Journal of Manufacturing Processes最新文献_第3页

Structure, mechanical properties, and wear behavior of functionally graded hybrid AA6061-B4C-CNT composites using combined stir casting and centrifugal casting 搅拌铸造和离心铸造复合AA6061-B4C-CNT功能梯度复合材料的组织、力学性能和磨损行为

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-03-15 Epub Date: 2026-01-30 DOI: 10.1016/j.jmapro.2026.01.094

Sukanta Sarkar , Ujjal Dey , Ketan Chouhan , C.S. Kumar , Siddhartha Roy

A functionally graded hybrid Al-B₄C-CNT composite cylinder was fabricated using combined stir and centrifugal casting to improve the properties of both the outer and inner surfaces. While a dense B₄C-rich region of approx. 1 mm thickness was achieved at the outermost surface due to the higher density of B₄C particles over molten AA6061, the areas adjacent to the inner surface were preferentially reinforced by CNTs. Electron backscattered diffraction (EBSD) analysis confirmed grain refinement and increased local strain in reinforcement-rich regions, with the finest grains and highest kernel average misorientation (KAM) value observed in the region, preferentially enriched with the CNTs. Raman spectroscopy confirmed the gradient CNT distribution, and high-resolution transmission electron microscope analysis proved the strong interfacial bonding due to the formation of a thin Al₄C₃ layer. Due to the presence of high B₄C content, the highest hardness of 520 ± 30 HV was achieved at the outer periphery, while the presence of CNTs in the inner regions resulted in higher hardness in those regions compared to the reinforcement-free mid-thickness zone of the cylinder. Samples from five regions along the thickness — outer, outer-middle, middle, middle-inner, and inner were subjected to three-point bend and wear tests. The inner-middle part demonstrated the best combination of flexural strength and toughness (flexural strength ∼350 MPa and flexural strain ∼11%) along with the lowest coefficient of friction (= 0.23) and specific wear rate due to the uniformly distributed CNT reinforcement. In conventional centrifugal-cast functionally graded composites, the inner surface generally suffers from inferior properties due to the accumulation of defects. In that respect, this novel composite design with gradient distribution of hybrid reinforcements provides a methodology to reinforce both surfaces simultaneously.

采用搅拌和离心联合铸造的方法制备了功能梯度杂化Al-B₄C-CNT复合圆柱体，提高了其内外表面的性能。而密集的富含b4c的区域大约有。由于熔融AA6061表面的B4C颗粒密度较高，最外表面的厚度达到了1mm，靠近内表面的区域优先被CNTs增强。电子背散射衍射（EBSD）分析证实，在富含碳纳米管的区域，晶粒细化，局部应变增加，晶粒细，籽粒平均取向偏差（KAM）值最高。拉曼光谱证实了碳纳米管的梯度分布，高分辨率透射电镜分析证实了由于形成薄Al4C3层而形成的强界面键合。由于B4C含量高，外边缘的硬度最高，达到520±30 HV，而内部区域存在CNTs导致这些区域的硬度高于圆柱体无增强的中厚区域。从沿厚度的五个区域——外、外-中、中、中-内和内进行三点弯曲和磨损试验。由于均匀分布的碳纳米管增强，内中部的抗弯强度和韧性组合最佳（抗弯强度~ 350mpa，抗弯应变~ 11%），摩擦系数最低（= 0.23），比磨损率最低。在传统的离心铸造功能梯度复合材料中，由于缺陷的积累，内表面通常性能较差。在这方面，这种具有梯度分布的混合增强材料的新型复合设计提供了一种同时增强两个表面的方法。

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引用次数: 0

An integrated learning, monitoring, and control system for ultrasonic metal welding 超声金属焊接的综合学习、监测和控制系统

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-03-15 Epub Date: 2026-02-05 DOI: 10.1016/j.jmapro.2026.01.077

