Manufacturing Letters最新文献

{"title":"Investigation of Novel Virtual Impactor Designs on the Aerodynamics of Material Flow in Aerosol Jet Printing (AJP)","authors":"Ethan O’Malley,&nbsp;Roozbeh Ross Salary","doi":"10.1016/j.mfglet.2026.07.105","DOIUrl":"10.1016/j.mfglet.2026.07.105","url":null,"abstract":"<div><div>This study presents a computational investigation into how different exhaust configurations affect the internal flow characteristics and aerodynamics of a virtual impactor (VI) designed for use in aerosol jet printing systems. Four geometrical designs were evaluated using Computational Fluid Dynamics (CFD), each incorporating a unique exhaust layout configuration, including a single perpendicular exhaust, dual perpendicular exhausts, dual parallel exhausts, and an annular exhaust configuration. The analysis focused on major aerodynamic parameters, including velocity fields, pressure profiles, turbulence characteristics, and recirculation behavior. Velocity contours revealed consistent high-speed jet formation in all cases, with observable flow splitting and axisymmetric deflection into the separation chamber. Design 2 produced the most balanced and symmetric velocity transitions, while Design 3 displayed irregular gradients near the collector inlet. Streamline analysis indicated that Design 2 suppressed counter-circulation loops more effectively than the other designs. Pressure analysis showed that Design 1 consistently exhibited elevated static pressure in the collector region, which may contribute to improved particle retention but potentially reduce inertial focusing. In contrast, Design 4 featured lower collector pressure, favoring inertial separation but possibly increasing recirculation risk. Turbulent kinetic energy (TKE) and eddy viscosity distributions remained similar across all designs, with turbulence concentrated near the jet separation zone. These findings emphasize importance of exhaust port symmetry and distribution in controlling internal VI flow behavior. The results provide actionable insights for optimizing geometry to balance flow stability, pressure profiles, and inertial separation efficiency in high-resolution printed electronics applications.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 903-914"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149095980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Welcome from the Editor-in-Chief","authors":"Laine Mears","doi":"10.1016/j.mfglet.2026.07.009","DOIUrl":"10.1016/j.mfglet.2026.07.009","url":null,"abstract":"","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Page 8"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149095955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data- Driven Quality Control and Process Planning for Continuous Carbon Fibre Reinforced Thermoplastic Composite 3D Printing","authors":"Anand Sankar Manipuzha,&nbsp;Rajkumar Velu,&nbsp;T.S. Sanjay,&nbsp;S. Parthasarathy,&nbsp;S.Suresh Raja","doi":"10.1016/j.mfglet.2026.07.089","DOIUrl":"10.1016/j.mfglet.2026.07.089","url":null,"abstract":"<div><div>Continuous carbon fibre-reinforced thermoplastic (CCFRTP) 3D printing enables lightweight, high-strength structures but remains highly sensitive to deposition parameters, leading to defects such as under-extrusion, over-extrusion, and poor layer adhesion. This study presents a data-driven Prescriptive Quality Control (PQC) framework integrating machine learning and explainable artificial intelligence (XAI) for predictive quality classification and parameter optimization in co-extrusion-based continuous fibre printing. A physically grounded dataset was established by systematically varying print speed, layer height, PLA feed rate, and thermal conditions, supported by optical and scanning electron microscopy (SEM)-based defect labelling across four quality classes. To address data sparsity, a domain-constrained Conditional Tabular Generative Adversarial Network (CTGAN) was employed for data augmentation, followed by supervised learning using Multi-Layer Perceptron (MLP), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) classifiers. XGBoost achieved 98.1% classification accuracy and was selected for its robustness and compatibility with SHapley Additive exPlanations (SHAP) analysis. Feature attribution identified print speed (mean SHAP = 0.351) and layer height (0.272) as dominant quality drivers, consistent with extrusion stability and interlayer fusion mechanics. Decision-boundary analysis revealed feasible parameter regions yielding &gt;0.85 probability of Good-quality prints. Independent forward printing validation on unseen parameter combinations demonstrated 87.5% prediction agreement and 87.5% optimization success, confirming practical generalization of the framework. The proposed approach provides a scalable and interpretable pathway for data-driven process planning in continuous fibre composite additive manufacturing without reliance on complex in-situ sensing.