Journal of Manufacturing Processes最新文献_第5页

A physics-informed neural network with adaptive loss weighting for tool wear and remaining useful life prediction in deep hole boring 一种具有自适应损失加权的物理信息神经网络，用于深孔钻孔中刀具磨损和剩余使用寿命预测

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-01-21 DOI: 10.1016/j.jmapro.2026.01.047

Pengfei Zhang , Hanxiao Zhao , Ang Li , Chao Sun , Hongzhe Zhang , Naohiko Sugita , Liming Shu

Tool wear and remaining useful life (RUL) prediction are critical for ensuring machining quality and reducing production costs, playing an important role in deep-hole machining. Recently, physics-informed neural network (PINN) has attracted great attention to achieve this goal. However, the weights between physics-based models and data-driven models are often set empirically, which severely affects training accuracy and stability. To address this issue, this paper proposes a PINN with adaptive loss weighting, by quantifying the variance of prediction errors for tool wear and RUL prediction. First, multi-channel signals in deep hole boring are used to extract time-domain and frequency-domain features. Then, correlation coefficients between tool wear and features are calculated for feature selection, and combined with cutting stroke information to form the dataset. Next, based on the cutting stroke and flank wear values, a tool wear rate model is constructed using the least squares method. This equation serves as the physical consistency constraint of the PINN. The total loss function is constructed by combining the data loss from the data-driven model, the monotonicity loss, and the physical consistency loss. Finally, based on the AutoRegressive Integrated Moving Average (ARIMA) model and historical tool wear values, multi-step-ahead forecasting of tool wear and RUL prediction are achieved. Results show that the proposed PINN with adaptive loss weighting achieves the best tool wear prediction performance, compared with PINNs without weight adjustment (fixed weights), without monotonicity constraints, or without physical consistency constraints. Moreover, ARIMA multi-step-ahead forecasts closely match the measured tool wear and outperform the GRU baseline. The findings of this paper lay the foundation for automation and even unmanned operation in deep-hole machining.

刀具磨损和剩余使用寿命（RUL）预测是保证加工质量和降低生产成本的关键，在深孔加工中起着重要作用。近年来，物理信息神经网络（PINN）在实现这一目标方面引起了人们的广泛关注。然而，基于物理的模型和数据驱动的模型之间的权重往往是经验设定的，这严重影响了训练的准确性和稳定性。为了解决这一问题，本文通过量化刀具磨损和RUL预测误差的方差，提出了一种自适应损失加权的PINN。首先，利用深孔掘进过程中的多通道信号提取深孔掘进过程的时域和频域特征；然后，计算刀具磨损与特征之间的相关系数进行特征选择，并结合切削行程信息形成数据集。其次，基于切削行程和刀面磨损值，采用最小二乘法建立刀具磨损率模型；该方程作为PINN的物理一致性约束。综合考虑数据驱动模型的数据损失、单调性损失和物理一致性损失，构造了总损失函数。最后，基于自回归综合移动平均（ARIMA）模型和刀具历史磨损值，实现了刀具磨损的多步预测和RUL预测。结果表明，与无权值调整（固定权值）、无单调性约束或无物理一致性约束的PINN相比，本文提出的具有自适应损失加权的PINN具有最佳的刀具磨损预测性能。此外，ARIMA多步提前预测与测量的工具磨损密切匹配，优于GRU基线。本文的研究结果为深孔加工的自动化甚至无人操作奠定了基础。

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引用次数: 0

Reducing tool wear in high-speed milling of Inconel 718 by optimizing flank-face coolant direction: A CFD-supported approach toward sustainable machining 通过优化侧面冷却剂方向来减少高速铣削Inconel 718的刀具磨损：cfd支持的可持续加工方法

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-01-21 DOI: 10.1016/j.jmapro.2026.01.065

Jingtian Mao , Kensuke Tsuchiya , Chikara Morigo , Shinji Yukinari , Hiroki Tahara , Yoshihide Kurashiki

