Journal of Manufacturing Processes最新文献_第8页

Evaluating perception intelligence of intelligentized robotic welding system using comprehensive evaluation approach based on fuzzy AHP 基于模糊层次分析法的智能机器人焊接系统感知智能评价方法

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2025-12-19 DOI: 10.1016/j.jmapro.2025.10.115

Qiang Liu, Yuqing Xu, Shanben Chen

Intelligentized robotic welding system (IRWS) has been playing an important role in manufacturing field, as a result, IRWS is evolving towards higher levels of intelligence. Accurately evaluating and mastering the intelligence level of IRWS provides a significant premise for improving the system's capabilities in perception, controlling, and decision making. As far as we know, this paper first proposes a universal framework for evaluating the perception intelligence of IRWS. In the proposed framework, which classifies the degree of perception intelligence in IRWS into four levels:

V =

{Humanoid intelligence, Bionic intelligence, Mechanical intelligence, Weak intelligence}, by combining fuzzy logic theory and analytic hierarchy process (AHP). In detail, the index system for perception intelligence is divided into two hierarchy levels using the AHP method, and index systems are established separately for each level. Then, the decision makers' language variables and relative importance weights of the factors in each level is established by fuzzy logic theory. Combining the AHP and fuzzy logic theory can obtain an accurate evaluation of the perception intelligence of the IRWS. In addition, a tungsten inert gas (TIG) welding system is taken as a case to illustrate the proposed framework. The results show that the proposed method can scientifically, and reliably evaluate the perception intelligence level of the welding system. The proposed method can be used by welding system engineers especially managers as an effective tool to master and improve system intelligence, furthermore, the proposed evaluation framework can provide as a reference for practitioners in other fields of manufacturing industry.

智能机器人焊接系统（IRWS）在制造领域发挥着重要的作用，因此，IRWS正朝着更高的智能水平发展。准确评估和掌握IRWS的智能化水平，是提高系统感知、控制和决策能力的重要前提。据我们所知，本文首先提出了一个评估IRWS感知智能的通用框架。该框架结合模糊逻辑理论和层次分析法（AHP），将IRWS的感知智能程度划分为V={Humanoid intelligence, Bionic intelligence, Mechanical intelligence， Weak intelligence}四个层次。采用层次分析法将感知智能指标体系划分为两个层次，每个层次分别建立指标体系。然后，运用模糊逻辑理论确定决策者的语言变量和各层次因素的相对重要性权重。将层次分析法与模糊逻辑理论相结合，可以得到对IRWS感知智能的准确评价。此外，还以钨惰性气体（TIG）焊接系统为例说明了所提出的框架。结果表明，该方法能够科学、可靠地评价焊接系统的感知智能水平。该方法可作为焊接系统工程师特别是管理人员掌握和提高系统智能的有效工具，同时也可为制造业其他领域的从业者提供参考。

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引用次数: 0

Physics-informed Fourier-Gaussian-Laplacian neural network for temperature field reconstruction and accurate prediction in laser wire additive manufacturing 基于物理信息的傅里叶-高斯-拉普拉斯神经网络在激光线材增材制造中的温度场重建和精确预测

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2025-12-19 DOI: 10.1016/j.jmapro.2025.12.031

Shoulan Yang , Zhengjingxuan Liao , Ze Wang , Weiwei Liu , Fengtao Wang , Madan Kumar , Shoukang Yu , Hongchao Zhang , Shitong Peng

Different from the relatively smooth and diffusion-dominated thermal evolution observed in powder-fed processes, laser wire additive manufacturing (LWAM) employs a continuous wire that directly couples with both the energy beam and the molten pool, generating more localized heat input and substantial thermal accumulation. Moreover, the process involves frequent transitions between wire transfer modes such as stable wire penetration, liquid bridge, and droplet, which dynamically modulate energy absorption and melt-pool behavior. Although these complex transfer modes are not directly simulated, they collectively shape the resulting surface temperature field, leading to abrupt, non-stationary fluctuations, higher variability, and stronger nonlinearity. Consequently, accurate prediction of the LWAM thermal field becomes particularly challenging due to these intrinsic process dynamics. To address these challenges, we propose a novel Fourier-Gaussian-Laplacian Physics-Informed Neural Network (FGL-PINN), which integrates Fourier feature encoding, Gaussian random feature loss, and Laplacian regularization into a unified architecture. This design enhances the model's sensitivity to high-frequency temperature gradients while reinforcing the physical consistency of heat diffusion processes. A series of systematic LWAM experiments is conducted to establish a high-quality process window, from which nine representative process parameter combinations were selected for training and testing FGL-PINN. Furthermore, we perform an ablation experiment to verify the contribution of each module. Experimental results demonstrate that FGL-PINN consistently achieves high prediction accuracy across all tested conditions, with R² values exceeding 0.99 and RMSE ranging from 5.41 to 12.90. The proposed framework offers a reliable and generalizable solution for high-fidelity temperature field prediction in LWAM.

