Manufacturing Letters最新文献

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Phase formation and mechanical analysis of sintered Ni25Al25Co15Fe15Mn8Ti7Cr5 high entropy alloy 烧结 Ni25Al25Co15Fe15Mn8Ti7Cr5 高熵合金的相形成和力学分析

IF 1.9 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2024-10-01 DOI: 10.1016/j.mfglet.2024.09.019

Emmanuel Olorundaisi , Bukola J. Babalola , Ufoma S. Anamu , Moipone L. Teffo , Ngeleshi Michel Kibambe , Anthony O. Ogunmefun , Peter Odetola , Peter A. Olubambi

In recent years, the pursuit of cutting-edge materials has intensified, with a focus on affordability, lightweight characteristics, and exceptional performance under high-temperature conditions, to serve as alternatives to Ni-base superalloys and other conventional alloys. Potential materials suitable for high-temperature structural applications with lightweight characteristics are intermetallics such as NiAl, and TiAl, but pose numerous fabrication challenges and poor ductility behaviour at room temperature. In view of this, a novel Ni₂₅Al₂₅Co₁₅Fe₁₅ Mn₈Ti₇Cr₅ high entropy alloy (HEA) was fabricated using spark plasma sintering (SPS). The alloy was developed at a sintering temperature of 850 °C, a heating rate of 90 °C/min, a pressure of 50 MPa, and a dwelling time of 5 min. X-ray diffraction, scanning electron microscopy, and Vickers hardness tester were used to investigate the phase formation, microstructure, and mechanical properties of the HEA, respectively. The microstructure of the sintered HEA shows a homogenous dispersion of the alloying metals. The sintered microstructures showed a mixture of simple and complex phases. The grain size analysis shows that the sintered HEA exhibited a lower grain size of 2.28 µm and a refined crystallite size of 3.159 µm. The microhardness value and relative density of the sintered HEA are 135.8 HV and 99.56 %, respectively.

近年来，人们对尖端材料的追求不断加强，重点关注材料的经济性、轻质特性以及在高温条件下的优异性能，以替代镍基超级合金和其他传统合金。适合高温结构应用且具有轻质特性的潜在材料是镍铝和钛铝等金属间化合物，但它们在制造方面存在诸多挑战，而且在室温下延展性能较差。有鉴于此，一种新型 Ni25Al25Co15Fe15 Mn8Ti7Cr5 高熵合金（HEA）采用火花等离子烧结（SPS）技术制成。该合金的烧结温度为 850 °C，加热速度为 90 °C/分钟，压力为 50 兆帕，停留时间为 5 分钟。利用 X 射线衍射、扫描电子显微镜和维氏硬度计分别研究了 HEA 的相形成、微观结构和机械性能。烧结 HEA 的微观结构显示出合金金属的均匀分散。烧结微结构显示出简单相和复杂相的混合。晶粒度分析表明，烧结 HEA 的晶粒度较低，为 2.28 µm，晶粒度较细，为 3.159 µm。烧结 HEA 的显微硬度值和相对密度分别为 135.8 HV 和 99.56 %。

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引用次数: 0

Thermo-mechanical and phase prediction of Ni25Al25Co14Fe14Ti9Mn8Cr5 high entropy alloys system using THERMO-CALC 使用 THERMO-CALC 对 Ni25Al25Co14Fe14Ti9Mn8Cr5 高熵合金体系进行热力学和相位预测

IF 1.9 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2024-10-01 DOI: 10.1016/j.mfglet.2024.09.020

Emmanuel Olorundaisi , Bukola J Babalola , Ufoma S. Anamu , Moipone L. Teffo , Ngeleshi M. Kibambe , Anthony O. Ogunmefun , Peter Odetola , Peter A. Olubambi

This study focuses on predicting phases and thermo-mechanical properties of NiAl-Ti-Mn-Co-Fe-Cr High Entropy Alloys (HEAs) using THERMOCALC software version 2021b with the TCHEA5 HEAs database. The thermodynamic simulation was used to investigate the phase formation and total hardness of the HEAs. The thermodynamic simulation result shows the presence of three major phases at room temperature, namely, BCC, SIGMA, and HEUSLER phases, with the BCC having a higher percentage of volume fraction of 62.4%. The activity of all components at high temperatures was studied, and the study shows Ni and Al to be stable at high temperatures, implying excellent mechanical properties are expected at high temperatures. The predicted total hardness is given as 96.2 HV.

