Manufacturing Letters最新文献

{"title":"Mathematical modeling and experimental Investigations on forming force during tube spinning of AA6061☆☆","authors":"Ravi Bhatt ,&nbsp;Mallika Bhatt ,&nbsp;Nader Asnafi","doi":"10.1016/j.mfglet.2025.06.046","DOIUrl":"10.1016/j.mfglet.2025.06.046","url":null,"abstract":"<div><div>In present research, a mathematical model based on dimensional analysis for estimating resultant force has been proposed for single roller backward tube spinning along with experimentations. Tube spinning is also known as flow forming process which is generally used to produce ultra precise thin-walled tubes for aviation, aerospace and defense application. The prediction of forces are important aspects for accurate tooling design and desired output of formed components. Therefore, an attempt has been made to propose a mathematical model to predict the resultant force. Subsequently, an indigenous experimental test rig has been developed to measure the force elements. Three operating parameters (speed, feed and reduction) and two tooling parameters (roller nose radius and leading angle) were considered for experiments. The operating variables were considered at three levels and tooling variables are taken for two levels for suitable robust experimental design (Taguchi L₃₆). Single roller backward spinning was adopted with the AA6061 as blank material as it is normally used aluminum alloy due to its intense applications. It has been observed that the axial force is found to be highest among other two components of forces i.e. radial and circumferential. Also, it has been found that the resultant force is mainly influenced by forming depth. It means, higher the forming depth, higher the resultant force. The proposed model was trained and tested against experimental data. The adequacy of the model was checked by various quantitative measures. The initial information can be obtained about resultant force with the use of the model to design the roller for different material conditions.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 386-395"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of metal additive manufacturing processes for the production of tailored blanks","authors":"Raphaela März,&nbsp;Marion Merklein","doi":"10.1016/j.mfglet.2025.06.050","DOIUrl":"10.1016/j.mfglet.2025.06.050","url":null,"abstract":"<div><div>The implementation of resource-efficient approaches to sheet metal forming, such as load-adapted design, has the potential to significantly reduce greenhouse gas emissions. The use of tailored blanks with different thicknesses and materials optimizes both the forming process and the final application of the products. The integration of additive manufacturing allows for greater customization and multi-material combinations, improving the geometric flexibility of semi-finished products. As part of the investigations, the potential of using powder bed fusion using a laser beam (PBF-LB/M) and laser-based directed energy deposition (DED-LB/M) to locally reinforce semi-finished sheet metal products is examined. For this purpose, customised semi-finished products are produced using both processes and analysed with regard to their geometry, metallographic structure and mechanical properties. Furthermore, the part properties after deep-drawing the tailored additive blanks are investigated.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 424-429"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An experimental investigation of hybrid fused filament fabrication with in-process machining","authors":"John D. Baron,&nbsp;Muhammad Omer Naveed,&nbsp;Lei Chen","doi":"10.1016/j.mfglet.2025.06.053","DOIUrl":"10.1016/j.mfglet.2025.06.053","url":null,"abstract":"<div><div>Fused filament fabrication (FFF) is the most widely used additive manufacturing process thanks to its low cost and easy setup, but it is limited by low accuracy, poor surface finish, slow build time, and inferior anisotropic mechanical properties. In this study, we experimentally investigate the integration of in-process machining with FFF using PLA filaments on a commercial multi-head printer setup. A hybrid FFF with in-process machining test platform with process monitoring capabilities was developed. The experimental platform development process identified that spindle rigidity and newly printed filament temperature control (e.g., quick cooling with compressed air nozzle) were two key considerations for a high-quality machined surface. To ensure the surface finish of the hybrid manufactured parts, especially on less accurate/repeatable FFF printer setup, it would be preferable to conduct finish cutting of FFF surfaces in one path to avoid misalignment error associated with