与粉末喂料过程中观察到的相对光滑和扩散主导的热演化不同，激光丝材增材制造（LWAM）采用连续的丝材，直接与能量束和熔池耦合，产生更多的局部热输入和大量的热积累。此外，这一过程涉及钢丝传递模式之间的频繁转换，如稳定的钢丝穿透、液体桥和液滴，这些模式动态地调节了能量吸收和熔池行为。虽然这些复杂的传递模式不能直接模拟，但它们共同塑造了产生的表面温度场，导致突然的、非平稳的波动、更高的变异性和更强的非线性。因此，由于这些内在的过程动力学，准确预测LWAM热场变得特别具有挑战性。为了解决这些挑战，我们提出了一种新的傅立叶-高斯-拉普拉斯物理信息神经网络（FGL-PINN），它将傅立叶特征编码、高斯随机特征损失和拉普拉斯正则化集成到一个统一的体系结构中。这种设计提高了模型对高频温度梯度的敏感性，同时加强了热扩散过程的物理一致性。通过一系列系统的LWAM实验，建立了一个高质量的工艺窗口，从中选择了9个具有代表性的工艺参数组合，对FGL-PINN进行了训练和测试。此外，我们还进行了烧蚀实验来验证每个模块的贡献。实验结果表明，FGL-PINN在所有测试条件下均具有较高的预测精度，R2值均超过0.99，RMSE范围为5.41 ~ 12.90。该框架为LWAM中的高保真温度场预测提供了一种可靠的、可推广的解决方案。

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引用次数: 0

Prediction and control of pointing accuracy in precision opto-mechanical systems with uncertainty reduction 减少不确定度的精密光机械系统指向精度预测与控制

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2025-12-19 DOI: 10.1016/j.jmapro.2025.12.038

Yuchen Ai , Qingchao Sun , Zhihao Fan , Shenhua Ma , Zibo Sun , Zhikang Huang , Xiaokai Mu , Wei Sun

Pointing accuracy is a core performance metric for opto-mechanical systems, yet its stability is often compromised by multi-source uncertainties during assembly. This paper proposes a novel prediction and control method with uncertainty reduction to enhance alignment accuracy and efficiency. The approach includes: (1) identifying uncertainty sources through system architecture analysis and quantifying them via multivariate distribution feature extraction and subinterval sampling; (2) establishing a kinematic model using the D-H method and building a pointing accuracy prediction model that integrates Nataf decomposition and Polynomial Chaos Expansion to determine the theoretical system accuracy limit; (3) introducing an alignment control strategy to reduce preload uncertainty, enabling performance-driven inverse determination and adaptive regulation. Alignment experimental validation shows that the pointing accuracy was improved from 329.61 arc-seconds to 195.05 arc-seconds (40.82 % enhancement), approaching the theoretical limit of 177.48 arc-seconds. The approach significantly improves alignment reliability and efficiency, offering theoretical support for uncertainty-reduced prediction and control in opto-mechanical systems.

指向精度是光机械系统的核心性能指标，但其稳定性往往受到装配过程中多源不确定性的影响。为了提高对准精度和效率，提出了一种减少不确定性的预测控制方法。该方法包括：(1)通过系统架构分析识别不确定性源，并通过多元分布特征提取和子区间采样对不确定性源进行量化；(2)采用D-H法建立运动学模型，建立结合Nataf分解和多项式混沌展开的指向精度预测模型，确定理论系统精度极限；(3)引入对准控制策略，降低预紧力不确定性，实现性能驱动的逆确定和自适应调节。对准实验验证表明，对准精度由329.61弧秒提高到195.05弧秒，提高了40.82%，接近理论极限177.48弧秒。该方法显著提高了对准的可靠性和效率，为光电系统的降低不确定性预测和控制提供了理论支持。

