Advances in Industrial and Manufacturing Engineering最新文献_第2页

Comprehensive pore defect analysis for electron beam-powder bed fusion of Ti48Al2Cr2Nb 电子束-粉末床熔合Ti48Al2Cr2Nb的孔隙缺陷综合分析

IF 6 Q2 ENGINEERING, INDUSTRIAL

Advances in Industrial and Manufacturing Engineering

Pub Date : 2025-08-27 DOI: 10.1016/j.aime.2025.100170

Tomisin Ayeni , Paria Karimi , Mohsen K. Keshavarz , Esmaeil Sadeghi , Mahdi Habibnejad-korayem , Mihaela Vlasea

The process-microstructure relationship of gamma-titanium aluminide (Ti-48Al-2Cr-2Nb) parts fabricated via electron beam-powder bed fusion (PBF-EB) process was investigated. A set of 107 records of process parameter combinations were deployed to analyze and classify relative density, lack-of-fusion (LoF) and Gas porosity defects. The bulk density ranges spanned 88 %–99.99 %, with Gas porosity spanning 0.01 %–0.30 %, and lack-of-fusion defects spanning 0.001 %–12 %. Based on literature pertaining to defects addressable via hot isostatic pressing, four classes of density performance were identified: excellent (>99.8 %), good (99.6–99.8 %), poor (98.0–99.6 %), and failed (<98.0 %). For the purpose of this study, a high density outcome (excellent class) is identified to be ideal in terms of expected mechanical properties, specifically strength, fatigue, and ductility. Pore properties were mapped against different energy representations, for example, volumetric energy density (VED) and normalized enthalpy (NE). The results showed the importance of utilizing NE to visualize data and identify zones in the process parameter space where best performance is expected. A region of NE > 15 is expected to have an excellent performance, whereas NE < 10 is expected to result in unacceptable porosity outcomes.

研究了电子束-粉末床熔合（PBF-EB）法制备γ -钛铝（Ti-48Al-2Cr-2Nb）零件的工艺-微观结构关系。利用107条工艺参数组合记录，对相对密度、熔合不足（LoF）和气体孔隙度缺陷进行分析和分类。体积密度范围为88% - 99.99%，气体孔隙度范围为0.01% - 0.30%，缺乏熔合缺陷范围为0.001 % - 12%。根据有关通过热等静压可解决的缺陷的文献，确定了四类密度性能：优秀（99.8%），良好（99.6 - 99.8%），差（98.0 - 99.6%）和不合格（98.0%）。为了本研究的目的，高密度的结果（优异级）被认为是理想的，就预期的机械性能而言，特别是强度，疲劳和延展性。孔隙性质根据不同的能量表示进行映射，例如，体积能量密度（VED）和归一化焓（NE）。结果显示了利用NE可视化数据和识别过程参数空间中预期最佳性能的区域的重要性。NE >； 15层的储层预计具有优异的性能，而NE >； 10层的储层预计将产生不可接受的孔隙度。

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引用次数: 0

Analysis of process parameter variations and heat treatment effects on the microstructure and mechanical properties of Inconel 718 fabricated by laser powder directed energy deposition (LP-DED) 工艺参数变化及热处理对激光粉末定向能沉积（LP-DED）制备Inconel 718显微组织和力学性能的影响

IF 6 Q2 ENGINEERING, INDUSTRIAL

Advances in Industrial and Manufacturing Engineering

Pub Date : 2025-08-16 DOI: 10.1016/j.aime.2025.100169

Dana Godinez , Anannya Doris , Edel Arrieta , Lawrence E. Murr , Colton Katsarelis , Paul R. Gradl , Amit J. Lopes , Francisco Medina

