Journal of Manufacturing Processes最新文献

{"title":"Enhancement mechanism of wetting and spreading during mesh-assisted laser–metal inert gas hybrid welding–brazing of steel/aluminum","authors":"Jingzhen Kuang ,&nbsp;Zhongyu Wang ,&nbsp;Haiwei Xu ,&nbsp;Yuanxing Li ,&nbsp;Zongtao Zhu ,&nbsp;Hui Chen","doi":"10.1016/j.jmapro.2025.02.020","DOIUrl":"10.1016/j.jmapro.2025.02.020","url":null,"abstract":"<div><div>This paper proposes the insertion of a stainless-steel mesh interlayer to enhance the laser–metal inert gas (MIG) welding–brazing process of aluminum (Al) to steel. The mesh improves the spreading behavior and overall properties of the steel/Al overlap joints. The impacts of the mesh on the spreading dynamics of molten Al and on the microstructural characteristics and mechanical properties of the resultant joints are investigated. Under capillary forces, the mesh aids the spreading of molten aluminum on the steel surface. Moreover, the mesh dissolves into the molten pool, elevating the iron (Fe) content, intensifying the interfacial reactions, and leading to the formation of intermetallic compound (IMC) particles within the weld. The intensified interfacial reactions drive the wetting and spreading of the molten Al. The IMC particles function as additional nucleation sites, refining the grain structure of the weld. The mesh improves the average tensile shear strength of the joints from 308 to 368 N/mm (an improvement of 19.5 %) and shifts the fracture area from the interface or weld seam to the heat-affected zone. In summary, the mesh enhances the mechanical properties of the joints by increasing the spreading width, refining the weld grains, and forming IMC as a secondary phase for reinforcement.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"139 ","pages":"Pages 25-37"},"PeriodicalIF":6.1,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402952","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":"Formability of a new composite counter-roller spinning process with active and passive rotation of the rollers","authors":"Ning Yang ,&nbsp;Lijun Zhang ,&nbsp;Hong Chi ,&nbsp;Lukuan Li ,&nbsp;Yucai Li ,&nbsp;Kaiguang Luo ,&nbsp;Su Liu ,&nbsp;Shen Fan ,&nbsp;Jian Zhong","doi":"10.1016/j.jmapro.2025.02.016","DOIUrl":"10.1016/j.jmapro.2025.02.016","url":null,"abstract":"<div><div>To address the issue of low forming precision in the traditional counter-roller spinning (CRS) process, caused by frictional torque during the initial spinning stage, a new composite counter-roller spinning process with active and passive rotation of the rollers (A&amp;P-CRS) is proposed. This method effectively alternates between active and passive roller rotations by segmenting different spinning stages, thereby achieving the dual benefits of torque reduction and enhanced stability, as well as improved quality and preserved performance. The optimal active rotation speed of the rollers in the initial spinning stage is determined, which in turn enables the identification of the points of transition between active and passive rotation to the stable spinning stage. As a result, peak torque is reduced by up to 35.90 %. Furthermore, a precise crystal plasticity finite element model (CPFEM) is developed using the sub-model technique and an enhanced hardening model, enabling accurate predictions of mesoscale forming characteristics at various locations, thus providing a viable alternative to extensive material characterization tests. An A&amp;P-CRS CNC machine is designed and experimentally evaluated. The results indicate that, under the new process, the average outer diameter deviation Δ<em>D</em>_R and average roundness <em>O</em> of the spun parts are improved by at least 22.35 % and 10.72 %, respectively, compared to CRS or full active counter-roller spinning (FACRS) processes. Additionally, the material undergoes a transformation from a diffuse {001}&lt;110&gt; texture to a {001}&lt;100&gt; \"soft\" texture with significantly higher polar density, resulting in the formation of the <em>η</em>-fiber structure. This texture formation is further elucidated through the coordinated action of all slip systems, based on the proposed average activity parameter <em>A</em>_{slip plane} for the slip planes. These findings deepen the understanding of both the macro and mesoscale formability of the CRS process, offering a novel approach to meet the growing demands for higher precision and integrated shape and performance manufacturing of thin-walled cylinders.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"138 ","pages":"Pages 169-185"},"PeriodicalIF":6.1,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403059","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":"Incorporation of acrylated cellulose nanocrystals into photocurable resin for high-fidelity printing of transparent 3D structures","authors":"Junsik Choi ,&nbsp;Deepika Thakur ,&nbsp;Jinhong Min ,&nbsp;Jiho Lee ,&nbsp;Hoon Kim ,&nbsp;Jinho Hyun","doi":"10.1016/j.jmapro.2025.02.023","DOIUrl":"10.1016/j.jmapro.2025.02.023","url":null,"abstract":"<div><div>The incorporation of cellulose nanocrystals (CNCs) into trimethylolpropane formal acrylate (CTFA) ink for digital light processing (DLP) 3D printing has been found to increase light scattering, which subsequently reduces the mechanical properties of printed structures. In this study, acrylated cellulose nanocrystals (A-CNCs) were