本研究的重点是利用 THERMOCALC 软件 2021b 版和 TCHEA5 高熵合金（HEAs）数据库预测 NiAl-Ti-Mn-Co-Fe-Cr 高熵合金（HEAs）的相和热机械性能。热力学模拟用于研究 HEA 的相形成和总硬度。热力学模拟结果表明，室温下存在三个主要相，即 BCC 相、SIGMA 相和 HEUSLER 相，其中 BCC 相的体积分数百分比较高，为 62.4%。对所有成分在高温下的活性进行了研究，研究结果表明，镍和铝在高温下是稳定的，这意味着在高温下有望获得优异的机械性能。预测的总硬度为 96.2 HV。

引用次数: 0

Characterization of oscillatory magnetic field-assisted finishing of directed energy deposition NASA HR-1 integral channels 振荡磁场辅助整理定向能量沉积 NASA HR-1 积分通道的特征

IF 1.9 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2024-10-01 DOI: 10.1016/j.mfglet.2024.09.085

Kateland Hutt , Justin Rietberg , Paul Gradl , Hitomi Yamaguchi

Additive manufacturing (AM), such as directed energy deposition (DED), enables fabrication of complex geometries for critical parts at near-net shape, but creates a need for post-processing to achieve desired geometry and performance. In particular, parts made using DED are sometimes printed with a high initial surface roughness, requiring post-processing to meet application-dependent requirements. Magnetic field-assisted finishing (MAF), in which a magnetic polishing tool is manipulated by magnetic force and generates relative motion against a target surface, has been applied to smooth AM parts. An advantage of MAF is that the magnetically manipulated polishing tools can finish both external part surfaces and part interiors. In this paper, an oscillating magnetic polishing tool is proposed to smooth the inner surfaces of rectangular NASA HR-1 alloy channels made using DED. Because effective tool motion allows reduction of surface roughness and waviness, parameters that control polishing-tool motion are of great interest. This paper describes three parameters that control polishing-tool motion: number of polishing tools, magnetic field, and abrasive slurry. The effects of tool motion on the polishing characteristics are demonstrated, showing that the roughness of the interior channel surface can be reduced from several tens of micron to a sub-micron level.

增材制造（AM），如定向能沉积（DED），能以接近净形的方式制造复杂几何形状的关键零件，但需要进行后处理，以实现所需的几何形状和性能。特别是，使用定向能沉积技术制造的零件有时会打印出较高的初始表面粗糙度，这就需要进行后处理，以满足与应用相关的要求。磁场辅助精加工（MAF）是通过磁力操纵磁性抛光工具，使其产生与目标表面的相对运动，已被应用于光滑的 AM 零件。磁场辅助抛光的优点是磁力操纵的抛光工具既能抛光零件外表面，也能抛光零件内部。本文提出了一种摆动磁性抛光工具，用于平滑使用 DED 制作的矩形 NASA HR-1 合金通道的内表面。由于有效的工具运动可以减少表面粗糙度和波纹，因此控制抛光工具运动的参数非常重要。本文介绍了控制抛光工具运动的三个参数：抛光工具数量、磁场和研磨浆。结果表明，抛光工具运动对抛光特性的影响可以将通道内表面的粗糙度从几十微米降低到亚微米级。

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引用次数: 0

A qualitative validation of an in-situ monitoring system for EHD inkjet printing via laser diffraction 通过激光衍射对 EHD 喷墨打印原位监测系统进行定性验证

