Journal of Manufacturing Processes最新文献_第8页

Achievement of ductile-regime removal in fabricating Gaussian curved microstructure processed by micro ball-end milling on soft-brittle KDP surface 在软脆 KDP 表面使用微球端铣削加工高斯曲线微结构时实现韧性消除

IF 6.1 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2024-10-03 DOI: 10.1016/j.jmapro.2024.09.103

Jian Cheng , Hongqin Lei , Yong Xiao , Linjie Zhao , Mingjun Chen , Youwang Hu , Qi Liu , Dinghuai Yang , Wenyu Ding , Guang Chen

Laser-induced damage points (known as defects) would seriously reduce the service life of large-aperture KDP optics in high-power laser devices. The ball-end milling procedure is recognized as an efficient method for creating a Gaussian mitigation pit (GMP) to restore the optical transmission performance of functional KDP crystals by removing defects. Nevertheless, achieving smooth and flawless Gaussian curved microstructures is a massive challenge for soft-brittle KDP crystals. Herein, a judging criterion of the ductile-regime machining for the GMP is developed by the models of uncut chip thickness (UCT) and critical milling depth. Simultaneously, the obtained judging criterion can be validated by the microstructure fabrication experiments. Besides, considering the spindle vibration, plowing effect, and machined surface texture, the influence of spindle speed (n), feed rate (f), and tool mark interval (d) on the surface formation mechanism of the GMP is analyzed, respectively. It can be discovered that the n of up to 60,000 r/min can lead to severe velocity fluctuation of the motion system, increasing the UCT and causing brittle fractures on the KDP surface. A low f can result in an undesirable plowing phenomenon, and a large number of crystal materials are accumulated in the up-cut process. Once the f reaches 72 mm/min, the tool path would fluctuate significantly, resulting in poor GMP surface texture. When the d exceeds 15 μm, the surface quality of the GMP can no longer meet the engineering requirements of the Ra ≤ 50 nm. Moreover, the optimized processing parameters of the microstructure fabrication are 47,800 r/min in the n, 30 mm/min in the f, and 5 μm in the d. This study can provide crucial guidance for obtaining the ultra-smooth and defect-free GMP processed in the ductile regime, which would resultantly possess significant theoretical importance and practical value in enhancing the optical properties of flawed KDP crystals.

激光诱发的损伤点（称为缺陷）会严重缩短高功率激光设备中大孔径 KDP 光学元件的使用寿命。球端铣削程序被认为是一种有效的方法，可以通过消除缺陷来创建高斯缓和凹坑（GMP），从而恢复功能性 KDP 晶体的光学传输性能。然而，对于软脆的 KDP 晶体来说，实现光滑无瑕的高斯曲线微结构是一项巨大的挑战。本文通过未切削切屑厚度（UCT）和临界铣削深度模型，建立了 GMP 的韧性机制加工判断标准。同时，所获得的判断标准可通过微结构制造实验进行验证。此外，考虑到主轴振动、耕作效应和加工表面纹理，分别分析了主轴转速（n）、进给速度（f）和刀痕间隔（d）对 GMP 表面形成机理的影响。结果发现，当 n 高达 60,000 r/min 时，会导致运动系统的速度剧烈波动，增加 UCT，使 KDP 表面产生脆性断裂。过低的 f 会导致不良的犁耕现象，并在上切过程中积累大量晶体材料。一旦 f 达到 72 mm/min，刀具路径就会出现明显波动，导致 GMP 表面纹理不佳。当 d 超过 15 μm 时，GMP 的表面质量已无法满足 Ra ≤ 50 nm 的工程要求。此外，微结构制造的优化加工参数为 n 值 47800 r/min、f 值 30 mm/min 和 d 值 5 μm。这项研究为获得在韧性机制下加工的超光滑无缺陷 GMP 提供了重要指导，从而在提高有缺陷 KDP 晶体的光学性能方面具有重要的理论意义和实用价值。

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引用次数: 0

A GPU-based approach for 5-axis flute grinding of end-mills with complex grinding wheel 基于 GPU 的复杂砂轮立铣刀五轴刃磨方法

IF 6.1 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2024-10-03 DOI: 10.1016/j.jmapro.2024.09.075