Kuan-Chieh Lu , Li-Wei Shih , Chenhui Shao

Ultrasonic metal welding (UMW) is a solid-state joining technology with widespread industrial applications. However, the weld quality in UMW is highly sensitive to process disturbances such as tool degradation and surface contamination. To address this challenge, this paper presents an integrated learning, monitoring, and control (LMC) system to improve process robustness and weld quality in UMW. The proposed system integrates in-situ sensing, online process monitoring, and within-cycle process adjustment to automatically compensate for process disturbances. Extensive experiments involving 700 welds with varied acting time, pressure adjustments, and contamination levels, are carried out to thoroughly evaluate the effectiveness of the LMC system. It is shown that the proposed method significantly and consistently outperforms the existing controller. Specifically, the weld success rate is increased from 0% to 92% under 20% surface contamination, and from 6% to 72% under 10% surface contamination. Furthermore, a response surface model is developed to quantify the causal relationships between control inputs (i.e., acting time and pressure increase amount) and the resulting weld success rate, which enables efficient optimization of control parameters. Overall, the proposed LMC approach improves the UMW process robustness and weld quality, demonstrating strong potential for industrial-scale implementation. To the best of our knowledge, this study represents one of the first integrated LMC systems developed for UMW.

超声波金属焊接（UMW）是一种具有广泛工业应用的固态焊接技术。然而，在UMW焊接质量是高度敏感的过程干扰，如工具退化和表面污染。为了解决这一挑战，本文提出了一种集成学习、监测和控制（LMC）系统，以提高UMW的工艺稳健性和焊接质量。该系统集成了原位传感、在线过程监测和周期内过程调节，以自动补偿过程干扰。为了彻底评估LMC系统的有效性，对700个不同作用时间、压力调节和污染水平的焊缝进行了广泛的实验。结果表明，该方法明显优于现有的控制器。具体来说，当表面污染为20%时，焊接成功率从0%提高到92%，当表面污染为10%时，焊接成功率从6%提高到72%。此外，建立了响应面模型来量化控制输入（即作用时间和压力增加量）与焊接成功率之间的因果关系，从而实现控制参数的有效优化。总体而言，所提出的LMC方法提高了UMW工艺的稳健性和焊接质量，显示出工业规模实施的强大潜力。据我们所知，这项研究是为UMW开发的第一个集成LMC系统之一。

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引用次数: 0

A novel fluid-driven vibration finishing method for internal surfaces of additively manufactured channels 一种新型增材制造通道内表面流体驱动振动精加工方法

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-03-15 Epub Date: 2026-02-04 DOI: 10.1016/j.jmapro.2026.01.100

Qikai Li , Mohammad Rakibul Hasan , Ankang Yuan , Ruoying Wang , Chao Ni , Pu Qin , Xu Zhu , Mingyang Lu , Qing Luo , Danlei Zhao , Guangyi Ma

To address the critical challenge of poor surface quality in complex internal channels fabricated by additive manufacturing (AM) technologies, this paper proposes a novel fluid-driven vibration finishing (FDVF) method for the internal surface of channels. When the fluid encounters an abrupt reduction in flow area, the static pressure decreases dramatically due to the increase in velocity. This pressure variation is utilized to drive periodic vibrations of a blocking ball within the channel. By leveraging the ball's impact on the internal surface and controlling the position of the ball, uniform finishing of the AM-fabricated channel can be achieved. The mechanisms of ball vibration and surface finishing processes were investigated through the integration of computational fluid dynamics simulations and high-speed imaging. Results showed >4 kHz high-frequency vibrations of the ball were generated coupled with periodic hydrodynamic cavitation, effectively finishing the wall with depths of material deformation surpassing 25 μm. A 3.6 mm inner-diameter SLM stainless steel tube with an initial average roughness Sa of 6.798 μm was finished under 3.5 MPa. After 60 min, the internal roughness Sa of a 90 mm tube was reduced by 98%, with axial roughness Sa variation within ±0.041 μm. Additionally, the controllability and feasibility of this method for complex channels was validated by finishing a U-shaped tube with an identical inner diameter, achieving a uniform roughness Sa below 0.1 μm on the straight part.

