Journal of Manufacturing Processes最新文献

{"title":"Sequential pool-based batch-mode active learning based on weighted uncertainty difference sampling for automated warping detection in additive manufacturing","authors":"Jungyoon Moon ,&nbsp;Kijung Park ,&nbsp;Sang-in Park","doi":"10.1016/j.jmapro.2025.09.016","DOIUrl":"10.1016/j.jmapro.2025.09.016","url":null,"abstract":"<div><div>Warping deformation is a common defect in parts fabricated through material extrusion for polymers. Despite the need for automated warping detection, developing an object detection model remains challenging due to the limited number of experimental samples, the similarity of time-series warping images, and the labor-intensive nature of image labeling. To facilitate efficient warping detection modeling, this study proposes a sequential pool-based batch-mode active learning framework that iteratively updates the warping detection model after each fabrication step to collect a sequential data pool. The proposed framework enhances modeling effectiveness through a novel data query method called weighted uncertainty difference sampling (WUDS). WUDS selects a batch dataset for new training data instances by considering both the current detection uncertainty and its difference in time-series images. To validate the proposed active learning framework based on WUDS, warping deformation images were collected from recorded video data during the material extrusion of five specimens using a metal–polymer composite filament. A warping detection model based on the You Only Look Once (YOLO) object detection algorithm was then trained using the proposed active learning framework with WUDS, along with three common data query methods for comparison. In addition, the effect of batch size on the performance of the proposed active learning framework with WUDS was analyzed to investigate modeling efficiency. The results demonstrate that the proposed active learning framework with WUDS achieved higher detection performance and lower performance variability than with other data query methods. Furthermore, the proposed active learning framework generated a competent warping detection model despite limited experiments for data collection and a partial set of the data pool. These findings suggest that the proposed active learning approach can contribute to rapid modeling with robust machine learning performance for manufacturing processes.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"153 ","pages":"Pages 933-947"},"PeriodicalIF":6.8,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A computational framework for optimising Extrusion Blow Moulding: Enhancing material efficiency and reducing waste for industry 4.0","authors":"Wagner de Campos Galuppo ,&nbsp;Pedro Santana ,&nbsp;Francisco Alves ,&nbsp;João Miguel Nóbrega","doi":"10.1016/j.jmapro.2025.09.038","DOIUrl":"10.1016/j.jmapro.2025.09.038","url":null,"abstract":"<div><div>This study presents a computational framework specifically designed to optimise parts produced through the Extrusion Blow Moulding (EBM) processes. By focusing on the crucial phases of the EBM process, namely mould clamping and parison inflation, the framework aims to assist manufacturers in precise material usage control, thereby reducing waste and optimising resources to produce the final parts. The simulation of those phases relies on advanced numerical simulations based on finite strain theory and membrane formulation. The optimisation is carried out iteratively and automatically. This optimisation process involves refining the thickness distributions and modifying initial controlling variables to achieve the desired final result that meets the desired specifications. The framework is evaluated through a series of detailed case studies, which include idealised models of cylindrical-like shape bottles and a practical application involving real-world industrial product with a more complex shape format. The latter study comprises an extensive experimental validation. The obtained results demonstrate the developed framework’s effectiveness in optimising material distribution, resulting in significant reductions in material waste and improvements in the quality of the final product. Moreover, the proposed framework proves to be a valuable tool for integrating EBM processes into Industry 4.0, offering an extensible and efficient solution for manufacturers aiming to enhance EBM production capabilities, while minimising environmental impact.