This study investigates the impact of flank face coolant nozzle orientation on tool wear suppression in the high-speed milling of Inconel 718. Preliminary dry milling of Ti-6Al-4V with a Tool-Nose-Aimed (TNA) tool revealed severe flank wear at the bolt side edge. This failure mode persisted in Inconel 718, where the TNA tool suffered from severe adhesion and brittle fracture at this location under dry, flood and all high-pressure coolant (HPC) conditions except ultra-high pressure coolant (UHPC) at 20 MPa. Thermal and Computational Fluid Dynamics (CFD) simulations diagnosed the cause: the bolt side edge is a thermal throttling zone, and the TNA's coolant jet core deviates from this critical spot. Guided by this analysis, a novel Bolt-Side-Edge-Flank-Aimed (BSEFA) tool was designed. Its nozzle orientation was optimized to ensure the jet core directly impinges on the flank face of the bolt side edge, enhancing convective heat transfer through higher liquidity, velocity, and Turbulence Kinetic Energy (TKE). Experimentally, the BSEFA tool suppressed catastrophic failure, massive adhesion and reduced maximum flank wear (VB_max) within the wear land by 40–56% compared to the TNA tool. CFD results confirmed the mechanism, showing the optimized nozzle delivered superior coolant coverage (liquidity >0.95), higher velocity (>110 m/s), and drastically intensified turbulence (TKE increase >150%) at the target. This work establishes that strategic coolant orientation surpasses indiscriminate pressure increase. The BSEFA strategy enables high performance with minimal flow rate (<1.0 L/min), representing a > 95% reduction versus flood cooling, offering a highly efficient and sustainable machining strategy.

研究了高速铣削Inconel 718时，后端面冷却液喷嘴取向对刀具磨损抑制的影响。用工具头瞄准（TNA）工具对Ti-6Al-4V进行初步干铣削，发现螺栓侧面边缘存在严重的侧面磨损。这种失效模式在Inconel 718中持续存在，在干燥、洪水和所有高压冷却剂（HPC）条件下（20mpa的超高压冷却剂（UHPC）除外），TNA工具在该位置都存在严重的粘连和脆性断裂。热学和计算流体动力学（CFD）模拟诊断了原因：螺栓侧边缘是一个热节流区，TNA的冷却剂射流核心偏离了这个临界点。在此基础上，设计了一种新型的螺栓-侧面-边缘-侧翼瞄准（BSEFA）工具。它的喷嘴方向进行了优化，以确保射流核心直接撞击螺栓侧面边缘的侧面，通过更高的流动性、速度和湍流动能（TKE）来增强对流换热。实验表明，与TNA工具相比，BSEFA工具抑制了灾难性失效、大量粘附，并将磨损区域内的最大侧面磨损（VBmax）降低了40-56%。CFD结果证实了这一机制，优化后的喷嘴提供了更好的冷却剂覆盖范围（流动性>；0.95），更高的速度（>110 m/s），并大幅加剧了目标处的湍流（TKE增加了>；150%）。这项工作确立了战略性冷却剂定向优于无差别的压力增加。BSEFA策略以最小的流量（1.0 L/min）实现高性能，与洪水冷却相比减少了95%，提供了高效和可持续的加工策略。

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引用次数: 0

Robust monitoring of arc welding processes: A generalizable framework with DVAE and particle filter 弧焊过程的鲁棒监测：DVAE和粒子滤波的通用框架

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-01-20 DOI: 10.1016/j.jmapro.2026.01.039

Yue Cao , Hai Lin , YuMing Zhang

Arc welding processes are vital for continuous fabrication but are susceptible to disturbances that cause defects and compromise weld quality. Real-time monitoring is therefore essential, yet remains challenging due to complex visual patterns and the nonlinear, time-varying nature of welding dynamics. While deep learning offers potential, its reliance on large, labeled datasets, and in particular, on process- and application-specific tuning, limits industrial scalability. We question whether there exists a common approach to characterize major arc processes across different applications. If so, by observing and monitoring characteristic variables as process states under a unified framework, scalability can be greatly improved. This paper presents a robust monitoring framework generalizable across arc welding processes. It integrates deep latent representation learning to extract compact features from weld pool views in an unsupervised manner and employs Bayesian filtering to enhance robustness against sensory disturbances that are both sustained and fluctuating in arc welding, such as arc radiation and specular reflection from the weld pool surface. To this end, we employ a Dynamic Variational Autoencoder (DVAE), composed of a Convolutional Neural Network (CNN)-based encoder-decoder and a Long Short-Term Memory (LSTM)-based transition model, to jointly learn compact latent representations of weld pool images and their evolution under control inputs. This setup fuses instantaneous visual representations with process dynamics modeling, enabling compact latent features that satisfy both objectives. To achieve robust real-time inference, a specialized Particle Filter (PF) is introduced to jointly propagate the latent state and the hidden state of the LSTM transition model, preserving both current and historical process information while suppressing sensor disturbances such as arc rotation and specular reflection. This design is well suited to the relatively slow and inertial dynamics of arc welding, allowing the PF to effectively fuse model-based predictions with real-time observations. The proposed framework is validated on both GTAW and GMAW processes without process-specific customization, demonstrating its generalizability and robustness.