针对增材制造（AM）技术制造复杂内通道表面质量差的关键问题，提出了一种新型的通道内表面流体驱动振动精加工（FDVF）方法。当流体流过面积突然减小时，由于速度的增加，静压急剧下降。这种压力变化被用来驱动通道内封堵球的周期性振动。通过利用球对内表面的冲击和控制球的位置，可以实现am制造通道的均匀精加工。通过计算流体动力学模拟和高速成像相结合的方法，研究了球振动和表面处理过程的机理。结果表明：该球产生了>；4 kHz的高频振动，并伴有周期性的流体动力空化，有效地完成了材料变形深度超过25 μm的管壁；在3.5 MPa的压力下，制备了一根内径为3.6 mm，初始平均粗糙度Sa为6.798 μm的SLM不锈钢管。60 min后，90 mm管的内部粗糙度Sa降低了98%，轴向粗糙度Sa变化幅度在±0.041 μm以内。此外，通过加工相同内径的u型管，验证了该方法在复杂通道上的可控性和可行性，直线部分粗糙度Sa均匀小于0.1 μm。

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引用次数: 0

High-temperature wear behaviour of laser-textured assisted cold-sprayed metal matrix composite coatings: tamping effect of particles in a confined space 激光织构辅助冷喷涂金属基复合涂层的高温磨损行为：密闭空间中颗粒的夯实效应

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-03-15 Epub Date: 2026-02-05 DOI: 10.1016/j.jmapro.2026.01.097

Zhiyuan Wang , Jianing Wang , Bowen Yao , Huan Chen , Fengyuan Bao , Yang Liu , Xueze Jin , Oleg Bashkov , Lin Cao

To address the surface protection challenges faced by turbine blades in gas turbines under extreme operating conditions—including high temperatures, high pressures, and high-velocity gas combustion gases—this study employs an efficient composite process combining laser surface texturing with cold spraying (LST-CS). This process is designed to enhance the interfacial bonding of cold-sprayed nickel-based coatings, thereby improving their operational reliability and extending component lifespan. Following substrate pretreatment, coating porosity decreased by 2.28%, bond strength increased by 3.68-fold, and wear rates at ambient and elevated temperatures decreased by 52.67% and 68.71% respectively. Experimental and characterisation analyses revealed that the textured groove structures not only increased particle-substrate contact area but also functioned as a guiding framework directing particle deposition. This induced a ceramic tamping effect within confined spaces, establishing a mortise-and-tenon mechanical interlocking structure at the coating-substrate interface. This structure not only enhances the bonding strength between the coating and the substrate, promoting overall densification of the coating, but also effectively suppresses crack initiation at elevated temperatures through dovetail mechanical anchoring. By leveraging substrate softening, it transforms frictional loads into lateral compression that reinforces interfacial bonding, thereby significantly mitigating high-temperature shear slippage and interfacial delamination. This extends the service life of the coating and provides a theoretical foundation and technical guidance for improving the surface repair performance of high-end equipment under extreme operating conditions.

为了解决燃气轮机涡轮叶片在极端工况下（包括高温、高压和高速燃气燃烧气体）面临的表面保护挑战，本研究采用了激光表面纹理与冷喷涂（LST-CS）相结合的高效复合工艺。该工艺旨在增强冷喷涂镍基涂层的界面结合，从而提高其运行可靠性并延长组件寿命。基材预处理后，涂层孔隙率降低了2.28%，结合强度提高了3.68倍，室温和高温下的磨损率分别降低了52.67%和68.71%。实验和表征分析表明，织构槽结构不仅增加了颗粒与衬底的接触面积，而且还起到了指导颗粒沉积的导向框架作用。这在有限的空间内诱发了陶瓷夯实效应，在涂层-衬底界面处建立了榫卯机械联锁结构。这种结构不仅提高了涂层与基体的结合强度，促进涂层的整体致密化，而且通过燕尾机械锚定有效抑制高温下裂纹的产生。通过利用基材软化，它将摩擦载荷转化为侧向压缩，从而加强界面结合，从而显著减轻高温剪切滑移和界面分层。这延长了涂层的使用寿命，为提高高端设备在极端工况下的表面修复性能提供了理论基础和技术指导。