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 753-764"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149096086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of Measurement Methods for Surface Roughness Clustering Analysis of Additively Manufactured Inconel 718","authors":"Alok Kumar,&nbsp;Kota Rohith Raj,&nbsp;Suresh Kumar Reddy Narala,&nbsp;Kundan K. Singh","doi":"10.1016/j.mfglet.2026.07.091","DOIUrl":"10.1016/j.mfglet.2026.07.091","url":null,"abstract":"<div><div>The present work proposes two different methods for measuring and reconstructing the surface generated by WAAM. The first method is based on a 3D scanner, while the second method utilizes a laser displacement sensor to capture the surface height at different deposition locations. After acquiring the point cloud data, the surface has been reconstructed to estimate the surface roughness. The surface roughness of various zones has been calculated and compared. The proposed two approaches yielded different maximum roughness values of 2.1 mm and 1 mm for the point cloud data captured using the laser displacement sensor and the 3D scanner, respectively. The topmost deposited layer exhibited surface roughness in the range of 0.06 to 2.1 mm when measured using the laser displacement sensor, whereas the roughness ranged from 0.02 to 0.93 mm in the case of the 3D scanner. Furthermore, K-means clustering analysis revealed two distinct roughness clusters across the entire WAAM-deposited surface.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 778-784"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149096088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pit Density Forecasting for Abrasive Finishing Processes of Nuclear Fusion Target Capsules","authors":"Shashank Galla,&nbsp;Vikash Sunakara,&nbsp;Sean Michael Hayes,&nbsp;Monika Biener,&nbsp;Suhas Bhandarkar,&nbsp;Satish Bukkapatanam","doi":"10.1016/j.mfglet.2026.07.058","DOIUrl":"10.1016/j.mfglet.2026.07.058","url":null,"abstract":"<div><div>Inertial Confinement Fusion (ICF) experiments at Lawrence Livermore National Laboratory require target shells with nanometer-scale surface precision for successful ignition. These shells undergo ultra-precision lapping and polishing; however, the process is susceptible to rare, deep pits that can induce hydrodynamic instabilities and degrade fusion performance. Because shell fabrication is time- and resource-intensive, reliable early prediction of shell quality is critical for reducing costs and improving yield. However, predicting pit evolution is challenging due to the nonlinear, stochastic, and stage-dependent dynamics of the process, while existing approaches rely on scalar metrics that fail to capture rare defects and distributional changes. To address this limitation, we propose a distribution forecasting model that predicts the full pit distribution across polishing stages. The approach employs a dual-encoder CNN–Transformer architecture that integrates kernel density estimation (KDE)-based pit distributions with process parameters through cross-attention. The model is trained using a composite loss combining Kullback–Leibler divergence, Wasserstein distance, and L2 error to capture tail behavior and distribution shifts. Across 21 experimental batches, the method reduces KL divergence and Wasserstein distance by 27–66% compared to multiple baselines and achieves 88% sensitivity in detecting large, deep pits at a 22% false positive rate. The framework enables early rejection of poor quality shells and facilitates process plan optimization, advancing a transition from reactive inspection to proactive, data-driven manufacturing.