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"154 ","pages":"Pages 249-269"},"PeriodicalIF":6.8,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal-transport-based geometry modeling for material extrusion additive manufacturing","authors":"Siqi Chen ,&nbsp;Shuai Liu ,&nbsp;Shuaiyin He ,&nbsp;Molong Duan","doi":"10.1016/j.jmapro.2025.09.042","DOIUrl":"10.1016/j.jmapro.2025.09.042","url":null,"abstract":"<div><div>Material extrusion additive manufacturing is increasingly adopted in the automotive, aerospace, and medical industries for its capability to create complex features at low cost. Despite high flexibility, parts fabricated with the material extrusion method continue to suffer from geometric inaccuracies and dimensional instability, particularly when manufacturing structures that require high geometric fidelity, such as those with intricate internal channels. To enhance the precision and stability of the material extrusion process, geometry modeling methods based on manufacturing parameters have been introduced. Researchers have employed physical models and neural networks to predict the geometry of printed parts. However, physical modeling is often characterized by high complexity and significant computational demands, while neural networks require a substantial amount of measurement data, resulting in a high cost in experiments. The high computation load and measurement data demand of existing geometry prediction methods prevent their widespread adoption in industrial settings, as they lead to prohibitively long simulation times and the inability to support real-time process optimization. To close the research gap, we propose an optimal-transport-based geometry modeling (OTB-GM) method for the material extrusion system. The proposed OTB-GM models the ironing effects of the moving nozzle for generating the final extruded profile, by minimizing the energy consumption of the transportation process. The OTB-GM begins by initializing the profile prior to ironing, resembling the shape of a Gaussian distribution. In constructing the model, we take into account the material's viscous resistance, changes in gravitational potential energy, and modifications to the surface geometry during ironing. We derive the formula of OTB-GM in two dimensions (2D) and three dimensions (3D) for modeling steady (like line) and dynamic (like corner) extrusion conditions, respectively. To validate the modeling accuracy of the proposed OTB-GM method, the straight line and corner parts are printed for 2D and 3D verification, respectively. Compared with the conventional ellipse geometry modeling method, the proposed OTB-GM reaches higher accuracy in both 2D and 3D validation cases.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"154 ","pages":"Pages 236-248"},"PeriodicalIF":6.8,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From simulation to metamodel to experiment: Evaluating the prediction accuracy of polynomial regression models for clinch joint properties","authors":"Jonathan-Markus Einwag ,&nbsp;Christian Steinfelder ,&nbsp;Sandro Wartzack ,&nbsp;Alexander Brosius ,&nbsp;Stefan Goetz","doi":"10.1016/j.jmapro.2025.09.059","DOIUrl":"10.1016/j.jmapro.2025.09.059","url":null,"abstract":"<div><div>In modern lightweight design, mechanical joining methods such as clinching are increasingly used due to their efficiency and suitability for joining dissimilar materials. However, variations in process parameters and material properties can lead to significant deviations in the resulting joint geometry. This study investigates the ability of global polynomial regression models to predict such deviations in clinch joint properties, based on finite element (FE) simulation data and evaluates them through variation simulations and experimental testing. A comprehensive dataset was generated using a validated simulation model to train polynomial regression models. These models were then applied to six distinct clinching process configurations. The metamodels show excellent agreement with the variation simulations, achieving coefficients of prognosis (CoP) above 0.95. Experimental validation using z-scores and Empirical Coverage Probability (ECP) indicates high predictive accuracy for bottom thickness (BT), partially accurate results for neck thickness (NE), and a systematic underestimation of interlock (IL). The predicted 95.5 % confidence intervals are overly conservative for bottom thickness, while for neck thickness and interlock, the intervals are often misaligned with the actual measurements, reflecting biased predictions. The results underline both the potential and the limitations of polynomial regression models for predicting variations in clinch joint properties. While the approach shows promise for designing reliable clinch joints, the study highlights challenges in transferring simulation-trained metamodels to experimental conditions due to uncertainties in the metamodels, the numerical simulations and the experiments.