synthesized by treating sulfonated CNCs with methacrylic acid and were successfully integrated into a UV-curable resin for DLP 3D printing. The effect of ultrasonication on A-CNC dispersion within the resin was assessed by measuring the change in the transmittance of suspensions. The composite resin ink containing A-CNCs retained transparency, and the resulting printed structures demonstrated significant mechanical reinforcement even at low A-CNC concentrations. This improvement is attributed to the high colloidal stability of A-CNCs within the ink. Furthermore, the suitability of the resin for 3D printing was confirmed through the examination of the morphologies of the printed structures. Moreover, the structures printed using A-CNC/CTFA exhibited shape memory behavior in response to thermal stimuli, affirming the potential of the composite resin in bioengineering applications.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"139 ","pages":"Pages 1-11"},"PeriodicalIF":6.1,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation on mechanical property and fracture behavior of galvanized steel-CFRTP joints fabricated via induction heating","authors":"Weiyan Chen ,&nbsp;Fuminobu Kimura ,&nbsp;Shuohan Wang ,&nbsp;Yusuke Kajihara","doi":"10.1016/j.jmapro.2025.02.010","DOIUrl":"10.1016/j.jmapro.2025.02.010","url":null,"abstract":"<div><div>As multi-material design becomes mainstream in automobile industry, the technology for joining different materials is becoming increasingly critical. This study proposes a strategy for directly joining carbon fiber thermoplastic (CFRTP) and galvanized steel (GS) using electromagnetic induction heating. A simple hot water treatment (HWT) method was utilized to produce nanostructures on the GS surface to enhance the joining strength. The effect of HWT time on the surface wettability and joining quality was investigated. The influences of induction heating conditions on the joining quality were also evaluated by joining interface temperature measurement and tensile shear test. The contact angles on GS surface were lower than 10° when HWT duration exceeded 20 min, demonstrating the superhydrophilicity. The optimized joining strength reached 39.8 MPa with the optimum joining interface temperature around 300 °C. The fracture mechanism was investigated through SEM observation of the facture surfaces and cross sections. Insufficient interface temperature can lead to inadequate fluidity of the molten CFRTP matrix, whereas excessively high temperature can precipitate the deterioration of both the matrix and the galvanic coating. Under optimized condition, the failure mechanism was identified as the occurrence and propagation of cracks within the CFRTP, attributed to the strong anchoring effect formed at the joining interface. The excellent mechanical properties of carbon fibers partially inhibited the propagation of cracks and contributed greatly to the high joining strength. In addition, a thermal cycle test was conducted to evaluate the reliability and durability of the joints. The result demonstrated the capacity of the joints to withstand environmental temperature change, with strength reduction within 5 % after 50 cycles.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"138 ","pages":"Pages 129-139"},"PeriodicalIF":6.1,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395284","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":"In-process monitoring strategies and methods in metal forming: A selective review","authors":"Xu He,&nbsp;Torgeir Welo,&nbsp;Jun Ma","doi":"10.1016/j.jmapro.2025.02.011","DOIUrl":"10.1016/j.jmapro.2025.02.011","url":null,"abstract":"<div><div>Metal forming is an important method for manufacturing of lightweight components that offer enhanced functionality, energy efficiency and sustainability. The digital transformation in manufacturing, characterized by Industry 4.0, has heightened the need for stringent standards regarding dimensional accuracy, product quality and productivity. This has placed increased focus on flexible and adaptive control strategies, alongside the integration of smart production lines. Consequently, there is an increasing demand for advanced in-process monitoring technologies to meet these evolving needs. This paper reviews in-process measurement methods used in forming processes for metal components. It examines aspects such as force, geometry, temperature and acoustic characteristics through a recent review of current literature. We emphasize the integration of these measurement techniques into metal forming operations with a primary focus on their role in optimizing manufacturing processes for meeting high product-quality standards. The study also highlights recent sensor technologies deployed in selected metal forming processes, including rolling, bending, stamping, and deep drawing to address the evolution of sensor technology in these applications. Key findings include the widespread adoption of optical sensors for high-precision geometric measurements, the use of thermocouples and FBG sensors for temperature monitoring, as well as the integration of acoustic emission sensors for, among other, real-time detection of defects. Despite considerable technology advancements, several challenges still prevail. This applies particularly to integration complexity, accuracy requirements and environmental conditions, emphasizing the continued need for ongoing research and further development efforts in the field. Future work should thus focus on improving sensor integration, measurement accuracy and developing robust solutions for various environmental manufacturing conditions to support implementation of Industry 4.0 strategies to meet digital manufacturing goals.