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引用次数: 0

Damage evolution mechanism of different fiber orientations of CFRP hole wall surface and suppression strategy in CFRP/Ti stacks drilling CFRP/Ti叠层钻井不同纤维取向CFRP孔壁损伤演化机理及抑制策略

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2025-12-19 DOI: 10.1016/j.jmapro.2025.12.029

Yuanxiao Li , Feng Jiao , Junjie Shen , Ziqiang Zhang , Huanfang Wang

CFRP/Ti stacks are extensively employed in aircraft structural components in the aerospace field, and the surface quality of mechanical connection holes greatly affects their service performance. For anisotropic CFRP, the formation and evolution of final hole wall defects under different fiber orientations are different. Understanding the damage evolution mechanism of CFRP hole surface in different fiber orientations is a prerequisite for damage suppression. In this paper, the effects of fiber fracture mode, drilling force, drilling temperature, hole wall rebound effect, tool wear and Ti chip evacuation process on the damage formation and evolution of different fiber orientations on CFRP hole wall surface were studied. The roughness variation factor (RVF_θ) is used to characterize the evolution process of hole wall roughness. Finally, the damage suppression strategy of ultrasonic and low-frequency combined vibration-assisted drilling (CVAD) is proposed. Results demonstrate that the final surface of CFRP is deteriorated in different degrees near the four fiber directions of 0°, 45°, 90° and 135°, especially in the reverse fiber cutting direction near 135°, the RVF_θ is the largest. The CVAD can decrease average drilling force and temperature, change Ti chips morphology, extend tool life and significantly reduce RVF_θ of CFRP at different fiber orientations, effectively inhibiting the deterioration of hole wall quality caused by Ti drilling phase, which can provide reference for improving the CFRP hole wall surface quality.

CFRP/Ti叠层广泛应用于航空航天领域的飞机结构件中，其机械连接孔的表面质量对叠层的使用性能影响很大。对于各向异性CFRP，不同纤维取向下最终孔壁缺陷的形成和演化是不同的。了解CFRP孔表面在不同纤维取向下的损伤演化机制是抑制损伤的前提。本文研究了纤维断裂方式、钻孔力、钻孔温度、孔壁回弹效应、刀具磨损和Ti屑排出过程对CFRP孔壁不同纤维取向损伤形成和演化的影响。粗糙度变化因子（RVFθ）用于表征孔壁粗糙度的演化过程。最后，提出了超声与低频联合振动辅助钻井（CVAD）的损伤抑制策略。结果表明：碳纤维布的最终表面在0°、45°、90°和135°四个纤维方向附近都有不同程度的劣化，特别是在135°附近的反纤维切割方向，RVFθ最大；CVAD可降低平均钻削力和钻削温度，改变Ti屑形貌，延长刀具寿命，显著降低不同纤维取向CFRP的RVFθ，有效抑制Ti钻削阶段引起的孔壁质量恶化，可为提高CFRP孔壁表面质量提供参考。

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引用次数: 0

Simultaneous tool wear condition and surface roughness prediction under limited samples 有限样品条件下刀具同时磨损状态及表面粗糙度预测

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2025-12-19 DOI: 10.1016/j.jmapro.2025.12.032

Hanbo Yang , Gedong Jiang , Wenwen Tian , Xuesong Mei , A.Y.C. Nee , S.K. Ong

In computer numerical control (CNC) machining, tool wear degrades surface roughness and poor surface condition accelerates tool wear. While tool wear and surface roughness are inherently coupled, simultaneous prediction of both factors remains challenging due to reliance on multiple intrusive sensors and extensive data collection requirements. To address this issue, the simultaneous tool wear condition and surface roughness prediction (STWC-SRP) framework under limited samples is proposed. First, the multi-domain features are extracted and selected from the spindle current signals. Next, the framework employs the conditional diffusion-based data generation method to create synthetic samples that preserve the underlying relationships between tool wear states and features of spindle current signals. The synthetic sample selection and surface roughness labeling method identifies the high-fidelity synthetic samples and computes corresponding surface roughness values for the synthetic samples. Finally, leveraging the real and the selected synthetic samples, the multi-task model achieves the simultaneous tool wear and surface roughness prediction, with a mean squared error of 0.0179 for surface roughness prediction, and accurate tool wear classification with no misidentifications across tested scenarios. Experimental results demonstrate that the STWC-SRP framework correctly identifies all tool wear conditions and achieves a Mean Squared Error (MSE) of 0.0179 and a Mean Absolute Error (MAE) of 0.1003 for surface roughness prediction, outperforming conventional approaches and confirming its practical applicability in industrial scenarios under limited samples.

