Journal of Manufacturing Processes最新文献

{"title":"Assessment of tool kinematics, mass scaling effects, and similarity theory in metal spinning simulation","authors":"Akla-Essoh Claude Korolakina ,&nbsp;Pierre-Olivier Bouchard ,&nbsp;Katia Mocellin ,&nbsp;Sjoerd Van der Veen ,&nbsp;Anne Lepied","doi":"10.1016/j.jmapro.2025.06.069","DOIUrl":"10.1016/j.jmapro.2025.06.069","url":null,"abstract":"<div><div>Spinning processes are incremental sheet forming (ISF) operations that require computationally expensive numerical simulations due to the large number of increments required and complex tool-workpiece contact interactions. Similarity theory has demonstrated its applicability to spinning process modeling and, when combined with mass scaling, shows potential for increasing computational efficiency. This potential is investigated in this work through a metal spinning setup. A model of the process is developed using two process kinematics approaches: the classical one as used in experiments, and a modified version where the roller follows an enforced helical path while the mandrel remains fully constrained. Comparison of global and local outputs demonstrates very similar predictions for both kinematics. Analysis of mass scaled models using the modified kinematics reveals that higher scaling factors lead to interference from inertia effects and deteriorated contact treatment due to increased time increments. The choice of mass scaling factor depends on the trade-off between the computational time and the desired model accuracy. For the present spinning configuration, mass scaled similar models show no clear improvement in predicting local variables compared to mass scaled full-size models at equivalent computational times.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"151 ","pages":"Pages 234-250"},"PeriodicalIF":6.1,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144633863","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":"Collaborative optimization of multi-stage machining parameters for compressor blades","authors":"Rui Zhang ,&nbsp;Junxue Ren ,&nbsp;Jinhua Zhou ,&nbsp;Qi Qi ,&nbsp;Hongmin Xin","doi":"10.1016/j.jmapro.2025.07.039","DOIUrl":"10.1016/j.jmapro.2025.07.039","url":null,"abstract":"<div><div>The machining accuracy of compressor blades directly affects their aerodynamic performance, and optimizing machining parameters is a mainstream approach to improve their precision. Existing studies predominantly utilize a phased and isolated optimization approach, which fails to account for the collaborative optimization of multi-stage machining parameters, resulting in less-than-ideal outcomes. To tackle this limitation, this paper proposes a collaborative optimization method for multi-stage machining parameters of compressor blades that considers error propagation. Firstly, the maximum machining error in the rough machining stage is calculated by integrating the adaptive kernel density estimation function with the small probability event principle (AKDE-SPE). Secondly, a data-driven predictive model for multi-stage machining errors is developed, and a multi-objective optimization framework is established to minimize finish machining errors and total machining time. Subsequently, the model is solved using the multi-objective dung beetle optimization algorithm (MODBO), producing a high-quality Pareto front solution set. On this basis, to reduce reliance on manual experience, a combined weighting-TOPSIS method is proposed for optimal parameters selection. Finally, a case study is conducted to demonstrate the efficacy of the proposed method. Experimental results demonstrate that, compared to the traditional empirical method, the collaborative optimization approach reduces contour error by 28.88 %, position error by 28.29 %, torsion error by 7.26 %, and machining time by 6.05 %. In comparison with the independent optimization method, it reduces contour error by 8.12 %, position error by 2.68 %, torsion error by 0.86 %, and machining time by 6.39 %.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"151 ","pages":"Pages 214-233"},"PeriodicalIF":6.1,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144633862","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":"Manufacturing uniform copper strips by a novel near-isometric continuous expansion extrusion process","authors":"Ying Zhao ,&nbsp;Hongwang Fu ,&nbsp;Zhiyong Yan ,&nbsp;Lili Guo ,&nbsp;Jiuyang Pei ,&nbsp;Xinbing Yun","doi":"10.1016/j.jmapro.2025.07.028","DOIUrl":"10.1016/j.jmapro.2025.07.028","url":null,"abstract":"<div><div>In this paper, a novel near-isometric continuous expansion extrusion was developed to fabricate copper strips. The technique was realized by modifying the deformation channels in continuous extrusion to form a C-shaped cross-section, where an accumulative strain of ~50 across the entire cross-section was achieved. Apart from this, the novel-designed deformation channels homogenize the strain distribution and thus facilitate the uniformity of strain rates and temperatures. Microstructure characterization and mechanical testing at the center and edge areas of the strip confirm the uniformity of the strip, demonstrating the superiority of this technique for manufacturing uniform strips. For comparison, the traditional flat strips produced by continuous extrusion were investigated, where non-uniformly distributed strain, strain rate, and temperature fields were revealed. The microstructures at the center and edge areas of the strip exhibit differences in grain size, dislocation density, and texture, resulting in different mechanical properties. Additionally, the newly designed near-isometric continuous expansion extrusion lowers the 20 % torque force, which shows great potential for extending the extrusion width-thickness ratio. Thus, compared with the traditional flat continuous extrusion and other severe plastic deformation techniques, the developed near-isometric continuous expansion extrusion shows considerable promise for manufacturing uniform metal strips.