IF 1.9 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2024-10-01 DOI: 10.1016/j.mfglet.2024.09.029

Xuepeng Jiang, Pengyu Zhang, Hantang Qin

Electrohydrodynamic inkjet printing enables high-resolution patterning for nano features. In-flight dynamics of EHD inkjet printing play an essential role in the quality control of printing results. We applied a laser diffraction/scattering in-situ analyzing setup for the EHD inkjet printing system to replace the zoom lens and high-speed camera imaging system. In contrast to conventional imaging systems, the laser diffraction/scattering system is based on analyzing the diffraction pattern and scattering intensity, respectively, which provided higher resolution for micro-scale jetting measurement and enabled sub-micron level jetting correlation between the voltage applied to the electrode and printing results. Furthermore, Taylor cone information from the nozzle head could also be analyzed in real-time to make adjustments to the printing process. In this work, we successfully validated the feasibility of laser diffraction analysis in-situ monitoring for EHD inkjet printing at micron and sub-micron levels.

电流体动力喷墨打印可实现纳米特征的高分辨率图案化。电流体动力喷墨打印的飞行动力学对打印结果的质量控制起着至关重要的作用。我们将激光衍射/散射原位分析装置用于 EHD 喷墨打印系统，以取代变焦镜头和高速摄像成像系统。与传统成像系统相比，激光衍射/散射系统分别基于对衍射图样和散射强度的分析，为微米尺度的喷射测量提供了更高的分辨率，并实现了施加在电极上的电压与打印结果之间的亚微米级喷射相关性。此外，还可以实时分析喷嘴头的泰勒锥信息，以便对打印过程进行调整。在这项工作中，我们成功验证了激光衍射分析原位监测在微米和亚微米级 EHD 喷墨打印中的可行性。

引用次数: 0

Optimization and prediction of additively manufactured PLA-PHA biodegradable polymer blend using TOPSIS and GA-ANN 利用 TOPSIS 和 GA-ANN 对添加式制造的聚乳酸--羟乙基苯酚可生物降解聚合物混合物进行优化和预测

IF 1.9 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2024-10-01 DOI: 10.1016/j.mfglet.2024.09.099

Shafahat Ali , Vijayant Mehra , Abdelkrem Eltaggaz , Ibrahim Deiab , Salman Pervaiz

Recent years have seen the proliferation of fused deposition modeling (FDM) as a means of manufacturing biodegradable products, for different applications such as rigid packaging, agricultural and biomedical. Blends of Polyhydroxyalkanoates (PHA) and polylactic acid (PLA) have been investigated to ascertain their prospective applications through FDM. This paper includes three parameters that affect the build process: layer height, nozzle temperature, and flow rate. 3D printed PLA/PHA can be characterized mechanically, and process parameters can be optimized to maximize design functionality. The experimental setup utilized a Taguchi L9 design, and TOSPIS was employed to optimize the output results. Using TOPSIS analysis, 0.2 mm layer thickness, 195 °C nozzle temperature, and 100 % flow rate were found to be the most optimal initiation parameters. The Taguchi analysis was used to analyze the output responses, and it was found that layer height had the greatest influence on mechanical properties, followed by flow rate and nozzle temperature. The percentage elongation at break has been improved significantly by adding PHA i.e., 170 % compared to PLA (5–10 %). This paper presents a framework for in-depth mechanical characterization of PLA-PHA 3D-printed parts, along with methods for optimizing process parameters to achieve optimal performance, as well as tools for modeling output responses using GA-ANN with an accuracy of 95 %.