multiple paths. With such hybrid FFF-machining integration strategies, a benchmark test showed that hybrid FFF using large layer thickness followed by a quick finish milling path yielded a surface finish of 5 times lower R_a value at 34% of the total cycle time compared to pure FFF with fine layers, which greatly enhances the efficiency and quality of FFF-based parts. In terms of hybrid part strength, Mode I fracture tests showed that the correlation between the machining depth of cut and the FFF print perimeter thickness was critical for the hybrid part fracture resistance. Partially cut filament could lead to weak bonding regions that were easier for crack initiation and propagation through a combination of inter-, intra-, and <em>trans</em>-laminar failures.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 442-452"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scheduling in Industry 4.0: A Digital Twin-based approach for scheduling and smart Material-Handling Considerations","authors":"Ahmed Azab ,&nbsp;Hani Pourvaziri","doi":"10.1016/j.mfglet.2025.06.018","DOIUrl":"10.1016/j.mfglet.2025.06.018","url":null,"abstract":"<div><div>Smart manufacturing constitutes the backbone of Industry 4.0 (I4.0), allowing for heightened autonomy of the various interacting cyber-physical systems on the production floor. Connectivity, a vital enabler, plays a crucial role through state-of-the-art Digital Twin (DT) technologies driven by underlying innovations like the industrial Internet of Things, Cloud Computing, and advancements in sensory devices. In this article, it is argued that a pre-DT optimal approach employing queuing aspects of the machine buffers can play a crucial role in optimally determining the baseline schedules for the shop as well as a few related system-design aspects vis-à-vis the size of the utilized fleet of smart Automated Guided Vehicles (sAGVs) and the employed buffer capacities. sAGVs are autonomous vehicles used for material transportation between machines, reducing manual handling and improving efficiency. Initial dispatching rules for the sAGVs are also determined at that stage. Such initially produced schedules and sAGV dispatching rules are constantly revisited, though, later in the development lifecycle of the manufacturing system at the DT level, according to the undertaking disruptions on the shop floor. At that DT stage, other operational aspects pertaining to the material handling system, namely, aisle directionality, mobile modular buffers, and input/output points of the work centers, are adjusted. The employed two-stage planning framework, integrating both Pre-DT and full-scale DT planning, aims to optimize aspects of the system from the design phase to its real-time operations, employing a novel methodology leveraging mathematical programming, queuing models, and deep learning. A key finding of this study is that dynamically adjusting aisle directionality, rerouting AGVs through alternative paths, and deploying modular mobile buffers while optimizing job scheduling significantly reduce transportation time, minimize delays, and enhance real-time adaptability. The proposed framework effectively mitigates disruptions, achieving 100% elimination of machine failure impact, a 33% reduction in aisle congestion delays, and a 37% decrease in buffer overflow delays, demonstrating notable improvements in system performance and resilience.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 136-147"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","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.2025.06.004","DOIUrl":"10.1016/j.mfglet.2025.06.004","url":null,"abstract":"","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Page 8"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive toolpath for improved thermal management in additive manufacturing (AM)","authors":"Marc Corfmat,&nbsp;Charles Ringham,&nbsp;Masakazu Soshi","doi":"10.1016/j.mfglet.2025.06.098","DOIUrl":"10.1016/j.mfglet.2025.06.098","url":null,"abstract":"<div><div>Additive manufacturing (AM) processes, such as Fused Filament Fabrication (FFF) and Directed Energy Deposition (DED), are highly susceptible to heat accumulation and uneven cooling, leading to residual stresses, geometric inaccuracies, and compromised material properties. While the magnitude of these effects is far smaller in FFF, effective thermal management is essential to address these challenges in DED. This paper proposes a novel adaptive toolpath control strategy that dynamically adjusts the deposition path of the subsequent layer based on the thermal gradient of the previous layer. While DED is the primary focus for this implementation, initial experimentation leveraged FFF due to its cost-effectiveness and similar thermal characteristics to DED, allowing for efficient testing and validation of the proposed strategy. Four infill stacking patterns—SAME, FLIP, ROTATE SAME, and ROTATE FLIP—were tested, revealing that FLIP and ROTATE FLIP produced more symmetric thermal distributions. These results demonstrate the feasibility of adaptive toolpath strategies for improving thermal management in DED, with future work focused on advanced algorithms, thermal simulations, and validation in DED applications.