishing surface quality of the blisk blade.

During the pulsed laser cladding process, complex thermal accumulation occurs between powder and beam due to the pulsed laser periodic change. The selection of process parameters affects the cladding layer quality, and the correlation between the parameters is high. It is of great significance to obtain high quality cladding layer to determine the influence of the powder-carrying gas nitrogen velocity, powder feeding port diameter, and powder feeding angle on the powder flow, as well as the optimal powder shading rate and the mechanism of powder interaction with pulsed laser beam. In this paper, a gas–solid coupling model during the pulsed laser cladding process of three-beam coaxial powder feeder was established, and the rotating Gaussian heat source function of pulsed laser was written to calculate the temperature, flow velocity, and concentration distribution considering the interaction between laser and powder. The orthogonal test method was used to optimize the process parameters in order to reduce the shading rate of powder and improve the laser energy utilization. On this basis, a full cycle three-dimensional multi-field coupling numerical model for pulsed laser cladding process was established, and the temperature, flow, stress fields, and multi-component heat and mass transfer behaviors were calculated under different powder shading rates. The flow temperature of powder was collected by infrared thermometer and compared with the numerical results, the reliability of the model was verified. This study provides a significant theoretical basis for the full-cycle optimization of process parameters and the improvement of cladding layer quality during pulsed laser cladding.

This study investigated the mechanism of UVAD using numerical and analytical techniques. Silicon wafers possess challenging cutting properties due to their inherent brittleness and susceptibility to cracking along specific crystal orientation. Hence, non-traditional cutting methods like UVAD hold promise for precision micro-hole drilling in silicon wafers. In order to comprehend the mechanism of UVAD, the numerical technique utilized a direct brittle micro-cracking model within a 2D finite element (FE) method. This facilitated a comparative analysis between conventional drilling (CD) and UVAD, with a specific focus on understanding the micro-cracking mechanisms during the mechanical process. This study examined primarily the cutting force, micro-fracture analysis, and cutting energy. The numerical technique effectively predicted micro-cracks within the brittle regime, a task that is challenging to accomplish using analytical methods alone. In parallel, an analytical technique was developed to predict brittle-ductile transition (BDT) lines by analyzing the thrust force and specific cutting energy (SCE), combined with the numerical technique. Various feed rates per revolution were tested to validate the analytical force predictions. The analytical results demonstrate that the force profile corresponds to the transient cutting depth, while the numerical results indicated that the direct brittle micro-cracking model effectively demonstrated the fracture mechanisms, particularly at greater depths of cut. The SCE graph can predict the formation of a ductile regime on the cutting surface of the drilled micro-hole, although predicting micro-fractures on the side edges of the drilled micro-holes remains challenging. Additionally, UVAD demonstrated a reduction in micro-fractures on the sides of drilled micro-holes, particularly at very low feed rates per revolution.