弧焊工艺对于连续制造是至关重要的，但它容易受到干扰，从而导致缺陷和降低焊接质量。因此，实时监测是必不可少的，但由于复杂的视觉模式和焊接动力学的非线性、时变性质，实时监测仍然具有挑战性。虽然深度学习提供了潜力，但它对大型标记数据集的依赖，特别是对特定于流程和应用程序的调优，限制了工业可扩展性。我们质疑是否存在一种共同的方法来表征跨不同应用的主要电弧过程。如果是这样，通过在统一的框架下将特征变量作为过程状态进行观察和监控，可以大大提高可扩展性。本文提出了一种适用于整个弧焊过程的鲁棒监测框架。它集成了深度潜在表示学习，以无监督的方式从焊池视图中提取紧凑的特征，并使用贝叶斯滤波来增强对电弧焊接中持续和波动的感觉干扰的鲁棒性，例如焊池表面的电弧辐射和镜面反射。为此，我们采用了一种动态变分自编码器（DVAE），由基于卷积神经网络（CNN）的编码器-解码器和基于长短期记忆（LSTM）的转换模型组成，共同学习焊接池图像的紧凑潜在表示及其在控制输入下的演变。这种设置将瞬时视觉表示与过程动力学建模融合在一起，实现了同时满足两个目标的紧凑潜在特征。为了实现鲁棒实时推断，引入了专用粒子滤波器（PF）来联合传播LSTM过渡模型的潜在状态和隐藏状态，在抑制传感器干扰（如电弧旋转和镜面反射）的同时保留当前和历史过程信息。这种设计非常适合相对缓慢的弧焊惯性动力学，使PF能够有效地将基于模型的预测与实时观测相融合。该框架在GTAW和GMAW过程上进行了验证，证明了其通用性和鲁棒性。

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引用次数: 0

Self-calibration method for rotary axis geometric errors in five-axis machine tools using gear-shaped workpieces 用齿轮形工件标定五轴机床旋转轴几何误差的方法

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-01-20 DOI: 10.1016/j.jmapro.2026.01.041

Kejian Chen , Sitong Xiang , Juntao Ni , Hainan Zhang , Jianguo Yang

With the continuous advancement of manufacturing precision requirements, the importance of machine tool accuracy inspection has become increasingly prominent. This study proposes a self-calibration approach for rotary axis geometric errors using a gear-shaped workpiece. By designing a gear-shaped workpiece featuring 12 arc surfaces, an error identification model is established, the study focuses on the contributions of the machine tool's linear axes and C-axis geometric errors to the probing deviations. Combined with on-machine measurement technology using a touch-trigger probe, this method achieves decoupled identification of linear axis errors, workpiece geometric errors, and rotary axis geometric errors. Specifically, the rotary axis geometric errors include 4 position-independent geometric errors (PIGEs) and 6 position-dependent geometric errors (PDGEs). The workpiece incorporates square groove features to facilitate re-clamping and alignment, enhancing the efficiency of periodic accuracy calibration. The proposed method's effectiveness is further confirmed through uncertainty analysis and comparative experimental verification against ball-bar and artifact-based identification methods.