Jianping Yang, Liming Wang, Yang Fang, Fangyi Li, Jianfeng Li

End-mills are used widely in industry, in which efficient chip evacuation and enhanced tool performance are directly influenced by the flute shapes. Generally, complex grinding wheels are employed to create intricate flute shapes with CNC grinding. In the kinematic of flute grinding, several transcendental equations with high non-linearity is derived and required to be solved. In some cases, the explicit expression for flute cannot be derived and the numerical method are generally applied, which requires various derivation or numerical program for different flute shapes. To address these challenges, this paper proposed a GPU-based approach for 5-axis flute grinding of end-mills with complex grinding wheel. In this method, a mesh model of the grinding wheel was established to transform the above complex equations into finding a set of point cloud which satisfied the envelope condition. To accelerate the computation time for searching those point cloud, a generalized GPU parallel processing algorithm were used to execute multiple compute threads. The validity of the approach was verified through a series of experiments. It demonstrated that this method achieved remarkable precision and broad applicability, fulfilling the diverse requirements of various grinding wheels and flute shapes. Furthermore, the high efficiency and versatility of this approach make it have great potential in the application of flute-grinding with various complex wheel in real-time path planning.

立铣刀在工业中应用广泛，其槽形直接影响到高效排屑和提高刀具性能。一般情况下，使用复杂的砂轮通过数控磨削加工出复杂的刃形。在刃磨运动学中，需要推导和求解多个非线性程度较高的超越方程。在某些情况下，无法推导出刃口的显式表达，一般采用数值方法，这就需要针对不同的刃口形状进行不同的推导或数值程序。为解决这些难题，本文提出了一种基于 GPU 的复杂砂轮立铣刀五轴槽磨削方法。在该方法中，通过建立砂轮的网格模型，将上述复杂方程转化为满足包络条件的点云集合。为了加快搜索这些点云的计算时间，使用了通用 GPU 并行处理算法来执行多个计算线程。通过一系列实验验证了该方法的有效性。实验表明，该方法精度高、适用性广，能满足各种砂轮和刃口形状的不同要求。此外，该方法的高效性和多功能性使其在实时路径规划中应用于各种复杂砂轮的刃磨方面具有巨大潜力。

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引用次数: 0

An investigation of the formability of ultra-thin CP-Ti-Gr2 foils considering thickness-to-grain-size effects under controlled heat treatment in μ-ISF 超薄 CP-Ti-Gr2 箔在 μ-ISF 受控热处理条件下的成型性研究，考虑厚度-晶粒尺寸效应

IF 6.1 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2024-10-02 DOI: 10.1016/j.jmapro.2024.09.107

Mainak Pal, Anupam Agrawal, Chandrakant K. Nirala

Micro-forming is an emerging micro-manufacturing process for the fabrication of miniature parts/components made of ultra-thin sheets (foils), forged billets, rods, etc. Achieving high formability in the micro-incremental sheet forming (μISF) process is difficult due to the size-effect and non-optimal selection of process parameters viz. step depth (∆z). The major sources of size-effects are pure volume source, surface-to-volume ratio, thickness-to-grain-size (t/d ratio), surface structure scalability, etc. In the micro-scale processes, studying the grain size of the material is crucial to understand the deformation behaviour. Additionally, the anisotropy is very prominent in thin foils and affects the micro-forming process adversely. In the present work, the intrinsic anisotropy of the foils is minimized through controlled heat treatment, and varying grain sizes, having different microstructures, are generated to investigate their effect on the formability of CP-Ti-Gr2 foils. Initially, the properties of the received material are tested along different directions through the uniaxial tensile test, followed by furnace annealing to produce equiaxed recrystallized grains and reduce the anisotropy of the foils. Subsequently, the specimens are heat-treated at different temperatures to generate a wide spectrum of grain sizes. Through extensive μISF experiments, it was established that higher annealing temperature and increase in grain size assisted in improving the ductility of the foils, leading to enhanced formability. Therefore, the combined effect of the grain size and step depth on the formability of the components is investigated. A relationship between formability and t/d ratio was established and its critical value was obtained. Interesting observations, contrary to those in macro-ISF process were observed, e.g. higher step depth in μISF helped in improving the formability of the micro-parts. The results were confirmed by measuring the forming forces during the process, and it presented a strong correlation with the yield stress values, further correlated with varying grain sizes of the foil. This work could pave the way for designing the μISF process parameters considering the size-effects at micro-scale deformation, through optimum t/d ratio, for maximizing the formability.