This study investigates the influence of laser power and subsequent heat treatments on the microstructure and mechanical properties of Inconel 718 specimens fabricated via Laser Powder Directed Energy Deposition (LP-DED). Five sets of samples, produced using laser power ranging from 350 W to 2620 W, were subjected to a standardized heat treatment process comprising stress relief, hot isostatic pressing (HIP), solution treatment, and two-step aging. The evolution of the microstructure at each heat treatment stage was characterized in correlation with hardness, tensile properties, and fatigue life. Results demonstrate that complete heat treatment homogenizes and refines the microstructure, transitioning from dendritic to an austenitic structure with annealing twins, leading to an increase in hardness. Additionally, despite variations in printing parameters, mechanical properties such as tensile strength and fatigue resistance remained consistent. This study reveals that specimens fabricated at 350 W exhibited the finest microstructure, yielding overall superior mechanical properties. These findings contribute to the optimization of post-processing methodologies for LP-DED-manufactured Inconel 718 components, particularly for aerospace applications.

研究了激光功率和后续热处理对激光粉末定向能沉积法（LP-DED）制备的Inconel 718显微组织和力学性能的影响。使用350 W至2620 W的激光功率生产的五组样品进行了标准化热处理工艺，包括应力消除，热等静压（HIP），固溶处理和两步时效。各热处理阶段显微组织的演变特征与硬度、拉伸性能和疲劳寿命相关。结果表明，完全热处理使组织均匀化和细化，从枝晶组织转变为具有退火孪晶的奥氏体组织，导致硬度提高。此外，尽管打印参数有所不同，但拉伸强度和抗疲劳性等机械性能保持一致。该研究表明，在350 W下制备的样品具有最精细的微观结构，具有整体优异的力学性能。这些发现有助于优化lp - d制造的Inconel 718组件的后处理方法，特别是用于航空航天应用。

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引用次数: 0

Predictive processing maps for laser-powder bed fusion using transfer learning and melt pool geometry 使用迁移学习和熔池几何的激光粉末床熔合预测加工图

IF 3.9 Q2 ENGINEERING, INDUSTRIAL

Advances in Industrial and Manufacturing Engineering

Pub Date : 2025-07-20 DOI: 10.1016/j.aime.2025.100168

F. Bahari-Sambran , A. Orozco-Caballero , F. Carreño , C.M. Cepeda-Jiménez

This study explores the use of artificial neural networks (ANN) and transfer learning (TL) to develop processing maps that guide defect-free manufacturing of as-built L-PBF aluminum (AlSi10Mg) and stainless steel (SS316L) specimens. The complex non-linear relationships between processing parameters and the thermal properties of the materials, which influence melt pool development, highlight the need for machine learning (ML) tools to achieve high-quality processability in a cost-effective manner. Commercial AlSi10Mg and SS316L powders were processed using L-PBF, resulting in various types of porosity, such as keyhole and lack-of-fusion defects, under different processing conditions. We first characterized the bulk density and melt pool features (width and depth) through optical microscopy and image analysis. Next, we trained ANN base models using data from existing literature to predict the bulk density and melt pool geometries of the as-built samples. Finally, we refined these models with our experimental data after transferring the base models. The results indicate that our proposed models and TL methodology effectively predict processing maps, identify optimal processing parameters for maximum density, and establish the threshold for lack-of-fusion porosity.

本研究探索了人工神经网络（ANN）和迁移学习（TL）的使用，以开发加工图，指导成品L-PBF铝（AlSi10Mg）和不锈钢（SS316L）样品的无缺陷制造。加工参数与材料热性能之间复杂的非线性关系会影响熔池的发展，这凸显了机器学习（ML）工具以经济有效的方式实现高质量可加工性的必要性。商用AlSi10Mg和SS316L粉末采用L-PBF进行加工，在不同的加工条件下会产生不同类型的孔隙，如钥匙孔和未熔合缺陷。我们首先通过光学显微镜和图像分析表征了体积密度和熔池特征（宽度和深度）。接下来，我们使用现有文献中的数据训练人工神经网络基础模型来预测建成样品的体积密度和熔池几何形状。最后，在基础模型的基础上，利用实验数据对模型进行了细化。结果表明，我们提出的模型和TL方法有效地预测了加工图，确定了最大密度的最佳加工参数，并建立了缺乏融合孔隙率的阈值。