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 832-838"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two step training a single physics-informed neural network for solving Navier Stokes equations with various boundary conditions","authors":"Vipul Bansal ,&nbsp;Shiyu Zhou ,&nbsp;Nicolas Strike","doi":"10.1016/j.mfglet.2025.06.009","DOIUrl":"10.1016/j.mfglet.2025.06.009","url":null,"abstract":"<div><div>Physics-Informed Neural Networks (PINNs) are a popular scientific machine learning framework used to solve partial differential equations (PDEs). One of the common applications of PINNs is in solving fluid flow problems using the Navier–Stokes (NS) equations. The NS equations are a set of PDEs that describe the flow of a viscous fluid and have been extensively applied in manufacturing problems, such as modeling flow in injection molding or the flow of molten metal in additive manufacturing. Solving a single PINN with various boundary conditions requires training a unified model to predict the flow field for each specific boundary condition setup. This poses a challenge in training PINNs due to the limited number of samples that can be taken from the parametric space corresponding to various boundary conditions, often leading to poor-quality solutions. To address this, we propose a two-step solution to solve PINNs for the Navier–Stokes equations with various boundary conditions. The proposed method enables PINNs to learn effectively both from the domain and from parametric spaces. This two-step approach provides the model with a finer initial understanding of the domain space and then shifts to sampling from the parametric space to enhance its knowledge of the parametric variations. Numerical studies demonstrate the effectiveness of the proposed approach compared to direct training of PINNs. Increased knowledge about domain space provides the model with better learning of boundary conditions and lower PDE residuals. The proposed method uses the same computational requirements as direct training but provides better convergence. Furthermore, the ability to learn parametric boundary conditions enables PINNs to be applied to a variety of versatile applications.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 48-58"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Femtosecond laser micromachining of barbed sutures","authors":"Walid Al Asad ,&nbsp;Shubha Majumder ,&nbsp;Karuna Nambi Gowri ,&nbsp;Martin W. King ,&nbsp;Xin Zhao","doi":"10.1016/j.mfglet.2025.06.061","DOIUrl":"10.1016/j.mfglet.2025.06.061","url":null,"abstract":"<div><div>This study explores the fabrication of barbed sutures of biodegradable polymers, such as P4HB and Cagut, using a femtosecond laser. Barbed sutures are in high demand for minimally invasive procedures, with the benefits of reducing the need for knots, enhancing wound closure stability and minimizing tissue trauma. Traditional approaches, such as mechanical cutting and longer-pulses lasers, result in imprecise cutting and extended thermal damage. In contrast, ultrashort pulse durations of femtosecond lasers enable high-precision cutting with the added benefits of minimal heat-affected zones. This research investigates the effects of key laser parameters, such as laser fluence, repetition rate, overlapping ratio and number of scans, on barb quality and identifies the optimal conditions for consistent, high-quality barbs with sharp tips and minimal thermal damage. Moreover, the threshold fluence values established here, for P4HB and Catgut, serve as a reference for future study. Results demonstrate that femtosecond laser technology can be a promising alternative to traditional barb fabrication techniques.