随着制造精度要求的不断提高，机床精度检测的重要性日益突出。提出了一种基于齿轮形工件的旋转轴几何误差自校正方法。通过设计具有12个圆弧面的齿轮形工件，建立了误差辨识模型，重点研究了机床直线轴和c轴几何误差对测头误差的贡献。该方法结合使用触摸触发探头的机上测量技术，实现了对直线轴误差、工件几何误差和旋转轴几何误差的解耦辨识。其中，旋转轴几何误差包括4个位置无关几何误差（PIGEs）和6个位置相关几何误差（PDGEs）。工件采用方槽特征，便于重新夹紧和对准，提高了周期性精度校准的效率。通过不确定度分析以及与基于球棒和伪像的识别方法的对比实验验证，进一步证实了该方法的有效性。

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引用次数: 0

A study on mitigation of tunneling defects and investigation on the mechanical behavior of double-sided friction stir welded Al 2014 plates Al - 2014双面搅拌摩擦焊板隧道缺陷缓解及力学行为研究

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-01-20 DOI: 10.1016/j.jmapro.2026.01.027

Raja Dharavathu , Kishora Shetty , Gopinath Muvvala

Friction stir welding (FSW) is a solid-state joining technique particularly effective for alloys that are difficult to weld by conventional fusion processes. However, welding of thick plates often necessitates robust kinematic systems, and steep thermal gradients can induce high flow stress near the tool tip, leading to tunneling or void defects. This study focuses on minimizing such defects and improving the mechanical performance of 8 mm thick 2014-T6 aluminum alloy joints produced by double-sided FSW. Process optimization was achieved by varying pin lengths, reducing welding speeds, and increasing the tool tilt angle from 0° to 2°, which enhanced plastic flow and material consolidation. Defect-free joints were obtained at welding speeds of 5, 10, and 20 mm/min with a rotational speed of 900 rpm and a 2° tilt angle. Despite the absence of macroscopic defects, the as-welded joints exhibited reduced tensile strength due to overaging and coarsening of Al₂Cu precipitates within the nugget zone (NZ), as confirmed by TEM. Comprehensive microstructural characterization using optical microscopy SEM, EDS and EBSD revealed precipitate dissolution and dynamic recrystallization within the NZ. Post-weld heat treatment (PWHT), consisting of solution treatment at 500 °C followed by artificial aging at 160 °C for 18 h, significantly enhanced strength and hardness owing to the re-precipitation of semi-coherent

θ^{'}

phases, though with a marginal decrease in ductility. Tensile testing with 2D digital image correlation indicated a strain hardening exponent of 0.25 in the as-welded NZ and 0.12 after PWHT, reflecting a transition from localized to more uniform plastic deformation behavior.

搅拌摩擦焊（FSW）是一种固态连接技术，对传统熔合工艺难以焊接的合金特别有效。然而，厚板的焊接通常需要强大的运动系统，陡峭的热梯度会在刀尖附近引起高流动应力，导致隧道或空洞缺陷。本研究的重点是减少这些缺陷，提高双面摩擦焊生产的8mm厚2014-T6铝合金接头的力学性能。通过改变销钉长度、降低焊接速度、将刀具倾斜角度从0°增加到2°，实现了工艺优化，从而增强了塑性流动和材料固结。焊接速度为5、10和20 mm/min，转速为900 rpm，倾斜角度为2°，焊接接头无缺陷。透射电镜证实，尽管没有宏观缺陷，但由于熔核区（NZ）内Al2Cu析出物的过时效和粗化，焊接接头的抗拉强度降低。利用光学显微镜、扫描电镜、能谱仪和电子能谱仪对NZ进行了全面的微观结构表征，发现了析出物溶解和动态再结晶。焊后热处理（PWHT）由500°C固溶处理和160°C人工时效18 h组成，由于半相干θ′相的再析出，强度和硬度显著提高，但塑性略有下降。二维数字图像相关拉伸试验表明，焊接状态下的NZ应变硬化指数为0.25，PWHT后的应变硬化指数为0.12，反映了局部塑性变形行为向更均匀塑性变形行为的转变。