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引用次数: 0

Implementation and evaluation of an Augmented Reality framework for sustainable practices in Industry 5.0 工业5.0中可持续实践的增强现实框架的实施和评估

IF 3.9 Q2 ENGINEERING, INDUSTRIAL

Advances in Industrial and Manufacturing Engineering

Pub Date : 2025-06-07 DOI: 10.1016/j.aime.2025.100166

Andrea Rega , Francesco Giuseppe Ciampi , Alessandro Zanella , Abdelgafar Ismail , Stanislao Patalano

Industry 5.0 requires practical methods to translate Augmented Reality (AR) concepts into effective shop floor applications, demonstrating their value to operators. This study introduces a framework for implementing and validating Augmented Reality (AR)-based tools designed to enhance sustainability awareness and assist operators in energy management within industrial settings. The approach combines a reference software architecture for rapid AR deployment with a three-part user-experience assessment, measuring usability (System Usability Scale - SUS), technology acceptance (Technology Acceptance Model - TAM), and cognitive workload (NASA-TLX). To test this framework, an AR-based prototype tool was deployed on enterprise smartphones and evaluated in three scenarios: monitoring service-utility energy consumption, monitoring production equipment, and conducting on- and off-the-job training of the operators. Thirty shop floor professionals completed tasks and provided UX feedback. The results showed good usability (mean SUS 78.4/100), with perceived ease of use and contextual relevance driving technology acceptance. Moreover Nasa TLX analysis indicates mental demand as the predominant factor. The findings confirm that the framework enables effective, human-centered AR deployments in modern industry and provides concrete design guidelines for future implementations.

工业5.0需要实用的方法将增强现实（AR）概念转化为有效的车间应用，向操作员展示其价值。本研究介绍了一个框架，用于实施和验证基于增强现实（AR）的工具，旨在提高可持续性意识，并帮助运营商在工业环境中进行能源管理。该方法将用于快速AR部署的参考软件架构与三部分用户体验评估相结合，测量可用性（系统可用性量表- SUS）、技术接受度（技术接受模型- TAM）和认知工作量（NASA-TLX）。为了测试该框架，在企业智能手机上部署了基于ar的原型工具，并在三种场景下进行了评估：监测服务公用事业能耗，监测生产设备，以及对操作员进行在职和脱产培训。30名车间专业人员完成任务并提供用户体验反馈。结果显示了良好的可用性（平均SUS 78.4/100），易用性和上下文相关性驱动技术接受度。此外，Nasa TLX分析表明，心理需求是主要因素。研究结果证实，该框架能够在现代工业中实现有效的、以人为本的AR部署，并为未来的实施提供具体的设计指南。

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引用次数: 0

Study on the influence of substrate preheating and deposition environment on the structural integrity of high carbon steel LMD parts of increased geometrical complexity 基体预热和沉积环境对几何复杂度增加的高碳钢LMD零件结构完整性影响的研究

IF 3.9 Q2 ENGINEERING, INDUSTRIAL

Advances in Industrial and Manufacturing Engineering

Pub Date : 2025-06-07 DOI: 10.1016/j.aime.2025.100167

Federico Mazzucato, Anna Valente

Laser Metal Deposition is finding growing industrial attractiveness thanks to its unique capability to locally restore worn metal components. In recent years, the industry is focusing on the application of metal Additive Manufacturing for the restoration of moulds and dies to improve process efficiency by reducing machine downtime and spare parts storage expenses. Although mould repair proved to be a cost-effective technological solution, the restoration of geometrically complex high carbon steel alloys through laser-based Additive Manufacturing still presents criticalities due to the low material weldability, high material oxygen reactivity, and high residual stresses generated by thermal cycling. This research work aims to analyse the influence of substrate preheating and the building environment on the structural integrity of steel specimens exhibiting 0.85 % carbon content and implementing geometrical features which are generally critical to restore by laser-based processes since they behave as thermal stress concentration. The performed preliminary observations highlight no delamination and no oxide regardless of process conditions. High-density (99.99 %) and crack-free high carbon steel depositions are achieved by reducing melt pool cooling rates during part manufacturing as a result of the increased environmental temperature surrounding the as-deposited material. Metallographic analysis demonstrates that carbide size decreases as cooling rates increase.