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"154 ","pages":"Pages 179-191"},"PeriodicalIF":6.8,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Curved layering and path planning of continuous fiber composites based on multi-direction slicing for robotic additive manufacturing","authors":"Yaxing Song ,&nbsp;Congze Fan ,&nbsp;Zhongde Shan ,&nbsp;Yiwei Chen ,&nbsp;Wenzhe Song ,&nbsp;Jiaxun Xu ,&nbsp;Weiyi Kong ,&nbsp;Wei Zhang ,&nbsp;Jing-Hua Zheng","doi":"10.1016/j.jmapro.2025.09.072","DOIUrl":"10.1016/j.jmapro.2025.09.072","url":null,"abstract":"<div><div>Curved path planning methods based on the surface structural characteristics of target models are key technologies for reducing support structure dependence, improving surface quality, and optimizing structural performance in additive manufacturing. The combined forming method of planar/curved surface paths is an important solution to balance the increased manufacturing time cost due to frequent adjustments of multi-degree-of-freedom printing postures. The present study proposed a curved layering and path planning strategy based on the discrete intersection points of multi-directional slices, achieving the unification of planar slicing and curved slicing in the processing logic of the model. Building on traditional planar contour offset methods, it introduced multiple vertical slices, achieving the dimensional transformation of discrete point information from 2D to 3D. Meanwhile, it utilized the normal information of the model's surface to optimize the spatial positions of the discrete points within each horizontal slice, enhancing the consistency of the layer thickness of the generated curved paths. This strategy was applied to path analysis and accuracy discussions on target models like helmet, and experimental validation was conducted using a continuous fiber multi-axis printing platform based on a six-axis robotic arm. The results showed that the curved slicing paths generated exhibited superior theoretical accuracy of surface contours, effectively suppressing the staircase effect. The surface contour accuracy in the fiber orientation direction reached 99.29 %. Furthermore, considering the structural deformation constraints of continuous fiber filaments during printing, the recommended layer thickness range was 0.20 to 0.24 mm for 0.4 mm size filaments.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"154 ","pages":"Pages 222-235"},"PeriodicalIF":6.8,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The study of an image feedback-assisted jet electrochemical additive manufacturing process","authors":"Wenlin Xiang ,&nbsp;Boru Chen ,&nbsp;Baohua Liu ,&nbsp;Chunren Lin ,&nbsp;Yabin Yang","doi":"10.1016/j.jmapro.2025.09.071","DOIUrl":"10.1016/j.jmapro.2025.09.071","url":null,"abstract":"<div><div>Jet electrochemical deposition (Jet ECD) has attracted increasing attention for its high deposition rate. However, the electrochemical deposition rate exhibits pronounced nonlinear characteristics over time, making it difficult to precisely control the growth of 3D structures. In the present study, an image-based monitoring and feedback mechanism is proposed and validated. This method utilizes a high-magnification camera to capture real-time images of the deposition zone. Through an image recognition algorithm, it identifies the contact state between the printed copper column and the liquid column. It then dynamically generates displacement control commands and enables precise regulation of deposition time and position. Moreover, it facilitates analysis of the nonlinear deposition rate during deposition. Experimental results demonstrate that this method effectively accommodates the nonlinear behavior inherent in the deposition process. It enables the successful fabrication of overhanging structures with angles ranging from 0° to 80°, exhibiting favorable morphology and high density. Additionally, the fabrication of helical multi-segment structures and trifurcated branch structures validates the method's applicability and scalability for manufacturing complex multi-directional 3D structures. This study provides a novel strategy for realizing closed-loop control in electrochemical additive manufacturing (ECAM) and lays a technical foundation for constructing high-precision, complex 3D structures.