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"151 ","pages":"Pages 173-187"},"PeriodicalIF":6.1,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144631207","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":"Tailored droplet deposition strategies for direct printing of fully functional components via molten metal jetting","authors":"Xiangyun Gao ,&nbsp;Pearl A. Agyakwa ,&nbsp;Marco Simonelli ,&nbsp;Mark East ,&nbsp;Richard J.M. Hague ,&nbsp;Negar Gilani","doi":"10.1016/j.jmapro.2025.07.004","DOIUrl":"10.1016/j.jmapro.2025.07.004","url":null,"abstract":"<div><div>Molten Metal Jetting (MMJ) is an emerging metal additive manufacturing technique with significant potential across various industries such as electronics, healthcare, aerospace, and robotics. In this process, components are built by depositing molten droplets one by one to form a 3D structure. Ensuring void-free deposition is essential for achieving high density, structural integrity, and electrical conductivity in printed parts. Despite its promise, current research lacks effective methods to fully eliminate internal voids which undermine the performance and functionality of the printed parts. This paper introduces a novel approach that applies tailored droplet deposition techniques to directly produce functional parts via MMJ, without the need for post-processing. Using tin as the printing material, this study evaluates density, electrical conductivity, and surface roughness in samples produced with four distinct methods at substrate temperatures of 150 °C, 100 °C, and 50 °C. The results show that each substrate temperature requires a specific approach, and the identified methods achieve fully dense, highly conductive, and smooth-surfaced parts. Furthermore, a method for printing on a low-temperature (50 °C) substrate was developed, effectively mitigating the influence of residual stress and enabling the fabrication of temperature-sensitive components. This research bridges a critical gap in MMJ by enabling the direct production of fully functional parts, paving the way for broader industrial applications of this technology.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"151 ","pages":"Pages 206-213"},"PeriodicalIF":6.1,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144633956","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 method for generating large-scale implicit lattice structures for direct manufacturing","authors":"Kaixiang Zhang ,&nbsp;Yizhe Yang ,&nbsp;Qingfeng Jia ,&nbsp;Bingshan Liu ,&nbsp;Shan Li ,&nbsp;Xin Li ,&nbsp;Gong Wang","doi":"10.1016/j.jmapro.2025.07.010","DOIUrl":"10.1016/j.jmapro.2025.07.010","url":null,"abstract":"<div><div>The advent of additive manufacturing has significantly expanded the application potential of lattice structures in complex engineering scenarios. However, processing large-scale lattice meshes poses challenges due to the exponential growth in data volume and computation time. To address this issue, this study proposes a hierarchical voxel modeling method of implicit lattices (HVMIL) based on the Signed Distance Field (SDF). First, a GPU-accelerated SDF construction algorithm is proposed, capable of generating lattice structures with millions of elements within milliseconds, achieving unprecedented computational efficiency. Second, a hierarchical voxelization approach, optimized for additive manufacturing, effectively mitigates precision loss associated with STL conversion. Finally, the proposed method supports implicit modeling of various unit cells and field-driven applications, further broadening its applicability. Experimental validation demonstrates that our approach not only meets the stringent requirements of lattice structure applications but also establishes a novel paradigm for efficient modeling and high-precision fabrication in additive manufacturing.