激光金属沉积由于其独特的局部修复磨损金属部件的能力，正在发现越来越多的工业吸引力。近年来，业界重点关注金属增材制造在模具修复中的应用，通过减少机器停机时间和备件存储费用来提高工艺效率。尽管模具修复被证明是一种具有成本效益的技术解决方案，但由于材料可焊性低、材料氧反应性高以及热循环产生的高残余应力，通过基于激光的增材制造修复几何复杂的高碳钢合金仍然存在关键问题。本研究工作旨在分析基材预热和建筑环境对碳含量为0.85%的钢试件结构完整性的影响，并实现几何特征，这些特征通常对通过基于激光的工艺恢复至关重要，因为它们表现为热应力集中。所进行的初步观察强调，无论工艺条件如何，都没有分层和氧化。高密度（99.99%）和无裂纹的高碳钢沉积是通过在零件制造过程中降低熔池冷却速率来实现的，因为沉积材料周围的环境温度升高了。金相分析表明，随着冷却速率的增加，碳化物尺寸减小。

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引用次数: 0

Performance of new cutting tool multilayer coatings for machining Ti-6Al-4V titanium alloy under cryogenic cooling conditions 低温冷却条件下加工Ti-6Al-4V钛合金的新型刀具多层涂层性能

IF 3.9 Q2 ENGINEERING, INDUSTRIAL

Advances in Industrial and Manufacturing Engineering

Pub Date : 2025-05-01 DOI: 10.1016/j.aime.2025.100165

Y. Zhang , J.C. Outeiro , C. Nouveau , B. Marcon , L.A. Denguir

Cr/CrN/AlCrN multilayer coatings were recently developed to meet the high challenges of machining Ti-6Al-4V alloy under cryogenic cooling conditions. The multilayer coatings were optimized by multiple deposition conditions and were characterized by multi-methods. It was proved that they are suitable for tribological applications with this alloy under extreme conditions. This paper addresses the performance of these coatings through tool wear tests and analysis. This performance was compared with that obtained in standard machining conditions used in the aerospace industry, which include flood metalworking fluids and uncoated cemented carbide tools. The results show that the application of a multilayer coating can improve significantly the tool life under cryogenic cooling conditions compared to the flood conditions. 33 % improvement of tool life was found under cryogenic cooling conditions when comparing this coating to the uncoated one. A statistical analysis shows a strong correlation between tool wear and the machining forces. This analysis also permitted to build models for predicting tool wear in function of measured forces.

Cr/CrN/AlCrN多层涂层是近年来为满足Ti-6Al-4V合金在低温冷却条件下加工的高要求而开发的。通过多种沉积条件对多层涂层进行了优化，并采用多种方法对其进行了表征。实验证明，它们适用于这种合金在极端条件下的摩擦学应用。本文通过刀具磨损试验和分析，探讨了这些涂层的性能。将该性能与航空航天工业中使用的标准加工条件（包括泛金属加工液和未涂层硬质合金刀具）进行了比较。结果表明，在低温冷却条件下，采用多层涂层可显著提高刀具的使用寿命。在低温冷却条件下，该涂层与未涂层相比，刀具寿命提高了33%。统计分析表明刀具磨损与加工力之间有很强的相关性。这种分析也允许建立模型，预测工具磨损的功能测量力。

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引用次数: 0

Toward generalizable machine learning prediction of downskin surface roughness in laser powder bed fusion 激光粉末床熔合中下皮表面粗糙度的广义机器学习预测