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引用次数: 0

Intelligent laser micromachining parameter optimization via causality-enhanced data-driven modeling 基于因果关系增强数据驱动建模的智能激光微加工参数优化

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-03-15 Epub Date: 2026-02-03 DOI: 10.1016/j.jmapro.2026.02.003

Wei-Ming Jiang , Yan-Ning Sun , Li-Lan Liu , Jie-Cai Feng , Zeng-Gui Gao

Laser micromachining is pivotal for producing surface micropore structures that comply with specifications in thermal barrier coating manufacturing. However, the intricate nonlinear interactions among laser parameters result in considerable variability in the final processing quality of the micropores. Data-driven methods have mapped laser parameters to processing quality, but traditional machine learning (ML) models provide limited understanding of the causal mechanisms involved, hindering deeper insights into quality optimization process. To address this limitation, this study proposes a causal-enhanced ML (CEML) framework that incorporates causality to identify the optimal combination of laser parameters for enhanced processing quality. The study is structured into three sequential experimental stages. First, a series of micromachining experiments were conducted to generate a dataset comprising laser parameters and corresponding micropore quality indicators. Second, based on the experimental dataset, causal analysis was conducted and the extracted causal information was integrated into model training. The resulting CEML surrogate model was benchmarked against baseline ML models, demonstrating improved predictive performance across multiple evaluation metrics and stable performance under 5-fold cross-validation. Third, a multi-objective optimization based on particle swarm optimization was employed to derive optimal parameters for improved processing quality. The effectiveness of the optimal parameters was subsequently validated through physical machining experiments.

在热障涂层制造中，激光微加工是制造符合规范的表面微孔结构的关键。然而，激光参数之间复杂的非线性相互作用导致微孔的最终加工质量有相当大的变化。数据驱动的方法已经将激光参数映射到加工质量，但传统的机器学习（ML）模型对所涉及的因果机制的理解有限，阻碍了对质量优化过程的深入了解。为了解决这一限制，本研究提出了一个因果关系增强的ML （CEML）框架，该框架包含因果关系，以确定提高加工质量的激光参数的最佳组合。这项研究分为三个连续的实验阶段。首先，进行一系列微加工实验，生成包含激光参数和相应微孔质量指标的数据集。其次，基于实验数据集进行因果分析，并将提取的因果信息整合到模型训练中。由此产生的CEML代理模型与基线ML模型进行了基准测试，在多个评估指标中显示出改进的预测性能，并且在5次交叉验证下表现稳定。第三，采用基于粒子群算法的多目标优化方法，求出提高加工质量的最优参数。通过物理加工实验验证了优化参数的有效性。

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引用次数: 0

Enhancing gear surface integrity: A study of longitudinal-torsional ultrasonic strengthening effect on surface roughness 提高齿轮表面完整性：纵向-扭转超声强化对表面粗糙度的影响研究

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-03-15 Epub Date: 2026-02-05 DOI: 10.1016/j.jmapro.2026.01.098