近年来，熔融沉积建模（FDM）作为一种制造可生物降解产品的手段，在硬包装、农业和生物医学等不同应用领域得到了广泛应用。研究人员对聚羟基烷酸（PHA）和聚乳酸（PLA）的混合物进行了调查，以确定它们在 FDM 中的应用前景。本文包括影响构建过程的三个参数：层高、喷嘴温度和流速。可以对 3D 打印的聚乳酸/羟基乙酸（PLA/PHA）进行机械表征，并对工艺参数进行优化，以最大限度地提高设计功能。实验设置采用田口 L9 设计，并使用 TOSPIS 对输出结果进行优化。通过 TOPSIS 分析，发现 0.2 毫米的层厚、195 ° C 的喷嘴温度和 100 % 的流量是最佳的启动参数。采用田口分析法对输出响应进行分析，发现层高对机械性能的影响最大，其次是流速和喷嘴温度。与聚乳酸（5-10%）相比，添加 PHA 后断裂伸长率显著提高了 170%。本文介绍了对聚乳酸-PHA 三维打印部件进行深入机械特性分析的框架，以及优化工艺参数以实现最佳性能的方法，还介绍了使用 GA-ANN 对输出响应进行建模的工具，建模精度高达 95%。

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引用次数: 0

Predictive models for 3D inkjet material printer using automated image analysis and machine learning algorithms 利用自动图像分析和机器学习算法建立三维喷墨材料打印机的预测模型

IF 1.9 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2024-10-01 DOI: 10.1016/j.mfglet.2024.09.101

Mutha Nandipati, Michael Ogunsanya, Salil Desai

Additive manufacturing (AM) is a smart manufacturing process to fabricate components with high precision, minimal post-processing, and increased component complexity in a variety of materials. This research focuses on developing automated image analysis and predictive models for a widely used 3D material inkjet printing (IJP) process. The interplay of four input process parameters, which include frequency, voltage, temperature, and meniscus vacuum, on the output metrics of the inkjet printer was evaluated using statistical measures (ANOVA). Droplet types were classified as no drop, satellite drop, and normal drop using four machine learning classifiers, including random forest, support vector classifier, k-nearest neighbor, and decision trees. Hyperparameter tuning was performed for each model for over 486 data points. Regression predictive models were developed for both ink droplet velocity and volume with three linear models (linear, lasso, and ridge regression) and four non-linear models (random forest, decision tree, support vector regression, and k-nearest neighbor). Mean squared error and the coefficient of determination, r-squared value, were used to evaluate the performance of the predictive models. For the drop type classification models, k-fold of 5 yielded the highest accuracy for the RF, KNN, and DT models of around 98%. Similarly, for the regression based predictive models RF, DT and KNN accuracy results ranged from 97 to 99%. All the machine learning models were validated with experimental data with high prediction accuracies accuracy. This research serves as a foundation for developing design guidelines for 3D material inkjet printing with applications in biosensors, flexible electronics, and regenerative tissue engineering.

快速成型制造（AM）是一种智能制造工艺，可利用各种材料制造出精度高、后处理最少、部件复杂度更高的部件。本研究的重点是为广泛使用的三维材料喷墨打印（IJP）工艺开发自动图像分析和预测模型。使用统计方法（方差分析）评估了四个输入工艺参数（包括频率、电压、温度和半月板真空度）对喷墨打印机输出指标的相互影响。使用四种机器学习分类器（包括随机森林、支持向量分类器、k-近邻和决策树）将液滴类型分为无液滴、卫星液滴和正常液滴。每个模型都对超过 486 个数据点进行了超参数调整。利用三个线性模型（线性、套索和脊回归）和四个非线性模型（随机森林、决策树、支持向量回归和 k 最近邻），为墨滴速度和体积开发了回归预测模型。平均平方误差和判定系数 r 平方值用于评估预测模型的性能。在水滴类型分类模型中，k-fold 为 5 时，RF、KNN 和 DT 模型的准确率最高，约为 98%。同样，对于基于回归的预测模型，RF、DT 和 KNN 的准确率在 97% 到 99% 之间。所有机器学习模型都通过实验数据进行了验证，预测准确率较高。这项研究为制定三维材料喷墨打印设计指南奠定了基础，可应用于生物传感器、柔性电子器件和再生组织工程。