{"title":"A study on mitigation of tunneling defects and investigation on the mechanical behavior of double-sided friction stir welded Al 2014 plates","authors":"Raja Dharavathu , Kishora Shetty , Gopinath Muvvala","doi":"10.1016/j.jmapro.2026.01.027","DOIUrl":"10.1016/j.jmapro.2026.01.027","url":null,"abstract":"<div><div>Friction stir welding (FSW) is a solid-state joining technique particularly effective for alloys that are difficult to weld by conventional fusion processes. However, welding of thick plates often necessitates robust kinematic systems, and steep thermal gradients can induce high flow stress near the tool tip, leading to tunneling or void defects. This study focuses on minimizing such defects and improving the mechanical performance of 8 mm thick 2014-T6 aluminum alloy joints produced by double-sided FSW. Process optimization was achieved by varying pin lengths, reducing welding speeds, and increasing the tool tilt angle from 0° to 2°, which enhanced plastic flow and material consolidation. Defect-free joints were obtained at welding speeds of 5, 10, and 20 mm/min with a rotational speed of 900 rpm and a 2° tilt angle. Despite the absence of macroscopic defects, the as-welded joints exhibited reduced tensile strength due to overaging and coarsening of Al<sub>2</sub>Cu precipitates within the nugget zone (NZ), as confirmed by TEM. Comprehensive microstructural characterization using optical microscopy SEM, EDS and EBSD revealed precipitate dissolution and dynamic recrystallization within the NZ. Post-weld heat treatment (PWHT), consisting of solution treatment at 500 °C followed by artificial aging at 160 °C for 18 h, significantly enhanced strength and hardness owing to the re-precipitation of semi-coherent <span><math><msup><mi>θ</mi><mo>′</mo></msup></math></span> phases, though with a marginal decrease in ductility. Tensile testing with 2D digital image correlation indicated a strain hardening exponent of 0.25 in the as-welded NZ and 0.12 after PWHT, reflecting a transition from localized to more uniform plastic deformation behavior.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"159 ","pages":"Pages 460-480"},"PeriodicalIF":6.8,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146024737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Surface analysis and assessment in large-amplitude longitudinal ultrasonic vibration-assisted milling of UD-CF/PEEK 大振幅纵向超声振动辅助铣削UD-CF/PEEK的表面分析与评价

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-01-20 DOI: 10.1016/j.jmapro.2026.01.058

Jin Zhang , Taimin Luo , Daixin Luo , Chenjie Deng , Guibao Tao , Huajun Cao

Ultrasonic vibration-assisted milling (UVAM) shows strong potential as an advanced processing technology for the efficient precision machining of carbon-fiber-reinforced-polyetheretherketone (CF/PEEK). Large-amplitude vibrations of 10 to 20 μm create more separation between the tool and workpiece, reducing milling forces and increasing chip removal energy. However, developing large-amplitude and high-efficiency ultrasonic vibration systems remains a challenge for UVAM. To address this, a large-amplitude longitudinal ultrasonic vibration-assisted milling (LALUVAM) toolholder was designed and manufactured in this research. To evaluate this toolholder for milling CF/PEEK with different fiber orientations, milling forces, temperature and surface quality were selected as multidimensional analysis metrics. The findings reveal that the force and temperature are constant at 52 N and 60 °C for a fiber orientation of 45° with a feed speed varying in the range of 600 to 1000 mm/min. The two-dimensional (2D) surface roughness values of machined surfaces with different fiber orientations, when utilizing a 15 μm amplitude ultrasonic toolholder, exhibit considerable variation across different measurement directions and regions. Consequently, it is recommended to employ three-dimensional (3D) surface roughness measurements to more accurately characterize the quality of the machined surfaces. Additionally, the size of the measurement area was found to significantly impact the 3D roughness results for different fiber orientations. Optimal measurement areas were determined to be 640 × 640 μm² for 0° and 45° fiber orientations, 1200 × 1200 μm² for the 90° fiber orientation, and 4022 × 640 μm² for the 135° fiber orientation. Surface defects are observed by scanning electron microscopy (SEM) to explain the cause of surface roughness variation. Moreover, high efficiency and quality milling of UD-CF/PEEK can be realized at a feed speed of 700 mm/min.