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"154 ","pages":"Pages 165-178"},"PeriodicalIF":6.8,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new cumulated temporal causal-effects based model for predicting the aging deformation of metal structural parts","authors":"Yang Ni ,&nbsp;Changqing Liu ,&nbsp;Yifan Zhang ,&nbsp;Yingguang Li","doi":"10.1016/j.jmapro.2025.09.054","DOIUrl":"10.1016/j.jmapro.2025.09.054","url":null,"abstract":"<div><div>The aging deformation of metal structural parts has emerged as a key factor affecting the dimensional accuracy, and the prediction ability of aging deformation is fundamental for its control. Causal deep learning methods have prominent advantages by introducing inductive biases for making the prediction using other observable variables than residual stress. However, the natural aging process of metal parts involves creep and stress relaxation, where the aging deformation is resulted by the cumulated temporal effects of time-varying residual stress from previous time stages. Existing causal deep learning methods are carried out only based on instant causal-effects of cause variables at a certain time stage, which ignores the cumulation of temporal causal-effects and restricts the prediction accuracy. To this end, this paper proposes a new cumulated temporal causal-effects based model. The cumulated causal-effects are defined as the convolution of time-varying causal variables and their mechanisms, and a modified dynamic convolutional neural network is applied in the model to learn the cumulated temporal causal-effects of residual stress and make aging deformation prediction. The machining of die forged structural parts is taken as a case study, and a Digital Image Correlation system is employed for aging deformation measurement. Experimental results show that the proposed model could beat all comparison models and predict aging deformation accurately and stably.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"154 ","pages":"Pages 208-221"},"PeriodicalIF":6.8,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and performance evaluation of a non-resonant ultrasonic vibration-assisted grinding device for ultra-high-strength gears","authors":"Junshuai Zhao ,&nbsp;Dan Wen ,&nbsp;Yanjun Zhao ,&nbsp;Jianhui Zhu ,&nbsp;Wenfeng Ding ,&nbsp;Biao Zhao","doi":"10.1016/j.jmapro.2025.09.090","DOIUrl":"10.1016/j.jmapro.2025.09.090","url":null,"abstract":"<div><div>To address the challenges posed by the high hardness and poor machinability of ultra-high-strength gears used in aerospace transmissions, this study innovatively proposes and validates an ultrasonic vibration-assisted grinding (UVAG) method. First, based on non-resonant design theory and the Rayleigh-Ritz method, a theoretical model of the gear-specific ultrasonic vibration unit was developed to determine the key structural parameters. Subsequently, finite element analysis (FEA) was used to perform modal analysis and structural optimization of the vibration unit, leading to the successful development of a UVAG device tailored for gear grinding. Finally, machining experiments confirmed the feasibility and significant advantages of this technology. The results show that, through theoretical design and finite element optimization, the actual resonant frequency of the developed ultrasonic vibration unit deviated less than 4.5 % from the designed value, and a uniform longitudinal ultrasonic amplitude of 6 μm was achieved circumferentially on the ultra-high-strength gear. Compared with conventional grinding (CG), the UVAG demonstrated significant advantages: the normal and tangential grinding forces were reduced by 34.9 % and 31.7 %, respectively. And the grinding temperature was reduced by 37.4 %. In addition, the surface roughness of the gear tip, flank, and root were significantly improved by 24.2 %, 19.1 %, and 19.6 %, respectively, resulting in enhanced surface quality of the ultra-high-strength gears. Moreover, this method effectively reduced clogging of the grinding wheel pores and adhesion of workpiece material on abrasive grains. This study integrates ultrasonic vibration into the ultra-high-strength gears grinding process, offering a practical and valuable technological solution for the efficient and high-quality machining of ultra-high-strength aerospace transmission gears.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"154 ","pages":"Pages 192-207"},"PeriodicalIF":6.8,"publicationDate":"2025-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A force-induced deformation prediction method without iteration considering the instantaneous undeformed chip thickness update for thin-walled part in flank milling","authors":"Shuyi Ge ,&nbsp;Jiale Zeng ,&nbsp;Kang Wang ,&nbsp;Liping Wang","doi":"10.1016/j.jmapro.2025.09.061","DOIUrl":"10.1016/j.jmapro.2025.09.061","url":null,"abstract":"<div><div>The thin-walled part is extensively applied to the plentiful industries including automotive and aerospace, which inevitably suffer the force-induced deformation during milling due to their low stiffness characteristics. This leads to a reduction in machining accuracy and even results in component damage. To address the issue, a deformation prediction model without iteration considering the IUCT (Instantaneous Undeformed Chip Thickness) update is proposed.