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 473-484"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149096154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Additive Manufacturing System for 3D Printed Electronics: Wire-Resin Co-Axial Material Extrusion","authors":"Carson Vath,&nbsp;Ashish Jacob,&nbsp;Kazi Safowan Shahed,&nbsp;Jacklyn Claire Griffis,&nbsp;Kazi Md Masum Billah,&nbsp;Guha Manogharan","doi":"10.1016/j.mfglet.2026.07.077","DOIUrl":"10.1016/j.mfglet.2026.07.077","url":null,"abstract":"<div><div>As interest in a system-level approach to electronics manufacturing grows, processes for independently manufacturing complex circuit designs are gaining more traction. The current processes face multiple challenges, for example, issues such as ink “wash-out” that continue to occur due to higher temperature and pressure in processes such as in-mold electronics. Other processes, such as embedded three-dimensional (EMB3D) printing, require creating a new mold design for every design iteration, which is challenging and time-consuming. Therefore, there is a need for a robust method to rapidly fabricate complex interconnections within the same machine envelope. Presently, there are limited wire-embedding techniques for manufacturing interconnections in a planar build layer. This paper presents a novel wire-embedding technique through a co-axial extrusion process, which can be retrofitted into a generic material extrusion (MEX)-based hybrid additive manufacturing (AM) machine and uses a wire-based feedstock, which is substantially less expensive than conductive inks and requires fewer processing steps than conventional direct ink writing systems. Hybrid AM machines retrofitted with this system can be used to develop capabilities to incorporate functional electronic components within the print volume and can be used in applications such as antennas, strain sensors, neural probes, sensing elements, electrodes, and anti-counterfeiting features, among others. Hybrid AM can potentially automate this process by integrating complementary techniques such as pick-and-place and wire-embedding simultaneously within a single build.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 654-660"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149096158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Numerical and Experimental Analysis on Jet Interaction Dynamics in Double-Nozzle Electrochemical Jet Machining","authors":"Ronaldo Singh Naorem,&nbsp;Pradeep Dixit","doi":"10.1016/j.mfglet.2026.07.073","DOIUrl":"10.1016/j.mfglet.2026.07.073","url":null,"abstract":"<div><div>This study presents a combined numerical and experimental investigation on the influence of pitch size in electrochemical jet machining (ECJM) using a double-nozzle configuration. The study focuses on understanding how electrolyte jets interact hydrodynamically and electrochemically when operated in close proximity. A two-dimensional finite element model was developed to simulate electrolyte flow, electric potential distribution, and material dissolution. Experimental validation was performed on tungsten plates using an in-house ECJM setup under various pitch and jet velocity conditions. Results revealed that smaller pitches lead to overlapping hydraulic jumps and merged electric fields, producing secondary dissolution between the nozzles. Increasing the pitch suppresses this interference, enabling localized and predictable machining. Fabrication of parallel micro-grooves arranged in a 2 mm pitch was demonstrated with minimal secondary dissolution. The findings offer practical design guidelines for optimizing multi-jet ECJM configurations aimed at high-precision and high-throughput micro-manufacturing.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 616-624"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149096160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancement in Surface Finish of Additively Manufactured 17-4PH Stainless Steel Using a Hybrid Chemical Machining–Magnetic Abrasive Finishing Approach","authors":"Harish Kumar,&nbsp;Gurpreet Singh,&nbsp;Anil Srivastava,&nbsp;Majid Husseini","doi":"10.1016/j.mfglet.2026.07.067","DOIUrl":"10.1016/j.mfglet.2026.07.067","url":null,"abstract":"<div><div>Additive Manufacturing (AM) is a cutting-edge technique utilized for the precise manufacturing of complex components made from a variety of material compositions. Although AM, generally, produces a better surface finish than traditional subtractive methods, additional post-processing is required to attain the desired surface characteristics. One commonly used AM material is 17-4PH stainless steel, which is majorly employed in modern industries like aerospace, marine, petroleum, chemical, medical, and firearms due to its superior physical and chemical properties compared to other stainless steels. Surface finish of additively fabricated 17-4PH stainless steel can be further improved using various finishing techniques. This study presents the results of a hybrid finishing approach, combining chemical machining and magnetic abrasive finishing (MAF), implemented to additively fabricated 17-4PH stainless steel. The influence of three key process parameters during chemical machining was investigated, while MAF parameters were held constant. Experimental results show that the sequential use of these two processes significantly enhances surface quality by reducing surface roughness (Ra) from range 2.06-2.42 µm to range 0.09-0.91 µm.