超声振动辅助铣削（UVAM）作为一种高效精密加工碳纤维增强聚醚醚酮（CF/PEEK）的先进加工技术，显示出强大的潜力。10 ~ 20 μm的大振幅振动使刀具和工件之间更加分离，降低铣削力，增加切屑去除能量。然而，开发大振幅、高效率的超声振动系统仍然是UVAM面临的挑战。为此，设计并制造了一种大振幅纵向超声振动辅助铣削（LALUVAM）刀架。以铣削力、铣削温度和铣削表面质量为多维分析指标，对不同纤维取向的CF/PEEK铣削效果进行了评价。结果表明，当纤维取向为45°时，力和温度在52 N和60°C下恒定，进给速度在600至1000 mm/min范围内变化。当使用振幅为15 μm的超声刀架时，不同纤维取向的加工表面的二维表面粗糙度值在不同的测量方向和区域表现出相当大的变化。因此，建议采用三维（3D）表面粗糙度测量来更准确地表征加工表面的质量。此外，发现测量区域的大小对不同纤维取向的三维粗糙度结果有显著影响。最佳测量面积分别为：0°和45°光纤方向640 × 640 μm2, 90°光纤方向1200 × 1200 μm2, 135°光纤方向4022 × 640 μm2。利用扫描电子显微镜（SEM）观察表面缺陷，解释表面粗糙度变化的原因。当进给速度为700 mm/min时，可实现UD-CF/PEEK的高效率、高质量铣削。

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引用次数: 0

Improving curved surface machining quality of blasting erosion arc milling by applying working fluid blockers 应用工作液阻断剂改善喷蚀弧铣曲面加工质量

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-01-20 DOI: 10.1016/j.jmapro.2026.01.056

Lin Gu , Kelin Li , Guojian He , Lijie Jiang , Xiaoka Wang

Electrical Arc Machining (EAM) is a promising method for processing difficult-to-cut materials, offering a satisfactory material removal rate and high efficiency. It has been applied in the aerospace industry to remove most of the residue from the blank to save machining time and cost. However, for aerospace parts with complex curved surfaces, such as blades, turbine disks, and impellers, it's prone to lead to intensive working fluid leakage during machining. This fluid leakage adversely recedes the arc breaking effect and results in an unacceptable coarse surface. To address this issue, this study defines the criteria for achieving good machined surface by EAM and proposes the working fluid guiding strategy including internal, external, and combined guiding approaches. The flow field is simulated and a blocker is designed to study the working fluid guiding strategy for the suppression of flushing deficiency. The results indicate that the combined strategy yields the most significant improvement effect, increasing the ratio of effective flushing by 1.2 times and desirable discharge rate by over 35%. Additionally, it noticeably reduces the surface roughness and the thickness of the recast layer. The validity of this novel approach is further demonstrated through the machining of a three-dimensional flow impeller sample using Blasting Erosion Arc Machining (BEAM) with the working fluid guiding strategy.

电弧加工（EAM）是一种很有前途的加工难切削材料的方法，具有令人满意的材料去除率和高效率。它已应用于航空航天工业，以去除毛坯中的大部分残留物，节省加工时间和成本。然而，对于具有复杂曲面的航空航天零件，如叶片、涡轮盘和叶轮，在加工过程中容易导致大量的工作液泄漏。这种流体泄漏对断弧效果不利，并导致不可接受的粗糙表面。为了解决这一问题，本研究定义了EAM获得良好加工表面的标准，并提出了包括内部导向、外部导向和组合导向在内的工作流体导向策略。模拟了流场，设计了阻挡剂，研究了抑制冲洗不足的工质导液策略。结果表明，该组合策略改善效果最显著，有效冲洗率提高1.2倍，理想排放率提高35%以上。此外，它显著降低了表面粗糙度和重铸层的厚度。通过采用工作流体导向策略对三维流动叶轮进行喷蚀弧加工（BEAM），进一步验证了该方法的有效性。

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引用次数: 0

Viscoelastic modeling and mechanism analysis of unbalanced filling in geometrically balanced injection molds 几何平衡注射模不平衡充型的粘弹性建模及机理分析

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-01-19 DOI: 10.1016/j.jmapro.2026.01.019