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 517-523"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An investigation of post-weld heat treatment for welded AISI 1007 steel using TIG-MIG hybrid welding technique","authors":"O. Olaogun ,&nbsp;P.A. Olubambi","doi":"10.1016/j.mfglet.2025.06.036","DOIUrl":"10.1016/j.mfglet.2025.06.036","url":null,"abstract":"<div><div>The adoption of hybrid welding in manufacturing sectors that produce heavy-duty machinery is increasing. Manufacturing industries that produce heavy duty machinery are increasingly utilizing hybrid welding. This is as a result of several drawbacks of standalone welding processes, such as undercut formation, spatter formation and low weld metal toughness. TIG-MIG hybrid welding, a special, low-cost hybrid welding process incorporating the properties of both TIG and MIG welding processes, produces precise welds. While this hybrid technique combines the benefits and improvement in its quality, its efficiency can be enhanced. Therefore, the post weld heat treatment of the TIG-MIG hybrid welded joint is proposed. This research presents an investigation of post weld heat treatment on TIG-MIG hybrid welded AISI 1007 steel. The hybrid welding procedure was carried out on a 7 mm AISI 1007 steel plate. The butt joint configuration had a single V-notch groove. The hybridized TIG-MIG welded joint is subjected to Post-Weld Heat Treatment (PWHT) in both normalizing and annealing conditions at 850 °C. Tensile, microhardness and charpy impact test were employed to investigate the mechanical properties of the hybrid welded joint. The microstructural examination was achieved using Raman and SEM with EDS attachment. Findings show that post weld heat treatments, particularly normalizing and annealing, improve the uniformity and refinement of the grain structure in the as-weld TIG-MIG hybrid welded joints. However, unlike in the normalized condition, microstructural images of the annealed TIG-MIG interface confirm the presence of carbide precipitates. The as-welded condition exhibits higher strength, while heat-treated conditions enhance ductility and toughness. Selecting the optimal welding condition should depend on the balance of strength, ductility, and toughness required for the application.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 294-305"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of machine learning to predict the properties of wood- composite made from PET, HDPE, and PP fibres","authors":"Derrick Mirindi ,&nbsp;David Sinkhonde ,&nbsp;Frederic Mirindi","doi":"10.1016/j.mfglet.2025.06.007","DOIUrl":"10.1016/j.mfglet.2025.06.007","url":null,"abstract":"<div><div>Plastic composites provide an eco-friendly substitute for conventional construction materials. Indeed, recycling waste plastic represents a progressive approach to waste management with the aim of mitigating the growing issue of pollution in urban environments. Our research aims to review the physical properties, including water absorption (WA) and thickness swelling (TS), and mechanical properties, such as the internal bond (IB), the modulus of rupture (MOR), and the modulus of elasticity (MOE), of the latest findings made of wood panels combined with plastic. We are focusing on three types of plastic, namely polyethylene terephthalate (PET), polypropylene (PP), and high-density polyethylene (HDPE). In addition, we employed machine learning (ML) algorithms, including the hierarchical clustering dendrogram, the Pearson correlation coefficient, the support vector regression, the random forest (RF), and the decision tree (DT) for prediction analysis. For instance, the results indicate that combining HDPE with wood pulp fiber increases the MOR (42.45 MPa) and MOE (66.7 MPa), respectively. Furthermore, mixed plastics such as PET, HDPE, PP, and LDPE improve the dimensional stability by reducing the WA (0.32 %) and TS (0.18 %), respectively. In most cases, these results meet the minimum standard requirement for general-purpose boards, according with the American National Standard for Particleboard (ANSI/A208.1-1999), the European standard (EN 312), and Brazilian Association of Technical (ABNT NBR) standard. In addition, the dendrogram identifies three primary clusters with varying Euclidean distances, indicating the performance of wood-plastic panels for both physical and mechanical properties. Notably, the dimensional stability among panels is stronger than that of mechanical properties. The correlation matrix is important for selecting an appropriate plastic. The SVR, RF, and DT algorithms make predictions by analyzing the properties of the panel. For instance, the DT algorithm shows that when WA is less than 25 %, the predicted value of TS is 0.24 %; in addition, when the value is between 25 % and 75 %, TS is equal to 7.92 %; also, when WA is greater than 75 %, TS is predicted to be at 13.7 %. This innovative method of utilizing ML and DL for prediction opens new possibilities for the use of plastic in panel production, as it allows for the selection of suitable materials and fabrication techniques to create a wood-plastic composite.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 24-35"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}