在计算机数控（CNC）加工中，刀具磨损降低了表面粗糙度，而不良的表面状况加速了刀具的磨损。虽然工具磨损和表面粗糙度本质上是耦合的，但由于依赖于多个侵入式传感器和广泛的数据收集要求，同时预测这两个因素仍然具有挑战性。针对这一问题，提出了有限样本条件下刀具磨损状态与表面粗糙度同步预测（STWC-SRP）框架。首先，从主轴电流信号中提取并选择多域特征；接下来，该框架采用基于条件扩散的数据生成方法来创建合成样本，这些样本保留了刀具磨损状态与主轴电流信号特征之间的潜在关系。合成样品选择和表面粗糙度标记方法对高保真合成样品进行识别，并计算合成样品相应的表面粗糙度值。最后，利用真实样本和选择的合成样本，多任务模型实现了刀具磨损和表面粗糙度的同时预测，表面粗糙度预测的均方差为0.0179，并且在测试场景中实现了准确的刀具磨损分类，没有错误识别。实验结果表明，STWC-SRP框架正确识别了所有刀具磨损状况，表面粗糙度预测的均方误差（MSE）为0.0179，平均绝对误差（MAE）为0.1003，优于传统方法，证实了其在有限样本工业场景下的实际适用性。

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引用次数: 0

Strengthening vat photopolymerization-fabricated SiC by particle gradation and reactive melt infiltration 用颗粒级配和反应性熔体渗透强化还原光聚合制备SiC

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2025-12-18 DOI: 10.1016/j.jmapro.2025.12.042

Junchao He , Ce Sun , Jinyi Geng , Huajun Sun , Xiao Han , Lixia Yang , Annan Chen , Xiaolong Gong , Peng Chen , Kai Liu , Yusheng Shi

Vat photopolymerization (VPP) technology holds significant potential for fabricating high-precision SiC components with complex structures. However, SiC, as a covalently bonded compound, exhibits low sintering activity, which greatly limits the densification process and its mechanical property. In this paper, a new bimodal particle size SiC combined with reactive melt infiltration (RMI) for fabricating high-performance SiC is developed. Compared with uniform particle sizes, a rational graded particle size distribution contributes to altering the single failure mode and enhancing the mechanical properties of SiC. During RMI, the incorporation of appropriate fine particles reduces the aggregation of residual silicon within SiC matrix, which confines the reaction between pyrolytic carbon and molten silicon to localized regions. This facilitates concentrated growth of the reinforcing β-SiC phase, serving as the key mechanism for performance improvement. The final SiC achieve a bulk density of 2.996 g/cm³ and a maximum flexural strength of 369.67 MPa, which reflecting an approximate 83 % improvement in strength. This method offers an effective solution for fabricating high-strength SiC with complex structures using VPP technology.

还原光聚合（VPP）技术在制造具有复杂结构的高精度SiC元件方面具有巨大的潜力。然而，碳化硅作为共价键合化合物，烧结活性较低，极大地限制了致密化过程及其力学性能。本文提出了一种新的双峰粒径碳化硅与反应熔体渗透相结合的高性能碳化硅制备方法。与均匀粒度相比，合理的分级粒度分布有助于改变SiC的单一破坏模式，提高其力学性能。在RMI过程中，适当的细颗粒的加入减少了SiC基体中残余硅的聚集，从而将热解碳与熔融硅的反应限制在局部区域。这有利于增强β-SiC相的集中生长，是性能提高的关键机制。最终碳化硅的体积密度为2.996 g/cm3，最大抗弯强度为369.67 MPa，强度提高了约83%。该方法为利用VPP技术制备复杂结构的高强度碳化硅提供了有效的解决方案。

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引用次数: 0

Mechanism of wettability enhancement of the AgCuTi-SiO2f/SiO2 system with a laser-manufactured bioinspired sinusoidal interface 激光制备生物激发正弦界面增强AgCuTi-SiO2f/SiO2体系润湿性的机理

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2025-12-18 DOI: 10.1016/j.jmapro.2025.11.083

Shuzhen Zhao , Lixia Zhang , Qing Chang , Bo Zhang , Zhan Sun , Yongbo Xu , Boyu Zhang , Fengying Wang