Yan Jiang, Qinyuan Yang, Qiang Guo, Bo Zhao, Tian Li, Ying Niu

Tooth surface properties are critical for gear longevity, efficiency, and accuracy. Traditional strengthening methods often fall short in high-precision, long-life applications. Fortunately, with its precise energy control, ultrasonic machining offers a novel approach to overcoming these drawbacks and achieving superior surfaces quality. However, there are few studies on the effect elucidation of longitudinal-torsional ultrasonic machining for gears. Thus, this paper introduces a new gear surface strengthening method by integrating longitudinal-torsional ultrasonic machining with gear meshing theory, focusing on surface formation mechanisms and roughness evolution. The underlying micro-forming mechanism, based on Boussinesq-Flamant theory, models the process in three stages: 1) Triangular indentation, where initial grinding peaks yield and subside under combined static and ultrasonic loading; 2) Crushing collapse, involving material work hardening, fracture, and flow into valleys under cyclic load, dissolving the original topography; 3) New surface formation, where stabilized plastic flow fills valleys to create a smooth, dense surface with beneficial residual compressive stress. This model systematically describes the evolution from the initial to the hardened surface. For validation, a dedicated experimental platform was used alongside white-light interferometry. Results show high consistency between experimental and theoretical surface morphology trends along the tooth profile, with an average quantitative error of 15%. These findings validate the three-stage model, providing a theoretical foundation for understanding and optimizing ultrasonic gear strengthening processes.

齿面特性对齿轮寿命、效率和精度至关重要。传统的强化方法在高精度、长寿命的应用中往往存在不足。幸运的是，凭借其精确的能量控制，超声波加工提供了一种克服这些缺点并获得卓越表面质量的新方法。然而，对齿轮纵扭超声加工的效果分析研究较少。因此，本文介绍了一种将纵扭超声加工与齿轮啮合理论相结合的齿轮表面强化新方法，重点研究了表面形成机理和粗糙度演变。基于Boussinesq-Flamant理论，将微成形机理分为三个阶段：1)三角形压痕，在静态和超声复合载荷下，初始磨峰屈服并沉降；2)破碎崩塌，材料在循环荷载作用下加工硬化、断裂、流向山谷，使原始地形溶解；3)新的表面形成，其中稳定的塑性流填充山谷，创造一个光滑，密集的表面与有益的残余压应力。该模型系统地描述了从初始表面到硬化表面的演变过程。为了验证，在白光干涉测量的同时使用了一个专用的实验平台。结果表明，沿齿廓方向的表面形貌趋势与实验结果高度一致，平均定量误差为15%。这些结果验证了三阶段模型，为理解和优化超声齿轮强化工艺提供了理论基础。

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引用次数: 0

Predicting submerged deflecting abrasive waterjet peening induced surface roughness based on vibration signal via a time-frequency parallel deep learning network 基于振动信号的时频并行深度学习网络预测水下偏转磨料水射流强化诱导表面粗糙度

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-03-15 Epub Date: 2026-02-09 DOI: 10.1016/j.jmapro.2026.01.103

Yu-Xin Chi , Shu-Lei Yao , Xian-Hao Zhu , Zhi-Yun Wang , Jie Qi , Ning Wang , Xian-Cheng Zhang

Waterjet peening (WJP) is an effective surface strengthening method for complex aeroengine components. However, the low stiffness of thin-walled parts, such as blades, can induce significant vibration responses during machining, which may adversely affect the final surface integrity. Therefore, process monitoring is crucial for capturing dynamic responses and providing timely feedback for quality control. However, owing to the complex working environment and strengthening mechanism, monitoring the WJP process remains challenging. In this study, vibration signals from thin-walled titanium alloy TA19 specimens were collected during submerged deflecting abrasive waterjet peening (SDAWJP). The vibration signals exhibited change trends consistent with those of surface roughness and showed clear sensitivity to variations in process parameters, thus enabling accurate prediction modeling. A time-frequency parallel deep learning network (TFPNet) was proposed, in which vibration features from both the time and frequency domains were extracted simultaneously and subsequently fused via an attention pooling mechanism to effectively predict the surface roughness. The prediction performance was evaluated under varying abrasive flow rates and water pressures. The proposed model achieved mean absolute percentage errors of 0.99% and 1.35%, respectively, which were significantly lower and more stable than those of the comparative methods. The findings are expected to provide support for the machining quality assurance in practical aviation components.