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"151 ","pages":"Pages 188-205"},"PeriodicalIF":6.1,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144631223","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":"Surface reinforcement of magnesium alloy achieved via high entropy alloys/Al2O3 composite coating manufactured by middle-low temperature micro-particles deposition","authors":"Yu Zhang ,&nbsp;Jian Zhu ,&nbsp;Mengmeng Xu ,&nbsp;Shuhao Zhao ,&nbsp;Qingqing Tang ,&nbsp;Shuai Wu ,&nbsp;Xidong Hui ,&nbsp;Yi Xu ,&nbsp;Yongling Wu ,&nbsp;Hongyu Zheng","doi":"10.1016/j.jmapro.2025.07.033","DOIUrl":"10.1016/j.jmapro.2025.07.033","url":null,"abstract":"<div><div>With the increasingly wide application of Mg alloys, their surface reinforcements have become a research hotspot. This work aimed to deposit high entropy alloys (HEAs)/ceramic composite coatings on AZ91D surface using middle-low temperature micro-particles deposition (MLT-MPD). Fully dense HEAs/Al₂O₃ coatings were obtained, and the roles of parameters on the deposition characteristics were explored. Moreover, the mechanical and surface corrosion resistances of the coating were assessed via microhardness, nanoindentation, micro-scratch, wear and electrochemical tests. No oxidation or ablation was found on the AZ91D substrate after deposition. The microhardness of as-deposited AZ91D was reinforced to be ~380 HV, which is 5 times that of the substrate. In addition, the coating exhibited both good stiffness and a certain degree of toughness. As a result, the wear resistances of the as-deposited samples were improved significantly. The wear widths and depths were reduced from 1829.27 ± 31.53 μm to 1158.33 ± 71.04 μm and from 107.21 ± 2.57 μm to 26.73 ± 1.30 μm, respectively. Furthermore, the electrochemical corrosion potential (E_corr) was improved from −1558.8 mV to −1094.5 mV, and the passive current density (I_p) was reduced from 122 μA/cm² to 0.0806 μA/cm². This work provides a new approach for surface reinforcement of Mg alloys, which exhibits good application value.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"151 ","pages":"Pages 160-172"},"PeriodicalIF":6.1,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144623764","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":"Dissimilar ultrasonic spot welding of AA6016 alloy-to-DP800 steel: The role of a novel AlSi(Fe) PVD coating","authors":"D. Bajaj ,&nbsp;V.V. Nemade ,&nbsp;N. Stöcker ,&nbsp;D. Sulik ,&nbsp;X.F. Fang ,&nbsp;N.S. Ma ,&nbsp;D.Y. Li ,&nbsp;D.L. Chen","doi":"10.1016/j.jmapro.2025.07.022","DOIUrl":"10.1016/j.jmapro.2025.07.022","url":null,"abstract":"<div><div>Lightweighting in the automotive industry often involves joining dissimilar materials, while ensuring the safety and durability of load-bearing components. However, the joining of dissimilar materials presents significant challenges due to differences in their physical and chemical properties. In this study, a novel AlSi(Fe) physical vapor deposition (PVD) coating was applied on DP800 steel to enhance its compatibility with AA6016 aluminum alloy during solid-state ultrasonic spot welding (USW). The AA6016-to-coated DP800 steel joints, fabricated at welding energies around 1250 J, surpassed the tensile lap shear load requirements specified in the AWS D17.2 standard. The presence of the PVD coating not only enhanced the tensile lap shear strength by 23 % (i.e., from 69 MPa to 85 MPa), but also reduced the welding energy required to achieve optimal joint performance by 37.5 % (i.e., from 2000 J to 1250 J). This reduction in energy consumption further contributed to improved welding efficiency. The AA6016-to-uncoated DP800 steel joints at a welding energy of 2000 J exhibited button pullout failure under tensile loading and high-stress cyclic loading, largely due to excessive thinning of the AA6016 alloy. In contrast, the AA6016-to-coated DP800 steel joints welded at 500 J showed adhesive failure caused by defects at the weld interface. However, at a welding energy of 1250 J, these joints demonstrated superior intermixing between the Al sub-layer of PVD coating and the AA6016 alloy, resulting in a combination of cohesive and adhesive failure modes. The findings reveal the effectiveness of the AlSi(Fe) PVD coating in improving the mechanical properties of the joints while enhancing the energy efficiency of the welding process.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"151 ","pages":"Pages 103-119"},"PeriodicalIF":6.1,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144623761","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":"Fabrication of smooth and deep microchannels on soft polymer by stretching enhanced cryogenic assisted micro milling","authors":"Partha Sarathi Mallick ,&nbsp;Ashwani Pratap ,&nbsp;Karali Patra","doi":"10.1016/j.jmapro.2025.07.038","DOIUrl":"10.1016/j.jmapro.2025.07.038","url":null,"abstract":"<div><div>Soft viscoelastic polymer is typically difficult –to-machine up to larger depth by cryogenic assisted micro milling (CAMM) process. Stretching enhanced cryogenic assisted micro milling (SECAMM), a single stage and unfilled processing method for soft polymer, is proposed in this study. Tensile stress is initially generated in bulk polymer by uniaxial stretching; then CAMM is performed to fabricate microchannel. To investigate the impact of structural change by directional stretching on deformation response, SECAMM is performed at different stretching ratio (1, 1.1, 1.25, 1.5, and 2) and cutting directions (0°, 45°, and 90°). Further to evaluate the changes in mechanical properties of bulk polymer under cryogenic environment, a scratch based method is used to determine coefficient of dynamic friction (CODF) and fracture toughness under different cutting condition. The study highlights that increase in stretch ratio reduces CODF and fracture toughness with minimum value along 90° direction. Results showed that SECAMM process helps to reduce surface roughness value of machined surface to 2.30 μm for 100 μm depth microchannel. Compared to CAMM, SECAMM along 90° direction reduces the material recovery percentage by 45–55 %, improves the microchannel dimensional accuracy, and enhance surface flatness.