The poor wettability of filler metals on the SiO_2f/SiO₂ composite surface adversely affected the brazing joint strength, constraining the application of SiO_2f/SiO₂ composite. In this paper, the bioinspired sinusoidal structure interface was designed and manufactured by the picosecond laser, aiming to enhance wettability. The wetting angles of the Ag-Cu-Ti filler metal on the SiO_2f/SiO₂ composite surface with different bioinspired sinusoidal structures were compared. Effects of the structural morphology and surface reaction state of bioinspired sinusoidal structures on the wetting mechanism were investigated. The results indicated that, as the amplitude of the sinusoidal structure decreased, the surface energy barrier that hindered wetting and the capillary force that promoted droplet spreading decreased simultaneously. Furthermore, active defects, such as ODC(II) and NBOHC, were generated on the structured surface. The surface rich in defects easily reacted with the Ag-Cu-Ti filler metal, which was beneficial for promoting the reactive wetting. An optimized double sinusoidal structure with 25 μm amplitude and 100 μm wavelength reduced the wetting angle from ~110° to ~70°. Dense and continuous Ti₅Si₃ + TiO₂/Cu₃Ti₃O reaction layers with a thickness of over 2 μm were formed, which indicated a reliable metallurgical bonding. Attributed to the promoted wettability and enhanced interfacial bonding, the SiO_2f/SiO₂ composites brazed joint was strengthened from 5 MPa to 23 MPa. This bioinspired sinusoidal structure could also be introduced in further ceramics-metal dissimilar interfaces to enhance wettability and interfacial bonding.

填充金属在SiO2f/SiO2复合材料表面的润湿性较差，影响了钎焊接头的强度，制约了SiO2f/SiO2复合材料的应用。本文利用皮秒激光设计和制造了仿生正弦结构界面，以提高材料的润湿性。比较了Ag-Cu-Ti填充金属在不同仿生正弦结构SiO2f/SiO2复合材料表面的润湿角。研究了仿生正弦结构的结构形态和表面反应状态对润湿机理的影响。结果表明，随着正弦结构幅值的减小，阻碍液滴润湿的表面能垒和促进液滴扩散的毛细力同时减小。此外，在结构表面生成了ODC（II）和NBOHC等活性缺陷。缺陷丰富的表面容易与Ag-Cu-Ti填充金属发生反应，有利于促进反应润湿。优化后的振幅为25 μm、波长为100 μm的双正弦结构使润湿角从~110°减小到~70°。形成了致密连续的Ti5Si3 + TiO2/ cu3ti30o反应层，反应层厚度大于2 μm，表明了可靠的冶金结合。SiO2f/SiO2复合材料钎焊接头的润湿性提高，界面结合能力增强，强度由5 MPa提高到23 MPa。这种受生物启发的正弦结构也可以进一步引入陶瓷-金属异质界面，以增强润湿性和界面结合。

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引用次数: 0

Autonomous parameter exploration in thermoplastic material-extrusion additive manufacturing using Bayesian optimization with intermediate features 基于中间特征贝叶斯优化的热塑性材料挤压增材制造自主参数探索

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2025-12-18 DOI: 10.1016/j.jmapro.2025.12.021

Yoshiki Sakai , Kota Aono , Takayuki Osa , Moju Zhao , Hirotoshi Tagata , Masanori Nakano , Akio Suguro , Masayuki Nakao , Keisuke Nagato

Material-extrusion additive manufacturing (MEX-AM) involves rapid and microscopic physical phenomena, such as melting, ejection, and solidification of thermoplastic polymers that occur at the nozzle tip. These processes are highly sensitive to various process parameters, such as nozzle temperature and scan speed, rendering parameter exploration costly and time-consuming. To expedite the identification of optimal processing conditions, this study focuses on tensile strength as the target property and introduces neck width, derived from sidewall asperities, as an in situ intermediate feature (IFV). Neck width can be measured non-destructively and demonstrates a strong correlation with tensile strength. A Bayesian optimization with intermediate features (BOIF) approach is proposed and implemented for higher-throughput parameter exploration through real-time monitoring of neck width during modeling. By optimizing nozzle temperature, this method achieves a throughput approximately 400 times greater than that of exhaustive tensile testing. When the parameter space is expanded to include scan speed, throughput increases by up to 800 times. These results highlight the effectiveness of the BOIF framework in reducing both the experimental cost and development time in MEX-AM process optimization. Moreover, the framework suggests that incorporating additional IFVs can enhance predictive accuracy, and extending the optimization to higher-dimensional parameter spaces can further amplify the efficiency gains.