水射流强化是航空发动机复杂部件表面强化的一种有效方法。然而，薄壁零件（如叶片）的低刚度在加工过程中会引起明显的振动响应，这可能会对最终的表面完整性产生不利影响。因此，过程监控对于捕获动态响应和为质量控制提供及时反馈至关重要。然而，由于复杂的工作环境和加强机制，监测WJP进程仍然具有挑战性。本文采集了TA19薄壁钛合金试样在水下偏转磨料水射流强化（SDAWJP）过程中的振动信号。振动信号的变化趋势与表面粗糙度的变化趋势一致，对工艺参数的变化具有明显的敏感性，从而能够准确地预测建模。提出了一种时频并行深度学习网络（TFPNet），该网络同时提取时域和频域的振动特征，然后通过注意力池机制进行融合，从而有效地预测表面粗糙度。在不同的磨料流量和水压条件下，对预测效果进行了评价。该模型的平均绝对百分比误差分别为0.99%和1.35%，显著低于对比方法，且更加稳定。研究结果有望为实际航空部件的加工质量保证提供支持。

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引用次数: 0

Surface flattening during aluminum sheet forming 铝板成形过程中的表面扁化

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-03-15 Epub Date: 2026-02-06 DOI: 10.1016/j.jmapro.2026.01.099

Farshid Jalali Moghadas , Matthijn de Rooij , Ton van den Boogaard , Javad Hazrati

Predicting friction in sheet metal forming is essential for accurate modelling of the process and therefore its optimization. Estimation of real contact area is prerequisite for reliable prediction of friction. In this paper, effects of normal load, as well as normal load combined by strain in aluminum sheet metal on the real area of contact are investigated. An earlier setup is improved to probe combined normal load and bulk strain effects on the real area of contact. Experiments are carried out on two grades of aluminum, AA6016 and AA5182 sheets with electro discharge surface textures (EDT). Fractional real area of contact at different contact pressure and strain levels is measured using confocal microscopic images of the deformed surfaces. A semi-analytical model is used to predict real area of contact evolution due to normal load using a hardness database of different asperity geometries. To account for flattening of asperities due to combined normal load and bulk strain, a new model is developed and calibrated based on the experiments. The experimental results show that extent of increase in real area of contact due to only normal load or combined normal load and strain depends on the surface texture, the material properties and contact conditions. Predictions of the new models were validated using different textures of the same aluminum grade. The results show that the models capture the evolution of real area of contact with reasonable accuracy. These models will be used to enhance friction modelling in aluminum sheet forming.

预测金属板料成形过程中的摩擦对过程的精确建模和优化至关重要。实际接触面积的估计是可靠预测摩擦的前提。本文研究了法向载荷以及法向载荷加应变对铝板实际接触面积的影响。改进了先前的设置，以探测法向载荷和体应变对实际接触面积的影响。以两种铝材AA6016和AA5182为研究对象，进行了电火花表面织构（EDT）实验。在不同的接触压力和应变水平的分数实际接触面积测量使用共聚焦显微镜图像的变形表面。采用一种半解析模型，利用不同硬度几何形状的硬度数据库来预测法向载荷引起的实际接触演化面积。为了考虑法向载荷和体应变共同作用下的凹凸不平的扁化现象，在实验的基础上建立了新的模型并进行了标定。实验结果表明，单纯法向载荷或法向载荷与应变组合作用下实际接触面积的增大程度与表面织构、材料性能和接触条件有关。使用相同铝等级的不同纹理验证了新模型的预测。结果表明，所建立的模型能较好地反映实际接触面积的演变过程。这些模型将用于增强铝板成形中的摩擦模型。

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引用次数: 0

Surface topography control in CoCrMo alloy additive manufacturing through laser powder bed fusion process 激光粉末床熔合CoCrMo合金增材制造中的表面形貌控制

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-03-15 Epub Date: 2026-01-31 DOI: 10.1016/j.jmapro.2026.01.091