IF 3.9 Q2 ENGINEERING, INDUSTRIAL

Advances in Industrial and Manufacturing Engineering

Pub Date : 2025-05-01 DOI: 10.1016/j.aime.2025.100163

Jigar Patel, Mihaela Vlasea, Sagar Patel

Downskin surface quality of laser powder bed fusion (L-PBF) remains a challenge due to the complex, multi-scale physics governing it. While numerical or experimental approaches alone can be significantly resource intensive, data-driven approaches such as machine learning (ML) have the potential to be more practical. However, the generalizability of ML models currently reported in literature is unclear; few ML models can predict reliably outside of their training domain. This study addresses these challenges by (i) demonstrating a downskin surface roughness classification model, trained on the largest reported dataset for downskin roughness (

\sim

400 downskin specimens spanning five builds and two ferrous alloys) and (ii) conducting a thorough investigation of the model’s generalizability. Additionally, this study highlights critical issues such as data imbalance, generalization to unseen data, and the importance of rigorous evaluation. By implementing robust ML practices, we focused on model performance across different training and evaluation domains. Our findings indicate satisfactory performance when using the more conservative balanced accuracy metric, achieving about 95% inter-domain and 83% intra-domain accuracy. Although there is still room for improvement, these results demonstrate a significant reduction in the risk of overfitting, thereby enhancing the classifier’s generalizability. This work underscores the importance of methodological rigor in machine learning applications, advocating for greater attention to data treatment and evaluation strategies. This approach may ultimately lead to more effective and usable ML models. The data-centric results indicated that (i) physics-informed features can improve performance during domain shifts, and (ii) increased the size and variety of datasets allows even computationally light models to achieve favorable performance.

由于控制激光粉末床熔合（L-PBF）的复杂、多尺度物理特性，下皮表面质量一直是一个挑战。虽然单独的数值或实验方法可能会占用大量资源，但数据驱动的方法（如机器学习（ML））有可能更加实用。然而，目前文献中报道的ML模型的泛化性尚不清楚；很少有机器学习模型可以可靠地预测其训练域之外的情况。本研究通过以下方式解决了这些挑战：(i)展示了一个下表层表面粗糙度分类模型，该模型在最大的下表层粗糙度报告数据集上进行了训练（约400个下表层样本，跨越五种建筑和两种黑色合金），（ii）对模型的可泛化性进行了彻底的调查。此外，本研究强调了关键问题，如数据不平衡、对未见数据的概化以及严格评估的重要性。通过实现健壮的机器学习实践，我们专注于不同训练和评估领域的模型性能。我们的研究结果表明，当使用更保守的平衡精度度量时，性能令人满意，域间精度约为95%，域内精度约为83%。尽管仍有改进的空间，但这些结果表明，过度拟合的风险显著降低，从而增强了分类器的可泛化性。这项工作强调了机器学习应用中方法严谨性的重要性，提倡更多地关注数据处理和评估策略。这种方法可能最终导致更有效和可用的ML模型。以数据为中心的结果表明，(i)物理信息特征可以在域转移期间提高性能，（ii）增加数据集的大小和种类，甚至可以使计算轻的模型获得良好的性能。

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引用次数: 0

Scaling laws for ring-shaped beam profiles in laser-based powder bed fusion of metals 激光粉末床金属熔合环形光束轮廓的标度规律