材料挤压增材制造（MEX-AM）涉及快速和微观的物理现象，例如发生在喷嘴尖端的热塑性聚合物的熔化、弹射和凝固。这些工艺对各种工艺参数（如喷嘴温度和扫描速度）高度敏感，使得参数探索成本高且耗时。为了加快最佳加工条件的确定，本研究将抗拉强度作为目标特性，并引入由侧壁凹凸度产生的颈宽作为原位中间特征（IFV）。颈宽可以非破坏性地测量，并表明与抗拉强度有很强的相关性。在建模过程中，通过实时监测颈部宽度，提出并实现了一种具有中间特征的贝叶斯优化（BOIF）方法，以实现更高吞吐量的参数探索。通过优化喷嘴温度，该方法的吞吐量比穷举拉伸测试高约400倍。当参数空间扩展到包括扫描速度时，吞吐量增加了800倍。这些结果突出了BOIF框架在降低MEX-AM工艺优化的实验成本和开发时间方面的有效性。此外，该框架表明，纳入额外的ifv可以提高预测精度，并且将优化扩展到更高维度的参数空间可以进一步放大效率增益。

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引用次数: 0

Achieving synergistic strength-ductility in CMT-WAAM fabricated AZ31 through in-situ oxidation and ultrasonic-assisted 通过原位氧化和超声辅助实现CMT-WAAM制备AZ31的强度-延性协同

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2025-12-18 DOI: 10.1016/j.jmapro.2025.12.015

Zhijun Tong , Kun Liu , Linbo Chen , Junjie Tan , Kang Peng , Xizhang Chen

Grain coarsening has long been a key factor limiting the performance of AZ31 magnesium alloy during Wire Arc Additive Manufacturing (WAAM). This research presented a novel method integrating in-situ oxidation with CMT-WAAM technology, introducing CO₂ gas in the additive manufacturing process and superimposing an external ultrasonic field. This dual approach enabled precise control over both the microstructural characteristics and mechanical performance of AZ31 magnesium alloy, creating a synergistic enhancement effect. Results showed that adding 1 vol% CO₂ (Group C1) generated MgO and MgAl₂O₄ via in-situ oxidation reactions, acting as nucleating agents that significantly increased nucleation sites and drastically improved the nucleation rate. This led to a substantial decrease of about 65 % in the average grain size, shrinking it from 49.96 μm down to 19.22 μm. The finer grains boosted the material's yield strength (YS) to 105.7 MPa and its ultimate tensile strength (UTS) to 235.6 MPa. However, the EL decreased from 18.8 % to 12.4 %. Furthermore, by further combining with external ultrasonic field (Group U1), the cavitation effect was utilized to reduce the temperature gradient of the molten pool and increase the cooling rate, thereby further refining the average grain size by 28 % to 13.83 μm, by 28 % to 13.83 μm, while facilitating the uniform distribution of particles. Mechanically, the U1 group samples with synergistic CO₂ and external ultrasonic field exhibited a UTS of 247.7 MPa and a YS of 108.7 MPa, representing increases of 12.6 % and 30.8 % compared to the pure argon-protected specimens, respectively. Meanwhile, the elongation reached 15.4 %, effectively alleviating the plasticity loss caused by single CO₂ treatment. The examination of the strengthening processes showed that the primary driver behind the boost in strength was the combined influence of grain boundary reinforcement, dislocation barriers, and dispersion strengthening. Meanwhile, the use of ultrasonic treatment helped maintain plasticity by reducing defects and ensuring a uniform distribution of particles. This research introduces an innovative approach to enhancing grain refinement and optimizing strength-ductility in magnesium alloy additive manufacturing.