Anup Kumar Maurya , G. Sivakumar , Murugaiyan Amirthalingam , M. Kamaraj

Laser powder bed fusion (LPBF) enables precise fabrication of CoCrMo alloy components for biomedical applications; however, achieving optimal surface properties for orthopedic implants remains challenging. Surface engineering plays a pivotal role in enhancing both biological and tribological responses, particularly in improving the adhesion of bioactive coatings. This study integrates LPBFed surface optimization with atmospheric plasma-sprayed (APS) hydroxyapatite (HAp) coatings to enhance interfacial bonding strength. LPBF process parameters were systematically optimized to tailor surface roughness, followed by APS deposition of HAp coatings on the optimized CoCrMo substrates. In this study, LPBF process parameters were varied to fabricate CoCrMo samples, and specimens were evaluated based on microhardness (320–375 ± 12 HV_0.5), porosity (<1.1%), relative density (~98.9%), and surface roughness (R_a: 3–13 μm). Based on these criteria, three representative samples were selected for in-depth microstructural and mechanical characterization. Microstructural analysis revealed a dual-phase γ-FCC + ε-HCP (~14.4 vol%) matrix with cellular substructures, columnar grains, and oxide inclusions. Transmission electron microscopy (TEM) analysis revealed nano-sized chromium-rich oxides (~50 nm) and (Co, Mo, W)₂Si Laves phases along grain boundaries, which act as dislocation barriers and contribute to enhanced strength, strain hardening, and microstructural stability. The optimized LPBFed CoCrMo alloy exhibited a yield strength of ~800 ± 15 MPa and elongation of 8 ± 0.5%, attributed to the refined cellular structure, planar defects, and solid-solution strengthening. Following HAp deposition via APS, adhesion strength measurements revealed significantly enhanced interfacial bonding (~45 MPa) in a sample with optimized surface morphology. Scanning electron microscope observations confirmed reduced tensile cracking and improved coating cohesion. Nanoindentation further demonstrated superior hardness and elastic modulus, indicating dense and mechanically stable coatings. These results confirm that LPBF combined with parameter optimization and surface engineering can significantly improve the mechanical integrity and adhesion strength of bioactive coatings for advanced orthopedic implants.

激光粉末床熔融（LPBF）能够精确制造用于生物医学应用的CoCrMo合金部件；然而，实现骨科植入物的最佳表面特性仍然具有挑战性。表面工程在增强生物和摩擦学反应方面起着关键作用，特别是在提高生物活性涂层的附着力方面。本研究将LPBFed表面优化与大气等离子喷涂（APS）羟基磷灰石（HAp）涂层相结合，以提高界面结合强度。系统优化LPBF工艺参数，以调整表面粗糙度，然后在优化后的CoCrMo衬底上APS沉积HAp涂层。在本研究中，通过改变LPBF工艺参数来制备CoCrMo样品，并根据显微硬度（320-375±12 HV0.5）、孔隙率（<1.1%）、相对密度（~98.9%）和表面粗糙度（Ra: 3-13 μm）对样品进行了评估。基于这些标准，选择了三个具有代表性的样品进行深入的微观组织和力学表征。显微组织分析表明，该基体为γ-FCC + ε-HCP （~14.4 vol%）双相基体，具有胞状亚结构、柱状晶粒和氧化物包裹体。透射电镜（TEM）分析发现，沿晶界存在纳米级富铬氧化物（~50 nm）和（Co, Mo， W）2Si Laves相，它们作为位错屏障，有助于提高强度、应变硬化和显微组织稳定性。优化后的LPBFed CoCrMo合金的屈服强度为~800±15 MPa，伸长率为8±0.5%，这主要归功于细化的胞状组织、平面缺陷和固溶强化。通过APS沉积HAp后，粘附强度测量显示，在优化表面形貌的样品中，界面结合显著增强（~45 MPa）。扫描电镜观察证实，拉伸开裂减少，涂层凝聚力提高。纳米压痕进一步显示出优异的硬度和弹性模量，表明涂层致密且机械稳定。这些结果证实，LPBF结合参数优化和表面工程可以显著提高先进骨科植入物生物活性涂层的机械完整性和粘附强度。