微型成形是一种新兴的微型制造工艺，用于制造由超薄板（箔）、锻造坯料、棒材等制成的微型零件/组件。由于尺寸效应和步进深度（Δz）等工艺参数的非最佳选择，在微增薄板成形（μISF）工艺中实现高成形性十分困难。尺寸效应的主要来源是纯体积源、表面-体积比、厚度-晶粒尺寸（t/d 比）、表面结构可扩展性等。在微尺度过程中，研究材料的晶粒尺寸对了解变形行为至关重要。此外，各向异性在薄金属箔中非常突出，会对微成型工艺产生不利影响。在本研究中，通过控制热处理使薄片的内在各向异性最小化，并生成具有不同微观结构的不同晶粒大小，以研究它们对 CP-Ti-Gr2 薄片成型性的影响。首先，通过单轴拉伸试验沿不同方向测试接收材料的性能，然后进行炉内退火，以产生等轴再结晶晶粒并降低箔的各向异性。随后，在不同温度下对试样进行热处理，以产生各种晶粒尺寸。通过大量的 μISF 实验，确定了较高的退火温度和晶粒大小的增加有助于改善铝箔的延展性，从而提高成型性。因此，我们研究了晶粒大小和台阶深度对部件成型性的综合影响。研究确定了成型性与 t/d 比率之间的关系，并得出了其临界值。观察到了与宏观 ISF 工艺相反的有趣现象，例如，μISF 中较高的台阶深度有助于改善微型部件的成型性。测量过程中的成型力证实了这一结果，它与屈服应力值密切相关，并与箔的不同晶粒尺寸进一步相关。这项工作可以为设计 μISF 工艺参数铺平道路，考虑到微尺度变形时的尺寸效应，通过最佳的 t/d 比，最大限度地提高成形性。

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引用次数: 0

A defect classification algorithm for gas tungsten arc welding process based on unsupervised learning and few-shot learning strategy 基于无监督学习和少量学习策略的气体钨极氩弧焊工艺缺陷分类算法

IF 6.1 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2024-10-02 DOI: 10.1016/j.jmapro.2024.09.084

Qiang Liu , Runquan Xiao , Yuqing Xu , Jingyuan Xu , Shanben Chen

Welding defect prediction is the foundation for ensuring welding quality in gas tungsten arc welding (GTAW). In the prediction process, method based on molten pool vision is the most effective. Since the classification of molten pool defects relies on a substantial volume of labeled data, it is challenging for the models to be applied industrially. This paper presents an algorithm, FS-Classifier, that can achieve high prediction accuracy based on a limited amount of labeled data. The FS-Classifier comprises two stages: Firstly, an unsupervised training approach named RaP is designed to pre-train the feature extractor using extensive unlabeled daily datasets. The RaP consists of a rotation angle prediction task and a position prediction task, which ensure that the network focuses on salient features and precise elements, respectively. Secondly, the support vectors constructed from limited labeled data are used for the feature classifier. The input data is classified to certain class by computing its distances to support vector. The model achieves an accuracy of 94.5 % on the private dataset and 92.8 % on the public dataset for the six classes of defects using 5 % of labeled data volume. In addition, comparative experiments show that our method only requires 5 % of labeled data to achieve accuracy comparable to traditional supervised learning methods. The proposed algorithm addresses the issue of relying on a substantial amount of labeled data in welding process defect classification.