晶粒粗化一直是限制AZ31镁合金电弧增材制造性能的关键因素。本研究提出了一种将原位氧化与CMT-WAAM技术相结合，在增材制造过程中引入CO2气体并叠加外部超声场的新方法。这种双重方法可以精确控制AZ31镁合金的微观组织特征和力学性能，从而产生协同增强效果。结果表明，加入1 vol% CO2 （C1族），通过原位氧化反应生成MgO和MgAl2O₄，作为成核剂，可显著增加成核位，大幅提高成核速率。平均晶粒尺寸从49.96 μm减小到19.22 μm，降幅约65%。晶粒细化后，材料的屈服强度（YS）达到105.7 MPa，极限抗拉强度（UTS）达到235.6 MPa。然而，EL从18.8%下降到12.4%。进一步结合外部超声场（U1组），利用空化效应降低熔池温度梯度，提高冷却速度，进一步细化平均晶粒尺寸28%至13.83 μm，细化28%至13.83 μm，同时促进颗粒均匀分布。机械上，CO2和外超声场协同作用的U1组样品的UTS为247.7 MPa， YS为108.7 MPa，分别比纯氩气保护的样品提高了12.6%和30.8%。伸长率达到15.4%，有效缓解了单一CO2处理造成的塑性损失。对强化过程的研究表明，强度提高背后的主要驱动因素是晶界强化、位错屏障和弥散强化的综合影响。同时，使用超声波处理有助于通过减少缺陷和确保颗粒均匀分布来保持塑性。本研究提出了一种在镁合金增材制造中提高晶粒细化和优化强度-塑性的创新方法。

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引用次数: 0

Length-optimal tool path generation for nonzero genus surfaces: Integrating field construction with isoline manipulation 非零曲面的长度最优刀具路径生成：将场构建与等值线操作相结合

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2025-12-18 DOI: 10.1016/j.jmapro.2025.12.040

Guangwen Yan , Tao Jiang , Jinting Xu , Yingshi Li , Yuwen Sun

Nonzero genus surfaces, as one of the most typical difficult-to-machine surfaces, are widely used in manufacturing of aerospace, molds, and automotive components. In these domains, large complex structures that prioritize machining efficiency are more common, thus optimizing the path length has always been a key focus in their finish machining. However, traditional iso-planar or mapping-based tool path generation methods primarily focus on geometric coverage of surfaces, which can hardly incorporate such manufacturing intent. Though the mainstream field-based methods for minimizing path length have shown success on genus-0 surfaces, they largely overlook the segmentation effect of genus on tool paths, failing to exploit the geometric anisotropy near genus to maximize scallop height between adjacent tool paths, thereby often resulting in suboptimal path length. To address these issues, this paper proposes to generate length-optimal tool paths for nonzero genus surfaces by constructing a maximal machining strip width direction field (MMSWDF) and manipulating isoline layout. First, a unified framework for calculating and modifying MMSWDF to ensure an ordered tool path pattern is developed by using triangular meshes and quadratic surface fitting. Then, a scalar field corresponding to the modified field is obtained by solving a Poisson equation, its isolines can be treated as the potential tool paths with maximal machining strip width. Further, to simplify the isoline layout, a tree-inspired isoline layout strategy is formulated to enable segmented offsetting of isolines near genus to maximize the scallop height. Subsequently, a heuristic tool path connection based on the shortest path search is applied to shorten the transition distance between adjacent subregions of tool paths. Finally, both simulations and physical experiment are conducted to validate the proposed method.

非零属曲面作为最典型的难加工曲面之一，广泛应用于航空航天、模具、汽车零部件等领域。在这些领域中，优先考虑加工效率的大型复杂结构更为常见，因此优化路径长度一直是其精加工的重点。然而，传统的等平面或基于映射的刀具轨迹生成方法主要关注曲面的几何覆盖，难以体现这种制造意图。尽管主流的基于现场的最小化路径长度方法在零类曲面上取得了成功，但它们在很大程度上忽略了类对刀具路径的分割作用，未能利用类附近的几何各向异性来最大化相邻刀具路径之间的扇贝高度，因此往往导致次优路径长度。为了解决这些问题，本文提出通过构造最大加工带宽度方向场（MMSWDF）和操纵等值线布局来生成非零曲面的长度最优刀具路径。首先，通过三角网格和二次曲面拟合，建立了统一的计算和修改MMSWDF的框架，以确保有序的刀具轨迹模式；然后，通过求解泊松方程得到与修正场对应的标量场，其等值线可作为最大加工带材宽度的潜在刀具轨迹。此外，为了简化等值线布局，提出了一种树型等值线布局策略，实现了等值线在属附近的分段偏移，使扇贝高度最大化。然后，应用基于最短路径搜索的启发式刀具路径连接来缩短刀具路径相邻子区域之间的过渡距离。最后，通过仿真和物理实验验证了该方法的有效性。

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