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引用次数: 0

Mechanical precision forming and force analysis in truing of arc-shaped diamond grinding wheel using tantalum rod 用钽棒加工圆弧形金刚石砂轮的机械精密成形及受力分析

IF 6.8 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2026-03-15 Epub Date: 2026-02-02 DOI: 10.1016/j.jmapro.2026.01.038

Bing Chen , Guangye Qing , Wenzhang Yang , Jun Yi , Jimin Ge , Bing Guo , Zhaohui Deng

Arc-shaped diamond grinding wheels, as ultra-precision machining tools, offer significant advantages in the processing of spherical, aspherical, and free-form optical components due to their unique arc profiles. However, owing to the elevated hardness and comparatively inferior fracture toughness of these optical components, inevitable wear of grinding wheels occurs during grinding, leading to loss of their precise geometry and thus affecting the machining quality of the components. Therefore, in this paper, tantalum metal is used as dresser for arc-shaped wheels, and the dressed wheels are applied to the processing of axially symmetric spherical optical components. First, using planar wheel dressing as an example, the force signals collected during the dressing process with green silicon carbide (GC) and tantalum blocks are detected and analyzed. The results show that although tantalum generates relatively large dressing forces, the force in the stable stage are more uniform and stable with reduced fluctuations, contributing to the geometric stability of the grinding wheel. Tantalum dressing outperforms GC blocks in terms of roundness error and three-dimensional roughness index. Finally, the efficacy of tantalum utilization in ultra-precision grinding is ultimately demonstrated through its use in dressing arc-shaped wheels, followed by a comparative analysis of the results obtained with GC grinding rods. The experimental findings indicate that the arc contour error of following tantalum dressing is 9.4 μm, while the run-out error is 8.7 μm. When grinding K9 optical glass with spherical surface, the surface roughness reaches 0.4032 μm, and the surface accuracy is 724.4224 nm. A comparison of the two methods reveals that tantalum dressing decreases form and run-out errors by 54.81% and 37.41%, respectively. At the same time, surface roughness and accuracy of the processed workpiece are improved by 38.15% and 55.80%, respectively. These results show that the use of tantalum can not only improve grinding wheels' shape accuracy (such as plane and arc-shaped wheels), but also further improve the workpiece quality.

弧形金刚石砂轮作为一种超精密加工工具，由于其独特的弧形轮廓，在球面、非球面和自由曲面光学元件的加工中具有显著的优势。然而，由于这些光学部件的硬度较高，而断裂韧性相对较差，在磨削过程中不可避免地会发生砂轮的磨损，导致其失去精确的几何形状，从而影响部件的加工质量。因此，本文采用金属钽作为圆弧轮修整剂，将修整后的圆弧轮应用于轴对称球面光学元件的加工。首先，以平面砂轮修整为例，对绿色碳化硅（GC）和钽块修整过程中采集的力信号进行检测和分析。结果表明：虽然钽产生较大的修整力，但稳定阶段的修整力更加均匀稳定，波动减小，有利于砂轮的几何稳定性；钽选矿在圆度误差和三维粗糙度指数方面优于GC块体。最后，通过钽在圆弧砂轮修整中的应用，最终证明了钽在超精密磨削中的有效性，并与GC磨棒的结果进行了对比分析。实验结果表明，后续钽修整电弧轮廓误差为9.4 μm，跳动误差为8.7 μm。磨削球形K9光学玻璃时，表面粗糙度达到0.4032 μm，表面精度为724.4224 nm。两种方法的对比表明，钽选矿方法使成形误差和跳动误差分别降低了54.81%和37.41%。同时，被加工工件的表面粗糙度和精度分别提高了38.15%和55.80%。这些结果表明，使用钽不仅可以提高砂轮的形状精度（如平面和圆弧形砂轮），还可以进一步提高工件质量。

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引用次数: 0