</div><div>First, based on the stiffness equation, the node division method is applied to tool-workpiece deformation model, in which solution scale is reduced to improve the model efficiency. Then, to establish an iterative model for the actual deformation, the coupling effect among the milling force, radial cutting depth, IUCT and deformation need to be considered into the prediction model. Next, a non-iterative deformation prediction method is proposed, in which the milling force model is reconstructed to obtain the generalized deformation formula of the closed-form solution. Moreover, the impact of the IUCT update on both milling force and deformation is analyzed. Finally, the correctness of the proposed method is verified through flank milling experiments, which shows the average accuracy of deformation can reach 97.5 %. The accuracy and efficiency of the proposed method are verified in different scenarios by comparison with other methods.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"154 ","pages":"Pages 134-149"},"PeriodicalIF":6.8,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Laser directed energy deposition additive manufacturing using friction stir channelling extruded wire","authors":"Yajie Chu ,&nbsp;Xingjian Zhao ,&nbsp;Wanting Sun ,&nbsp;Sam Holdsworth ,&nbsp;Dikai Guan ,&nbsp;Yuze Huang","doi":"10.1016/j.jmapro.2025.09.060","DOIUrl":"10.1016/j.jmapro.2025.09.060","url":null,"abstract":"<div><div>This paper investigates a new ‘forged’ wire additive manufacturing processing, in which the metal wire is produced as a by-product from stationary shoulder friction stir channelling (SS-FSC) under the severe plastic deformation mechanism (known as CoreFlow®), and then used as the feedstock in directed energy deposition with a laser beam and wire feedstock (DED-LB/w) additive manufacturing. For the first time, the ‘by-products’ produced in the SS-FSC process, which are ‘forged’ 6082 aluminium alloy wire, were tested with built-tracks using DED-LB/w. Process mapping was built to demarcate the melting states, including the stable, dripping, and incomplete melting regimes, over a wide range of laser energy densities (92 to 303 <span><math><mi>kJ</mi><mo>·</mo><mi>s</mi><mo>·</mo><msup><mi>g</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup><mo>·</mo><msup><mi>cm</mi><mrow><mo>−</mo><mn>2</mn></mrow></msup></math></span>). Metallurgy tests were also conducted to reveal the evolution of the microstructure and defect formation of the deposited tracks. It was found that: (i) Stable deposition with a grain size of <span><math><mn>9</mn><mo>−</mo><mn>20</mn><mspace></mspace><mi>μm</mi></math></span> can be achieved with optimised processing parameters, i.e., energy density <span><math><mn>243</mn><mspace></mspace><mi>kJ</mi><mo>·</mo><mi>s</mi><mo>·</mo><msup><mi>g</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup><mo>·</mo><msup><mi>cm</mi><mrow><mo>−</mo><mn>2</mn></mrow></msup></math></span> with a laser power <span><math><mn>3.8</mn><mspace></mspace><mi>kW</mi></math></span>, a scanning speed <span><math><mn>0.8</mn><mspace></mspace><mi>cm</mi><mo>·</mo><msup><mi>s</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup></math></span> and a wire feed rate <span><math><mn>2.0</mn><mspace></mspace><mi>cm</mi><mo>·</mo><msup><mi>s</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup></math></span>; (ii) The substructure morphology is gradually transitioned from columnar at the track bottom to cellular (<span><math><mn>8.9</mn><mo>±</mo><mn>1.8</mn><mspace></mspace><mi>μm</mi></math></span>) at the top, driven by an increased cooling rate; and (iii) The built track porosity is mainly composed of gas pores that are small (equivalent diameter of <span><math><mn>20</mn><mo>−</mo><mn>50</mn><mspace></mspace><mi>μm</mi></math></span>) and spherical, primarily resulting from the ambient gas, the SS-FSC extruded wire oxides and contaminations. The study supports resource-efficient, low-carbon manufacturing via reuse of by-products, in alignment with the Net Zero Strategy.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"154 ","pages":"Pages 122-133"},"PeriodicalIF":6.8,"publicationDate":"2025-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145223313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}