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引用次数: 0

A study on the gas film formation in electrochemical discharging processes by molecular dynamics simulation 通过分子动力学模拟研究电化学放电过程中的气膜形成

IF 1.9 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2024-10-01 DOI: 10.1016/j.mfglet.2024.09.042

Yu-Jen Chen, Murali Sundaram

Molecular Dynamics (MD) simulations have emerged as a potent analytical tool for dissecting the intricate processes involved in nano gas film bubble generation. This study employs MD simulations to identify critical voltage that marks the transition from bubble saturation to gas film formation, while employing a mimic electrolysis model to expedite simulations through accelerated molecular insert rates. The simulations provide insights into underlying mechanisms, revealing the reforming and condensing dynamics of gas structures preceding gas film genesis. Experimental validation corroborates the accuracy of critical voltage predictions derived from MD simulations, with the close alignment between simulated critical points and experimental outcomes underscoring the robust predictive capability of MD simulations in elucidating electrochemical discharging (ECD) processes.

分子动力学（MD）模拟已成为剖析纳米气膜气泡生成复杂过程的有效分析工具。本研究利用 MD 模拟来确定从气泡饱和到气膜形成的临界电压，同时采用模拟电解模型，通过加快分子插入速率来加速模拟。模拟深入揭示了气膜形成前气体结构的重整和冷凝动态。实验验证证实了 MD 模拟得出的临界电压预测的准确性，模拟临界点与实验结果之间的密切吻合强调了 MD 模拟在阐明电化学放电 (ECD) 过程中的强大预测能力。

引用次数: 0

NAMRC 52 fast-tracked research papers to Journal of Manufacturing Systems and Journal of Manufacturing Processes NAMRC 向《制造系统杂志》和《制造工艺杂志》快速提交 52 篇研究论文

IF 1.9 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2024-10-01 DOI: 10.1016/j.mfglet.2024.09.003

Robert X. Gao (NAMRI/SME Scientific Committee Chair), Xun Xu (NAMRI/SME Scientific Committee Chair-Elect), Ihab Ragai (NAMRI/SME Scientific Committee Advisor)

引用次数: 0

Hybrid manufacturing cost models: Additive friction stir deposition, measurement, and CNC machining 混合制造成本模型：快速摩擦搅拌沉积、测量和数控加工

IF 1.9 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2024-10-01 DOI: 10.1016/j.mfglet.2024.09.038

Nathan Wilson , Robert Patterson , Elijah Charles , Malachi Landis , Joshua Kincaid , Ryan Garcia , Gregory Corson , Tony Schmitz

Based on its potential to reduce lead times, hybrid manufacturing, which often includes both additive manufacturing and machining processes, is receiving more attention from manufacturers as they seek to increase their supply chain resilience and efficiency. A new solid-state additive manufacturing, referred to as additive friction stir deposition (AFSD), has shown the potential to become an important process for hybrid manufacturing. To justify the selection of a hybrid manufacturing approach, the cost needs to be estimated for comparison to conventional approaches. Historically, hybrid manufacturing costs have been difficult to estimate due to the complexity and diversity of the manufacturing processes. This paper proposes cost models that include additive friction stir deposition, structured light scanning, milling, and turning, which can be combined in hybrid manufacturing process planning. These cost models are demonstrated in a case study and cost estimates are compared for hybrid and conventional (machining-only) manufacturing approaches. For the selected case, the hybrid manufacturing process cost was $1007.58, while the conventional milling process cost was $833.60. The results of the case study show that both labor and material costs must be considered to make an informed decision between hybrid and conventional manufacturing approaches.