Shaozhen Hua, Hui Li, Huabo Liu

Unbalanced filling in injection molding of geometrically balanced molds is a bad phenomenon that leads defects and has not been fully understanding. In this work, numerical simulation technique is taken to explore unbalanced filling. The melt during filling is considered to be incompressible, non-isothermal and viscoelastic fluids with Giesekus viscoelastic model to described its rheological character. A coupled finite volume method (FVM) and moving particle simulation (MPS) method was developed. Melt and air flow in cavity are treated as a whole flow field and solved by FVM, while the melt front is captured by the moving particles method. A benchmark case for the MPS method was then used to validate the developed algorithm. Additionally, the melt front progression, gate pressure, temperature distribution, and viscoelastic characteristics during injection molding were simulated and compared to experimental results or other numerical results. Results demonstrate that the developed algorithm can accurately simulate the non-isothermal viscoelastic injection molding process of the melt. Subsequently, the developed algorithm was applied to simulate both balanced and unbalanced filling processes during injection molding. Analysis of shear rate, temperature, and the first and second normal stress differences confirmed the validity of the established theory that shear-induced heating drives unbalanced filling. Furthermore, numerical results demonstrated that in tapered tubular runners, the first normal stress difference promotes balanced flow in naturally balanced runner systems, while the second normal stress difference induces unbalanced filling.

几何平衡模具注射成型中的不平衡填充是一种导致缺陷的不良现象，目前尚未得到充分认识。在这项工作中，采用数值模拟技术来研究不平衡填充。将填充过程中的熔体视为不可压缩、非等温粘弹性流体，用Giesekus粘弹性模型描述其流变特性。提出了一种有限体积法（FVM）和运动粒子模拟（MPS）的耦合方法。将熔体和空腔内空气流动作为一个整体流场，采用FVM方法求解，熔体前缘采用运动粒子法捕获。然后使用MPS方法的基准案例来验证所开发的算法。此外，还模拟了注射成型过程中熔体前缘进程、浇口压力、温度分布和粘弹性特性，并与实验结果或其他数值结果进行了比较。结果表明，该算法能够准确地模拟熔体的非等温粘弹性注射成型过程。随后，将所开发的算法应用于模拟注射成型过程中的平衡和不平衡填充过程。对剪切速率、温度和第一、第二正应力差的分析证实了剪切加热驱动不平衡充填的理论的有效性。此外，数值结果表明，在锥形管流道中，第一个法向应力差促进了自然平衡流道系统的平衡流动，而第二个法向应力差导致了不平衡填充。

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引用次数: 0

A review on tufting technology for 3D preforms: Manufacturing, process parameters and performance implications 三维预成形簇封技术综述：制造、工艺参数和性能影响

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-01-19 DOI: 10.1016/j.jmapro.2026.01.022

Jian Hu , Hao Shen , Xavier Legrand , Peng Wang

Tufting is a promising technology for reinforcing composite materials, offering notable advantages in both performance and cost-effectiveness. It effectively improves the delamination resistance and impact tolerance of multi-layered composite structures, making it highly applicable across a range of industries, including transportation, construction, energy, and defence. In recent years, significant advancements have been made in the development of tufted multi-layered composites. Nevertheless, there remain gaps in the systematic understanding of the tufting process. This review provides an overview of the current stage of tufting technology, including its definition, key tufting parameters, and the potential damage to tufted composites. Additionally, the paper summarises current research on the forming and simulation of tufted preforms. Future research efforts should focus on optimising the tufting process, standardising techniques, and expanding its industrial applications.

簇绒是一种很有前途的复合材料增强技术，在性能和成本效益方面都有显著的优势。它有效地提高了多层复合材料结构的抗分层能力和抗冲击能力，使其在交通运输、建筑、能源和国防等一系列行业中具有很高的适用性。近年来，簇状多层复合材料的发展取得了重大进展。然而，在对簇绒过程的系统认识方面仍然存在差距。本文综述了现阶段簇绒技术的发展概况，包括簇绒技术的定义、关键簇绒参数以及簇绒复合材料的潜在危害。此外，本文还对簇状预制件的成形和仿真研究现状进行了综述。未来的研究工作应集中在优化簇绒工艺、标准化技术和扩大其工业应用上。

引用次数: 0

High-performance CoCrFeNi/6061 aluminum matrix composites fabricated by cold spray-friction stir processing composite additive manufacturing 采用冷喷涂-搅拌摩擦复合增材制造制备高性能CoCrFeNi/6061铝基复合材料

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-01-19 DOI: 10.1016/j.jmapro.2026.01.048