焊接缺陷预测是确保气体钨极氩弧焊（GTAW）焊接质量的基础。在预测过程中，基于熔池视觉的方法最为有效。由于熔池缺陷分类依赖于大量的标记数据，因此模型的工业应用具有挑战性。本文提出了一种算法 FS-分类器，它能在有限的标注数据量基础上实现较高的预测精度。FS-Classifier 包括两个阶段：首先，设计了一种名为 RaP 的无监督训练方法，利用大量未标记的日常数据集对特征提取器进行预训练。RaP 包括一个旋转角度预测任务和一个位置预测任务，确保网络分别关注突出特征和精确元素。其次，从有限的标注数据中构建的支持向量被用于特征分类器。通过计算输入数据与支持向量的距离，将输入数据归入特定类别。使用 5% 的标注数据量，该模型在私有数据集上对六类缺陷的准确率达到 94.5%，在公共数据集上达到 92.8%。此外，对比实验表明，我们的方法只需要 5% 的标注数据就能达到与传统监督学习方法相当的准确率。所提出的算法解决了焊接工艺缺陷分类中依赖大量标注数据的问题。

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引用次数: 0

Metal additive manufacturing: Principles and applications 金属增材制造：原理与应用

IF 6.1 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2024-10-02 DOI: 10.1016/j.jmapro.2024.09.101

S. Patel, Y. Liu, Z. Siddique, I. Ghamarian

Additive manufacturing (AM) of metals has gained massive attention due to its salient features, such as a tool-free process, near-net shape product development, less fabrication time, and no restriction on product size. This paper provides a brief overview of common metal AM processes, including powder bed fusion, binder jetting, directed energy deposition, and sheet lamination. The advantages of each metal AM technology and their limitations are compared and addressed with examples. Critical steps to ensure the successful 3D printing of metal structures are discussed for each metal AM approach. The effect of each processing parameter is critically analyzed to enhance fabrication characteristics. The metal AM mechanisms, optimization of processing parameters, powder preparation techniques and their effects on the powder morphology, and applications of metal AM are discussed.

金属快速成型制造（AM）具有无需工具、产品开发接近净形、制造时间短、不受产品尺寸限制等显著特点，因而受到广泛关注。本文简要介绍了常见的金属 AM 工艺，包括粉末床熔融、粘合剂喷射、定向能沉积和薄片层压。本文通过实例对每种金属 AM 技术的优势和局限性进行了比较和论述。针对每种金属 AM 方法，讨论了确保成功 3D 打印金属结构的关键步骤。对每个加工参数的影响进行了批判性分析，以提高制造特性。讨论了金属 AM 机制、加工参数优化、粉末制备技术及其对粉末形态的影响，以及金属 AM 的应用。

引用次数: 0

Machining performance and wear mechanism of CVD diamond-coated micro-grinding tools in micro-grinding of fused silica CVD 金刚石涂层微磨工具在熔融石英微磨中的加工性能和磨损机理

IF 6.1 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2024-10-01 DOI: 10.1016/j.jmapro.2024.09.037

Wei Li , ChangJin Long , Zhenyang Deng , XuDong Guo , YingHui Ren , Qiang Lin , Bin Shen

This paper investigates the fabrication and application of chemical vapor deposition (CVD) diamond-coated micro-grinding tools in machining fused silica. The study innovatively fabricated four diamond-coated micro-grinding tools (10,000#, 6000#, 3000#, 1500#) using hot filament chemical vapor deposition and explored their formation mechanism, grinding performance, as well as wear and failure mechanism. The results revealed that a larger grain size leads to a flatter film surface with prominent planar features, columnar growth characteristics, and fewer internal defects. Machining experiments revealed that the grinding quality increases with increasing feed rate and grinding depth. On the other hand, it decreases with increasing spindle speed. Nevertheless, the dominant failure mechanism of 1500# and 3000# micro-grinding tools is primarily brittle fracture. Meanwhile, 6000# micro-grinding tools are featured with both brittle fracture and ductile domain removal. Micro-grinding tools with grind size 10,000# are featured with ductile domain removal and demonstrated the best machining quality. The results showed that crack generation and extension caused by abrasive and bonded wear are the leading causes of diamond film failure in micro-grinding tools, and the larger the average grain size, the better the wear resistance. This research provides new insight into the wear mechanism of diamond-coated micro-grinding tools and contributes to developing CVD diamond-coated micro-grinding tools for precision machining hard and brittle materials.