混合制造（通常包括快速成型制造和机械加工工艺）具有缩短交付周期的潜力，因此正受到制造商的更多关注，因为他们正努力提高供应链的弹性和效率。一种新的固态快速成型制造工艺，即快速摩擦搅拌沉积（AFSD），已显示出成为混合制造重要工艺的潜力。为了证明选择混合制造方法的合理性，需要对成本进行估算，以便与传统方法进行比较。由于制造工艺的复杂性和多样性，混合制造成本一直难以估算。本文提出的成本模型包括快速摩擦搅拌沉积、结构光扫描、铣削和车削，可在混合制造工艺规划中结合使用。这些成本模型在一个案例研究中进行了演示，并对混合制造和传统（纯机械加工）制造方法的成本估算进行了比较。在所选案例中，混合制造工艺成本为 1007.58 美元，而传统铣削工艺成本为 833.60 美元。案例研究结果表明，要在混合制造方法和传统制造方法之间做出明智的决定，必须同时考虑人工成本和材料成本。

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引用次数: 0

Effect of materials and process parameters on machinability of stainless steels 材料和工艺参数对不锈钢机加工性能的影响

IF 1.9 Q3 ENGINEERING, MANUFACTURING

Manufacturing Letters

Pub Date : 2024-10-01 DOI: 10.1016/j.mfglet.2024.09.088

Iqbal Shareef , Durga Kumar Raja Potluri , Gerry Horton

Stainless steels, recognized for their corrosion resistance attributed to a minimum of 11 % Chromium, encompass a variety of alloys with distinctive microstructures and properties. Machinability significantly varies among these alloys. Austenitic steels such as SS303 and 304 present challenges, demonstrating poor surface finish and high power consumption. This study, employing a central composite design, investigates the machinability of AISI 303, 304, 316, AISI 416, and AISI A36. Turning tests with PVD TiAlN-coated inserts revealed optimal parameters for cutting speeds (90.5256–244.411 m/min), feed (0.0635–0.4826 mm/rev), and depth (0.00016–0.00187 m.). Surface finish analysis identified AISI 316 as the best, closely followed by AISI 303. From a power consumption standpoint, AISI 303 performed the best, and concerning fragmented chip morphology, AISI 303 also excelled. The superior performance of AISI 303 is attributed to 2 % Manganese and 0.15 % Sulfur, proving to be the most effective combination compared to the other four steels, resulting in a higher percentage of MnS₂, optimal for improving machinability. The depth of cut emerges as the most influential factor affecting dimensional accuracy. These findings hold practical significance in the selection of stainless steels and corresponding process parameters across various industries, including the manufacturing of heavy earthmoving equipment. By shedding light on the optimal composition and machining conditions, this study contributes valuable insights for enhancing performance and efficiency in stainless steel applications.

不锈钢因至少含有 11% 的铬而被公认为具有耐腐蚀性，它包括各种具有独特微观结构和性能的合金。这些合金的机加工性能差异很大。奥氏体钢（如 SS303 和 304）面临的挑战是表面光洁度差、功耗高。本研究采用中心复合设计，调查了 AISI 303、304、316、AISI 416 和 AISI A36 的机加工性能。使用 PVD TiAlN 涂层刀片进行的车削测试显示了切削速度（90.5256-244.411 米/分钟）、进给量（0.0635-0.4826 毫米/转）和深度（0.00016-0.00187 米）的最佳参数。表面光洁度分析表明，AISI 316 的光洁度最好，紧随其后的是 AISI 303。从功耗的角度来看，AISI 303 的性能最佳，而在碎屑形态方面，AISI 303 也表现出色。AISI 303 的优异性能归功于 2% 的锰和 0.15% 的硫，与其他四种钢材相比，这是最有效的组合，从而产生了更高比例的 MnS2，是提高加工性能的最佳选择。切削深度是影响尺寸精度的最大因素。这些发现对各行各业（包括重型推土设备制造行业）选择不锈钢和相应的工艺参数具有实际意义。通过阐明最佳成分和加工条件，这项研究为提高不锈钢应用的性能和效率提供了有价值的见解。

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