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 561-569"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149096309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the Three-Dimensional Reconstruction Accuracy of Additively Manufactured Parts using Structure from Motion","authors":"Hossein Kabir,&nbsp;Charles T. Whealton,&nbsp;William P. King","doi":"10.1016/j.mfglet.2026.07.036","DOIUrl":"10.1016/j.mfglet.2026.07.036","url":null,"abstract":"<div><div>Additive manufacturing (AM) adoption in production environments requires the ability to verify geometry and tolerances. Inspection technologies such as laser and structured-light scanners offer good performance but face limitations in cost, portability, and flexibility. There is a need for complementary low-cost approaches for routine inspection tasks. This paper develops a workflow for part inspection using Structure-from-Motion (SfM), a method that creates three-dimensional (3D) objects from photographs. The workflow is tailored for AM inspection, systematically isolating the influence of surface appearance (texture/ reflectivity), sensor modality, image count, and imaging parameters (downsampling and magnification) on reconstruction fidelity. The paper studies 3D reconstruction of an AM engine bracket fabricated with six controlled surface finishes, with both polymer and metal parts. The bracket is imaged with monochrome and color machine-vision cameras. We demonstrate calibrated capture, incremental reconstruction, and joint bundle adjustment. The reconstruction quality is quantified through photometric consistency and dimensional accuracy as a function of the number and type of images used for SfM. The reconstructed 3D objects are compared against laser scan and caliper measurements. We find that surface appearance strongly dictates reconstruction accuracy, and that monochrome imaging provides more stable feature detection and lower error than color imaging. Increasing the number of viewpoints improves accuracy up to approximately 360 images, beyond which additional viewpoints yield little benefit. Reasonably good 3D reconstruction is possible with 180 images, depending on the part finish and other parameters. We find that SfM can achieve dimensional accuracy smaller than 0.1 mm, with residual errors concentrated in occluded or high-curvature regions. The paper establishes practical guidelines for applying SfM as a low-cost metrology tool for AM part inspection and reverse engineering.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 271-282"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149096528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Foaming-Process-Derived Graphene Oxide-Based Foamed PDMS with Micro Scale Air Pockets","authors":"Jongwoo Hong,&nbsp;Hyunjune Lee,&nbsp;Jin Hong,&nbsp;Geon Mo Kim,&nbsp;Junghyun Joo,&nbsp;Teajong Hwang,&nbsp;Sung Woon Cha,&nbsp;Seong Chan Jun","doi":"10.1016/j.mfglet.2026.07.024","DOIUrl":"10.1016/j.mfglet.2026.07.024","url":null,"abstract":"<div><div>Lightweight polymeric foams have attracted considerable attention as thermal insulation, impact absorption layers, and even soft robotics owing to their low density, tunable elasticity and low thermal conductivity. In this study, a graphene oxide (GO) based foamed polydimethylsiloxane (PDMS) composite was fabricated through a controlled foaming process, forming a 3D porous network with micro air pockets uniformly distributed within the PDMS matrix. The incorporation of GO enhanced the interfacial bonding with PDMS chains, promoting stable bubble formation and improving the overall pore uniformity. Structural investigation indicated that the resultant foam possessed an average pore size of 52.6 <span><math><mi>μ</mi></math></span> m and uniformity of 71.2%, reflecting a meticulously regulated microstructure affected by both foaming temperature and GO content. These findings offer essential understanding of the process-structure interaction in polymeric foams and underscore the potential of GO/PDMS composites as adaptable platforms for lightweight and flexible functional materials.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"49 ","pages":"Pages 147-152"},"PeriodicalIF":2.8,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149096604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}