本文研究了化学气相沉积（CVD）金刚石涂层微磨工具在加工熔融石英中的制造和应用。研究采用热丝化学气相沉积法创新性地制造了四种金刚石涂层微磨工具（10000#、6000#、3000#、1500#），并探讨了它们的形成机理、磨削性能以及磨损和失效机理。结果表明，晶粒尺寸越大，薄膜表面越平整，平面特征越突出，具有柱状生长特征，内部缺陷越少。加工实验表明，磨削质量随着进给速度和磨削深度的增加而提高。另一方面，磨削质量随着主轴转速的增加而降低。不过，1500#和 3000#微磨工具的主要失效机理是脆性断裂。与此同时，6000# 微粉磨工具既有脆性断裂，也有韧性域去除。磨削尺寸为 10,000# 的微磨工具具有韧性域去除的特点，并表现出最佳的加工质量。研究结果表明，磨料磨损和粘结磨损导致的裂纹产生和扩展是微磨工具金刚石膜失效的主要原因，平均粒度越大，耐磨性越好。这项研究为了解金刚石涂层微磨工具的磨损机理提供了新的视角，有助于开发用于精密加工硬脆材料的 CVD 金刚石涂层微磨工具。

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引用次数: 0

Bionic design and optimization of cutting tools: Applications and processability 切削工具的仿生设计和优化：应用和加工性能

IF 6.1 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2024-09-30 DOI: 10.1016/j.jmapro.2024.09.058

Shuai Huang , Sheng Liu , Dazhong Wang , Akiyama Takao , Shujing Wu , Chen Li , Daohui Xiang , Changhe Li

Cutting is a fundamental machining method extensively utilized across various fields, including mechanical engineering, agriculture, forestry, biomedical instrumentation, mineral exploration, and extraterrestrial missions. However, during cutting operations, tools are exposed to high temperatures and friction, which result in diminished cutting efficiency, reduced tool life, and compromised workpiece quality. Advances in bionics are gradually mitigating these challenges. Bionic design provides rich, reliable, and efficient prototypes that enhance tool performance while promoting environmentally friendly, harmonious, and sustainable tool development. In the bionic optimization of cutting tools, the selection of appropriate bionic prototypes and models is crucial. However, the complexity and ambiguity inherent in bionic prototype functions impede the development and widespread adoption of bionic tools. This paper initially focuses on the classification of bionic tools, subsequently proposing five categories of bio-inspired design elements and topological models from the perspective of bio-inspired cutting tools. The second section discusses the applications, advantages, and cutting performance of five types of bionic tools, with an emphasis on both the biomimetic optimization of the tool body and non-tool bodies. These tools are designed by emulating the diverse biological characteristics exhibited by various organisms. Additionally, the underlying mechanisms of the five categories of bionic tools, as well as the corresponding optimization strategies, are explored. Finally, this paper summarizes research on bionic tools and analyzes the current opportunities and challenges they face. In summary, compared to traditional tools, bionic tools demonstrate superior performance in energy efficiency, friction reduction, wear resistance, lubrication, extended service life, and multifunctionality. This offers valuable insights for researchers involved in the design and development of cutting tools.

切削是一种基本的加工方法，广泛应用于机械工程、农业、林业、生物医学仪器、矿物勘探和地外任务等各个领域。然而，在切削操作过程中，刀具会暴露在高温和摩擦的环境中，从而导致切削效率降低、刀具寿命缩短以及工件质量受损。仿生学的进步正在逐步缓解这些挑战。仿生设计可提供丰富、可靠和高效的原型，在提高刀具性能的同时，促进环保、和谐和可持续的刀具发展。在切削工具的仿生优化过程中，选择合适的仿生原型和模型至关重要。然而，仿生原型功能固有的复杂性和模糊性阻碍了仿生工具的开发和广泛应用。本文首先关注仿生工具的分类，随后从生物启发切削工具的角度提出了五类生物启发设计元素和拓扑模型。第二部分讨论了五类仿生工具的应用、优势和切削性能，重点是工具本体和非工具本体的仿生优化。这些工具是模仿各种生物的不同生物特性设计的。此外，本文还探讨了五类仿生工具的基本机制以及相应的优化策略。最后，本文对仿生工具的研究进行了总结，并分析了当前仿生工具面临的机遇和挑战。总之，与传统工具相比，仿生工具在节能、减少摩擦、耐磨、润滑、延长使用寿命和多功能性等方面表现出卓越的性能。这为从事切削工具设计和开发的研究人员提供了宝贵的见解。