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"151 ","pages":"Pages 120-141"},"PeriodicalIF":6.1,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144623762","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":"Enhancing heating uniformity of radio frequency additive manufacturing via functional grading","authors":"Hongtao Song ,&nbsp;Ali Sohaib ,&nbsp;Jared Allison ,&nbsp;Christopher Tuck ,&nbsp;Richard Hague ,&nbsp;John Pearce ,&nbsp;Joseph Beaman ,&nbsp;Carolyn Seepersad","doi":"10.1016/j.jmapro.2025.07.013","DOIUrl":"10.1016/j.jmapro.2025.07.013","url":null,"abstract":"<div><div>Radio Frequency Additive Manufacturing (RFAM) is an additive manufacturing process that utilizes Radio Frequency (RF) radiation as the sole heat source to heat and sinter an entire object simultaneously. Parts are fabricated selectively from powders, similarly to powder bed fusion but with RF radiation replacing laser or electron beams as the energy source. Typical polymer powders, such as nylon 11 or 12, are relatively transparent to RF energy sources, but polymer powders that are doped with conductive additives selectively absorb RF energy. By depositing electrically conductive dopants into selective regions of an insulating polymer powder bed, those regions of the powder bed can be sintered quickly and volumetrically via RF radiation into engineered parts. Previous work demonstrated that heating uniformity is a challenge related to the dopant density and the geometry of the part, but simulations suggested that it can be addressed by functionally (spatially) grading the dopant density. In this work, those simulation-based, functionally graded designs are fabricated for the first time via a combination of binder jetting additive manufacturing and sintering in an RF heating apparatus. The heating uniformity and geometric accuracy of the functionally graded samples are evaluated and compared to that of uniformly doped samples. The results show that functionally graded samples exhibit enhanced heating uniformity and improved geometric accuracy.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"151 ","pages":"Pages 142-159"},"PeriodicalIF":6.1,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144623763","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":"Pi-TabNet: An explainable physics-informed deep learning method for flatness prediction in cold-rolled copper strips","authors":"Bowei Duan ,&nbsp;Dongcheng Wang ,&nbsp;Guodong Wang ,&nbsp;Yexin Hu ,&nbsp;Yanghuan Xu ,&nbsp;Hongmin Liu","doi":"10.1016/j.jmapro.2025.06.090","DOIUrl":"10.1016/j.jmapro.2025.06.090","url":null,"abstract":"<div><div>Flatness is a critical quality indicator for high-end cold-rolled strip products. In industrial applications, flatness is automatically measured and controlled through flatness measurement and control systems. Traditional mechanistic models for flatness prediction face challenges, including low accuracy, lengthy development cycles, and slow computational speeds. Although deep learning-based intelligent models show potential, their industrial adoption remains limited due to poor explainability, insufficient incorporation of physics-informed knowledge from the rolling domain, and low-quality training data. Furthermore, flatness prediction for cold-rolled copper strips remains an underexplored research area. To address these challenges, this study proposes an explainable, physics-informed deep learning method for flatness prediction at the exit stage of cold-rolled copper strips. Using industrial big data, actual operating conditions, and data mining techniques, two flatness datasets were constructed for cold-rolled copper strips under representative industrial scenarios. Guided by prior physical knowledge from the rolling domain, a novel deep neural network architecture, Physics-informed TabNet (Pi-TabNet), was developed. The training process incorporates physical constraints, ensuring that flatness predictions comply with physical laws, which improves the model's explainability and robustness. The results on the test set indicate that the proposed method achieves higher prediction accuracy than other classical algorithms and demonstrates strong generalization performance. Furthermore, transfer learning experiments indicate that the proposed physics-informed model possesses strong feature extraction capabilities and adapts well to varying data distributions across different scenarios. Additionally, the SHapley Additive exPlanations (SHAP) method, an explainable artificial intelligence (XAI) technique, was employed to elucidate the model's decision-making process, which improves the transparency and reliability of the predictions. Finally, a physical consistency analysis method based on Legendre basis functions is proposed to systematically verify the model's physical consistency and interpretability under perturbations of key process parameters.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"150 ","pages":"Pages 1260-1281"},"PeriodicalIF":6.1,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144605991","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}