Peng Han , Jiaxing Duan , Qianzhi Ma , Jia Lin , Fengming Qiang , Wen Wang , Ke Qiao , Kuaishe Wang

To overcome the poor strength-ductility trade-off in ceramic particle-reinforced aluminum matrix composites (AMCs), this study fabricated CoCrFeNi particle-reinforced AMCs using cold spray and cold spray-friction stir processing composite additive manufacturing (CFAM) technology, respectively. The microstructures and mechanical properties of the AMCs were systematically optimized through a short-time T6 heat treatment. A comprehensive microstructural characterization of the AMCs was performed using X-ray diffraction, scanning electron microscopy, electron backscatter diffraction, and transmission electron microscopy. The tensile strength was evaluated and the strengthening mechanism was determined. The results indicated that the cold-sprayed AMCs contained significant porosity and a highly inhomogeneous grain structure. The CoCrFeNi/Al interfaces were primarily characterized by mechanical bonding, with no significant interfacial reactions observed. Comparatively, the AMCs fabricated by CFAM demonstrated significantly refined, homogenized, and densified microstructures, with an average grain size of 1.46 μm. Enhanced elemental interdiffusion occurred at the CoCrFeNi/Al interface, and numerous intermetallic compounds, specifically Al₇Cr and Al₉(Co,Fe,Ni)₂, were found to be homogeneously dispersed within the Al matrix. After short-time T6 heat treatment, the average grain size of the AMCs fabricated by CFAM experienced slight growth, reaching an average of 1.92 μm. Concurrently, interfacial reaction at the CoCrFeNi/Al interface intensified, leading to the formation of a dual-layer interfacial reaction zone. This zone consisted of an inner layer enriched with α-Al(Co,Cr,Fe,Ni)Si and an outer layer enriched with Al₉(Co,Fe,Ni)₂ and Al₁₃(Co,Fe,Ni)₄. Meanwhile, the tensile strength of the AMCs fabricated by CFAM improved by 98 MPa compared to the pre-heat-treated state, reaching 368 MPa. This enhancement was primarily attributed to the short-time T6 heat treatment achieving concurrent optimization of the CoCrFeNi/Al interfacial reaction products and the precipitated phase within the Al matrix, thereby achieving excellent strength and elongation in the AMCs. In summary, this study developed an effective approach for fabricating high-performance AMCs reinforced with CoCrFeNi particles.

为了克服陶瓷颗粒增强铝基复合材料（AMCs）强度-延性差的问题，本研究分别采用冷喷涂和冷喷涂-搅拌摩擦加工复合增材制造（CFAM）技术制备了CoCrFeNi颗粒增强铝基复合材料。通过T6短时间热处理，系统优化了复合材料的组织和力学性能。利用x射线衍射、扫描电子显微镜、电子背散射衍射和透射电子显微镜对AMCs进行了全面的微观结构表征。评估了材料的抗拉强度，确定了强化机理。结果表明，冷喷涂后的碳纤维具有显著的孔隙率和高度不均匀的晶粒结构。CoCrFeNi/Al界面以机械键合为主，未观察到明显的界面反应。相比之下，CFAM制备的碳纤维具有明显的细化、均匀化和致密化的微观结构，平均晶粒尺寸为1.46 μm。元素间扩散增强发生在CoCrFeNi/Al界面，大量金属间化合物，特别是Al7Cr和Al9(Co,Fe,Ni)2，均匀分布在Al基体中。经过T6短时间热处理后，CFAM制备的碳纤维的平均晶粒尺寸略有增大，达到1.92 μm。同时，CoCrFeNi/Al界面处的界面反应增强，形成了双层界面反应区。该带由富含α-Al(Co,Cr,Fe,Ni)Si的内层和富含Al9(Co,Fe,Ni)2和Al13(Co,Fe,Ni)4的外层组成。同时，CFAM制备的碳纤维的抗拉强度比热处理前提高了98 MPa，达到了368 MPa。这种增强主要是由于短时间T6热处理同时优化了CoCrFeNi/Al界面反应产物和Al基体内的析出相，从而获得了优异的强度和伸长率。总之，本研究开发了一种制备CoCrFeNi颗粒增强高性能amc的有效方法。

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