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引用次数: 0

Online monitoring method for chip pin with minor deformation defects based on depth-histogram modalities and target-oriented multimodal self-attention mechanism 基于深度组态图模式和目标导向多模态自关注机制的芯片引脚微小变形缺陷在线监测方法

IF 6.1 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2024-09-30 DOI: 10.1016/j.jmapro.2024.09.063

Changdu Du, Lei Xu, Jun Chen, Nachuan He

In the process of chip SMT (surface mounting technology), the quality of the chip pins determines the success rate of the mounting process. However, existing target detection algorithms present poor performance when dealing with deformations in the pins, which is insufficient to meet the industrial demands for accuracy and speed of online monitoring. To solve this problem, a real-time detection method based on DH (Depth-Histogram) Modalities and TMSM (Target-oriented Multimodal Self-attention Mechanism) is proposed. There are three parts in this method, including feature extraction, feature fusion, and decision module. Firstly, a lightweight network for feature extraction and fusion is employed to extract geometric information from the depth images. Subsequently, the Decision Module is used to determine whether there are defects in the pins. Within this framework, the HIEF (Histogram-Integrated Embedding Function) is utilized to extract a one-dimensional vector with height information from the histogram, which is then aligned with the flattened depth image to form DH Modalities. To validate the effectiveness of the proposed algorithm, two datasets are constructed. Experimental results demonstrate that the proposed method has a good performance to meet the speed and accuracy requirements of online monitoring.

在芯片 SMT（表面贴装技术）工艺中，芯片引脚的质量决定了贴装工艺的成功率。然而，现有的目标检测算法在处理引脚变形时性能较差，无法满足工业领域对在线监测精度和速度的要求。为解决这一问题，我们提出了一种基于 DH（深度-组态图）模态和 TMSM（面向目标的多模态自注意机制）的实时检测方法。该方法分为三个部分，包括特征提取、特征融合和决策模块。首先，采用轻量级特征提取和融合网络从深度图像中提取几何信息。随后，决策模块用于确定插脚是否存在缺陷。在此框架内，利用 HIEF（直方图集成嵌入函数）从直方图中提取包含高度信息的一维向量，然后将其与扁平化深度图像对齐，形成 DH 模态。为了验证所提算法的有效性，我们构建了两个数据集。实验结果表明，所提出的方法性能良好，能够满足在线监测的速度和准确性要求。

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引用次数: 0

Strip deviation analysis and prediction based on time series methods in hot rolling process 基于时间序列方法的热轧过程中的板带偏差分析和预测

IF 6.1 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2024-09-30 DOI: 10.1016/j.jmapro.2024.09.012

Han Gao , Xu Li , Shuren Jin , Yumei Qin , Jianzhao Cao , Feng Luan , Dianhua Zhang

Strip deviation presents a significant challenge in hot rolling processes, affecting both product quality and manufacturing efficiency. Currently, most of the strip deviation correction operations rely on manual adjustments, which are labor-intensive and error-prone. This study pioneers the integration of a strip deviation measurement system with a time series prediction model to predict strip deviation and provide operators with timely warning signals. It introduces a novel time series prediction model utilizing dual attention mechanisms: one to identify feature-level correlations and another to capture temporal-level dependencies and patterns. An optimized version of the traditional Multi-Head Attention mechanism, named Compact Multi-Head Attention, is incorporated. To further boost the model's predictive accuracy, a shuffle operation is also integrated. Additionally, the dataset is augmented with rolling force difference and roller gap difference, based on an analysis of strip deviation principles, leading to notable improvements in predictive accuracy. Comprehensive testing with actual data from a hot strip mill confirms the model's outstanding performance in predicting strip deviation, surpassing several baseline models. The results highlight the effectiveness of this approach in strip deviation prediction in industrial environments.