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"138 ","pages":"Pages 100-128"},"PeriodicalIF":6.1,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Weld TOFD defect classification method based on multi-scale CNN and cascaded focused attention","authors":"Donglin Tang ,&nbsp;Junhui Zhang ,&nbsp;Pingjie Wang ,&nbsp;Yuanyuan He","doi":"10.1016/j.jmapro.2025.02.019","DOIUrl":"10.1016/j.jmapro.2025.02.019","url":null,"abstract":"<div><div>Aiming at the problems of high noise and interference fringes of weld defect images in TOFD detection technology, and the challenges of feature information loss and computational efficiency imbalance faced by current deep learning models in processing such images. We innovatively propose a defect identification model of hybrid CNN and Transformer architecture named MCFNet (Multi Cascaded Focused Network). The multi-scale feature fusion (MSFF) module is introduced to enhance the ability of local information extraction. At the same time, an efficient and fast transformer module (EFTM) has been designed. In this module, a cascaded group attention (CGA) mechanism is employed to segment feature graphs, and focused linear attention is utilized instead of the traditional multi-head self-attention (MHSA). This design aims to reduce computational complexity and enhance the diversity of attention mechanisms. In order to verify the performance of the model, we constructed a TOFD defect dataset STTOFD-DEF and conducted extensive experiments. The experimental results show that MCFNet achieves a high accuracy of 98.72 % on defect identification, while maintaining a Params of 10.21 M, Flops of 0.423G and inference time of 55.60 ms, and surpasses the existing classical networks in many key indicators. In visualization and identification performance verification, MCFNet demonstrated the highest accuracy in identifying the most dangerous welding defects, such as Lack of fusion and Crack, demonstrating its reliability and effectiveness in practical engineering applications.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"138 ","pages":"Pages 157-168"},"PeriodicalIF":6.1,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395955","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":"Prediction of 3D temperature field through single 2D temperature data based on transfer learning-based PINN model in laser-based directed energy deposition","authors":"Shitong Peng ,&nbsp;Shoulan Yang ,&nbsp;Baoyun Gao ,&nbsp;Weiwei Liu ,&nbsp;Fengtao Wang ,&nbsp;Zijue Tang","doi":"10.1016/j.jmapro.2025.02.015","DOIUrl":"10.1016/j.jmapro.2025.02.015","url":null,"abstract":"<div><div>Temperature field is critical in laser additive manufacturing and significantly influences component deformation, microstructure, and mechanical properties. Accurate monitoring and control of temperature evolution are essential for achieving optimal fabrication quality. However, current monitoring technologies struggle to capture the 3D temperature field comprehensively, necessitating reliance on numerical simulations that are cost-prohibitive and time-inefficient. In this regard, we integrate physics-informed neural networks (PINNs) with transfer learning, leveraging these promising techniques to solve computational physics problems and data scarcity issues, respectively. We proposed a transfer learning-based PINN framework for efficiently and accurately predicting the 3D temperature field during the blue laser deposition of aluminum‑magnesium alloy powder. The PINN architecture incorporates a lightweight attention block, ResNet block, and fully connected layers, with a customized loss function that includes residual terms of physical rules, particularly the often-overlooked thermal convection process. The PINN is pre-trained using numerical simulation data on additive processes and fine-tuned using a 5-dimensional tensor dataset derived from infrared images of the single-track single layer blue laser deposition experiment. The blue laser deposition experiment demonstrated the effectiveness and superiority of the proposed method. Results indicated that the average temperature prediction error is &lt;1.3 %, and the training time on the target task is reduced to one-third of the pre-training time. Our model also showed higher prediction accuracy than other PINN derivatives. This framework is highly adaptable and can be extended to other metal AM processes under the proposed architecture, enhancing the real-time temperature field prediction for metal additive manufacturing.