IF 3.9 Q2 ENGINEERING, INDUSTRIAL

Advances in Industrial and Manufacturing Engineering

Pub Date : 2025-05-01 DOI: 10.1016/j.aime.2025.100164

Jonas Grünewald, Moritz Wittemer, Katrin Wudy

The application of alternative beam shapes is a current research trend to stabilize and accelerate the laser-based powder bed fusion of metals process. Although many publications show a reduced process dynamic and an enlargement of the process window for dense components using non-Gaussian beam profiles, a generally valid correlation between the energy input - in terms of the beam shape and the process parameters - and the melting mode is lacking. Consequently, intensive experimental work is required to qualify process parameters for alternative beam profiles. The present work aims to reduce this experimental effort for the parameter qualification of alternative beam profiles by estimating the melting modes based on dimensionless parameters. For this purpose, a simple heat conduction model is applied to a new database of melt track widths and depths generated with various ring-shaped beam profiles with different spot sizes. The approach shows a correlation between the dimensionless enthalpy and the melt track depth and width if the 2^nd moment method is used to determine the spot size of the laser beam profiles. Finally, introducing a maximum dimensionless enthalpy considering the peak intensity of the beam profile used enables the estimation of the melting mode. Regardless of the beam profile, the transition from conduction mode to keyhole mode occurs between maximum dimensionless enthalpies of 6.25 ± 0.85 and 8.65 ± 0.30.

为了稳定和加速激光粉末床金属熔合过程，应用可选择的光束形状是当前的研究趋势。尽管许多出版物表明，使用非高斯光束剖面的致密组件的过程动态降低和过程窗口扩大，但缺乏能量输入（就光束形状和工艺参数而言）与熔化模式之间的普遍有效的相关性。因此，需要大量的实验工作来确定可选光束轮廓的工艺参数。本工作旨在通过基于无量纲参数估计熔化模式来减少对备选梁廓形参数确定的实验努力。为此，将一个简单的热传导模型应用于由不同光斑尺寸的环形光束轮廓生成的熔体轨迹宽度和深度的新数据库。该方法表明，用二阶矩法确定激光束轮廓的光斑尺寸时，无量纲焓与熔体轨迹深度和宽度之间存在相关性。最后，引入最大无因次焓，考虑到所使用的光束轮廓的峰值强度，使熔化模式的估计。无论光束形状如何，从传导模式到锁孔模式的转变发生在最大无因次焓为6.25±0.85和8.65±0.30之间。

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引用次数: 0

Integrating 3D printing, simulations and surrogate modelling: A comprehensive study on additive manufacturing focusing on a metal twin-cantilever benchmark 集成3D打印，仿真和代理建模：以金属双悬臂基准为重点的增材制造综合研究

IF 3.9 Q2 ENGINEERING, INDUSTRIAL

Advances in Industrial and Manufacturing Engineering

Pub Date : 2025-04-04 DOI: 10.1016/j.aime.2025.100162

C. Mallor , S. Lani , V. Zambrano , H. Ghasemi-Tabasi , S. Calvo , A. Burn

Additive Manufacturing by powder bed fusion of metals using a laser beam (PBF-LB/M) is constantly growing as an advanced technology to produce metal components. It offers greater design freedom compared to conventional processes and allows the production of complex, lighter geometries with numerous applications in a variety of industries. However, the time and cost required to achieve production readiness present significant challenges to the widespread adoption of new parts development. Success in builds is not reliable until tested, with common issues including distortion, and warpage. The expensive costs of physical iteration to optimize parameters calls for digital simulation to mitigate build failures. This paper presents the successful development of a surrogate model for predicting distortion in a PBF-LB/M metal part. The methodology is grounded on a design of experiments, additive manufacturing tests, finite element modelling playing a critical role, alongside reduced order methods to achieve a surrogate model for improving the additive manufacturing process. The reduced order method for creating the surrogate model is based on tensor decomposition and designed for easy integration into a digital twin, while preserving the underlying physics by retaining the effects of input variables on the final output. The validity of the proposed approach is demonstrated through a benchmark example involving the manufacturing of a metal twin-cantilever part using different laser power, scan speed, and preheating conditions. The twin-cantilever surrogate model developed embeds physics-based simulations and facilitates efficient estimation of deflections. It offers accurate results useful during process setting calibration and improves understanding of how the process parameters affect the final built part.