带钢偏差是热轧工艺中的一项重大挑战，会影响产品质量和生产效率。目前，大多数板带偏差校正操作都依赖人工调整，既耗费人力，又容易出错。本研究开创性地将带钢偏差测量系统与时间序列预测模型相结合，预测带钢偏差并为操作人员提供及时的预警信号。它引入了一种利用双重关注机制的新型时间序列预测模型：一种用于识别特征级相关性，另一种用于捕捉时间级依赖性和模式。该模型是传统多头注意力机制的优化版本，被命名为紧凑型多头注意力。为了进一步提高模型的预测准确性，还集成了洗牌操作。此外，根据对板带偏差原理的分析，数据集还增加了轧制力差异和轧辊间隙差异，从而显著提高了预测精度。利用热轧带钢轧机的实际数据进行的综合测试证实，该模型在预测带钢偏差方面表现出色，超过了多个基准模型。结果凸显了这种方法在工业环境中预测板带偏差的有效性。

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引用次数: 0

The effects of TiC particle on microstructure and mechanical properties of Inconel 718 fabricated by selective arc melting TiC 粒子对选择性电弧熔炼法制造的 Inconel 718 的微观结构和机械性能的影响

IF 6.1 1区工程技术 Q1 ENGINEERING, MANUFACTURING

Journal of Manufacturing Processes

Pub Date : 2024-09-30 DOI: 10.1016/j.jmapro.2024.09.050

Weiran Xie , Xiaodong Yang , Haiou Yang , Xiaoming Duan

Adding titanium carbide reinforcement particles into Inconel 718 matrix is considered to be an effective way of further improving the mechanical properties of Inconel 718 components fabricated by selective laser melting (SLM). However, SLM-fabricated TiC/Inconel 718 composite components typically exhibit the pore defects caused by poor wettability between the matrix and the TiC particles, which attributed to the low heat input of laser during deposition. A powder bed based additive manufacturing method using arc plasma as heat source, named selective arc melting (SAM), was developed in previous study by the authors. Significantly higher heat input from the arc heat source contributes to inhibiting the generation of pore defects in TiC/Inconel 718 composite components during SAM. In this paper, thin-walled parts of Inconel 718 and TiC/Inconel 718 composites were first fabricated by the SAM method. Then, the deposition geometry, microstructure, tensile properties and hardness of as-fabricated Inconel 718 and TiC/Inconel 718 composites components were systematically studied and compared. Results showed that a large number of dispersed carbides and fine equiaxed grains were observed in the TiC/Inconel 718 composites. Most of the added TiC particles were melted and the Inconel 718 matrix bonded well to the carbide precipitation phases. The TiC/Inconel 718 composite part exhibited better surface quality, tensile strength, ductility and hardness than that of Inconel 718. The combined effects of precipitation strengthening and fine grain strengthening were the main reasons for the better mechanical performance of the TiC/Inconel 718 composite part.

在 Inconel 718 基体中添加碳化钛增强颗粒被认为是进一步改善通过选择性激光熔化（SLM）制造的 Inconel 718 组件机械性能的有效方法。然而，SLM 制造的 TiC/Inconel 718 复合材料部件通常会出现孔隙缺陷，原因是基体与 TiC 颗粒之间的润湿性较差，这归因于沉积过程中激光输入的热量较低。作者在之前的研究中开发了一种基于粉末床的增材制造方法，使用电弧等离子体作为热源，命名为选择性电弧熔化（SAM）。在 SAM 过程中，电弧热源输入的热量明显较高，这有助于抑制 TiC/Inconel 718 复合材料部件中孔隙缺陷的产生。本文首先采用 SAM 方法制造了 Inconel 718 和 TiC/Inconel 718 复合材料的薄壁部件。然后，系统研究并比较了制备的 Inconel 718 和 TiC/Inconel 718 复合材料部件的沉积几何形状、微观结构、拉伸性能和硬度。结果表明，在 TiC/Inconel 718 复合材料中观察到大量分散的碳化物和细小的等轴晶粒。大部分添加的 TiC 颗粒被熔化，Inconel 718 基体与碳化物析出相很好地结合在一起。TiC/Inconel 718 复合材料部件的表面质量、抗拉强度、延展性和硬度均优于 Inconel 718。析出强化和细晶粒强化的共同作用是 TiC/Inconel 718 复合材料部件具有更好机械性能的主要原因。

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引用次数: 0