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"138 ","pages":"Pages 140-156"},"PeriodicalIF":6.1,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395285","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":"Rapid forming of high-entropy alloy under extreme low temperature via ultrasonic vibration","authors":"Yu Zhang ,&nbsp;Pengyu Huang ,&nbsp;Luyao Li ,&nbsp;Xin Li ,&nbsp;Wenxin Wen ,&nbsp;Sajad Sohrabi ,&nbsp;Jinbiao Huang ,&nbsp;Wenhao Lu ,&nbsp;Yong Xiao ,&nbsp;Dan Li ,&nbsp;Jiang Ma","doi":"10.1016/j.jmapro.2025.01.097","DOIUrl":"10.1016/j.jmapro.2025.01.097","url":null,"abstract":"<div><div>Low-temperature forming technology has a wide range of applications, particularly in aerospace and polar exploration. However, its application often confined by the low-temperature brittleness of metallic materials. This study proposes a simple and efficient route to form high-entropy alloys at a low temperature (77 K) using ultrasonic vibration, termed ultrasonic-assisted plastic forming. Our findings demonstrate that this ultra-fast processing technology can achieves a macroscopic high strain rate of 1.25 × 10⁻¹ s⁻¹ with significantly lower stress compared to conventional compression methods. The reduction in stress is attributed to the deformation twin and large angle grain rotation induced by ultrasonic vibration, which activate additional slip systems and facilitates deformation. The Vickers hardness in the processed surface increases by 39.1 % compared to the as-cast sample, suggesting the method enables simultaneous surface modification and forming. Furthermore, fine multi-scale structures and with small parts of special shapes are fabricated successfully using the proposed method. The detailed structure characterization of the formed sample and the proposed forming mechanism provide valuable insight into deformation under dynamic loading. Owing to its high efficiency and lightweight equipment requirements resulting from low forming stress, ultrasonic-assisted plastic forming holds potential for engineering applications in forming metal alloys, even in extreme environments.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"139 ","pages":"Pages 12-24"},"PeriodicalIF":6.1,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402951","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":"Monitoring of Argon plasma in a coating manufacturing process by utilising IR imaging techniques","authors":"David Miller ,&nbsp;V. Viswanathan ,&nbsp;Divya Tiwari ,&nbsp;Windo Hutabarat ,&nbsp;Saurav Goel ,&nbsp;Beth Muthoni Irungu ,&nbsp;Allan Matthews ,&nbsp;Ashutosh Tiwari","doi":"10.1016/j.jmapro.2025.01.093","DOIUrl":"10.1016/j.jmapro.2025.01.093","url":null,"abstract":"<div><div>Atmospheric plasma spray is a complex multivariable manufacturing process used in a wide range of industries. Deviations in the process parameters have been shown to affect the coating quality. Currently, the quality analysis is performed at the end of the process rather than checking for defects during the process. However, monitoring for these deviations during a coating process is difficult due to environmental hazards such as UV radiation, dusty environment, and excessive noise generation. A commercially available thermal imaging camera was integrated into this space to directly monitor the atmospheric plasma heat distribution and its influence on the in-flight particle trajectories during spraying. A novel metric called asymmetric angle is proposed to monitor the asymmetry of the plasma heat distribution. This is an important metric as a symmetric heat distribution is required to heat all the particles adequately to form a good quality coating. Further metrics of Gaussian Aspect Ratio (GAR) and contour area were found to have a relationship with the plasma gas flow rate and are discussed. The spray angle of the material is also tracked by fitting a 1D line to the regional Shannon entropy of the thermal image. The limitations of these metrics are discussed with possible avenues of further investigation.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"138 ","pages":"Pages 79-89"},"PeriodicalIF":6.1,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A real-time optimization method for thermo-chemical coupled curing process of composites with LSTM network","authors":"Wenyuan Tang ,&nbsp;Liang He ,&nbsp;Xinyu Hui ,&nbsp;Yingjie Xu ,&nbsp;Rutong Yang ,&nbsp;Yutong Liu ,&nbsp;Weihong Zhang","doi":"10.1016/j.jmapro.2025.01.072","DOIUrl":"10.1016/j.jmapro.2025.01.072","url":null,"abstract":"<div><div>In this present work, a novel real-time optimization method is introduced for autoclave curing of carbon fiber reinforced polymer (CFRP) composites, which employs LSTM network to actively control the defects, i.e. temperature overshoot and uneven cure induced by curing process. Firstly, a finite element (FE) based thermo-chemical coupled model is developed to evaluate the temperature and DoC evolutions, and experimentally validated by a large-size T-stiffened composite panel. Then, the information of curing profiles and the corresponding temperature and DoC differences extracted from FE simulations are used for Long Short-Term Memory (LSTM) network training. Finally, a real-time control framework is proposed by integrating the LSTM network with Q-learning algorithm to minimize the temperature and DoC differences during the curing process by adjusting the curing profile. The optimized curing profile shows a significant improvement compared to the original two dwell profile, with the temperature difference and DoC difference in the thickness and length directions both reduced. This design of curing profile can provide more insights into the composite intelligent manufacturing.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"138 ","pages":"Pages 90-99"},"PeriodicalIF":6.1,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387803","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}