利用激光粉末床熔融金属的增材制造技术（PBF-LB/M）作为一种生产金属部件的先进技术正在不断发展。与传统工艺相比，它提供了更大的设计自由度，并允许生产复杂，更轻的几何形状，在各种行业中有许多应用。然而，实现生产准备所需的时间和成本对新零件开发的广泛采用提出了重大挑战。在测试之前，构建的成功是不可靠的，常见的问题包括扭曲和翘曲。优化参数的物理迭代的昂贵成本需要数字模拟来减轻构建失败。本文介绍了一个用于预测PBF-LB/M金属零件变形的代理模型的成功开发。该方法基于实验设计、增材制造测试、发挥关键作用的有限元建模，以及减少订单的方法，以实现替代模型，以改进增材制造过程。用于创建代理模型的降阶方法基于张量分解，旨在轻松集成到数字孪生中，同时通过保留输入变量对最终输出的影响来保留底层物理。通过不同激光功率、扫描速度和预热条件下的金属双悬臂零件的加工，验证了该方法的有效性。开发的双悬臂代理模型嵌入了基于物理的模拟，并促进了对挠度的有效估计。它提供了准确的结果，在过程设置校准有用，并提高了对工艺参数如何影响最终构建部分的理解。

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引用次数: 0

Manipulating martensitic transformation and residual stress development in stress superposed incremental forming of SS304 SS304应力叠加增量成形中马氏体相变和残余应力发展的调控

IF 3.9 Q2 ENGINEERING, INDUSTRIAL

Advances in Industrial and Manufacturing Engineering

Pub Date : 2025-03-18 DOI: 10.1016/j.aime.2025.100161

Elizabeth M. Mamros , Fabian Maaß , Thomas H. Gnäupel-Herold , A. Erman Tekkaya , Brad L. Kinsey , Jinjin Ha

Stress superposition is one of the strategies used in metal deformation processes to increase the material formability, decrease the required forming forces, and create highly customized components. To investigate the effects of tensile and compressive stresses superposed to the single point incremental forming (SPIF) process, experiments and numerical simulations were conducted for a stainless steel 304 (SS304) truncated square pyramid geometry. Tensile stresses were superposed in-plane on the specimen blank by a custom hydraulic frame, and compressive stresses were incorporated via a polyurethane die. Identified parameters for a martensitic transformation kinetics model for SS304 were used in a two-step finite element approach to predict the

α

’-martensite volume fraction. These results were compared to experimental results measured by a Feritscope at four locations along each pyramid wall and validated by electron backscatter diffraction. The residual stresses were measured using x-ray diffraction. The parts from each incremental forming process revealed differences in the residual stresses, which impacted the final geometries, and the

α

’-martensite volume fraction at the four measurement locations. The evolution of the stress state, defined by the stress triaxiality and Lode angle parameter, for each process contributed to the phase transformation variance. It was found that superposing both tensile and compressive stresses to SPIF resulted in the greatest phase transformation and lowest magnitude of residual stresses near the base and the greatest overall geometrical accuracy. Stress-superposed incremental forming can be implemented to manipulate final part properties, which is ideal for applications requiring highly customized parts, e.g., biomedical trauma fixation hardware.

应力叠加是金属变形过程中使用的策略之一，可以提高材料的成形性，降低所需的成形力，并创建高度定制的部件。为了研究单点增量成形（SPIF）过程中拉伸和压缩应力的影响，对304不锈钢（SS304）的截形方形金字塔几何形状进行了实验和数值模拟。拉伸应力由定制的液压框架在平面上叠加在试样空白上，压应力通过聚氨酯模具合并。利用SS304的马氏体相变动力学模型中确定的参数，采用两步有限元法预测α′-马氏体体积分数。这些结果与Feritscope在每个金字塔壁四个位置测量的实验结果进行了比较，并通过电子背散射衍射进行了验证。用x射线衍射测量了残余应力。不同增量成形工艺的零件在残余应力和α′-马氏体体积分数上存在差异，这影响了最终的几何形状。应力状态的演变（由应力三轴性和Lode角参数定义）对每个过程的相变变化有贡献。结果表明，在SPIF上叠加拉压应力时，其相变最大，基底附近残余应力最小，整体几何精度最高。应力叠加式增量成形可用于控制最终零件的性能，这对于需要高度定制零件的应用非常理想，例如生物医学创伤固定硬件。

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引用次数: 0