Russel Bradley, Stanley S. Salim, Brian W. Anthony
{"title":"Learning through development of a digital manufacturing system in a learning factory using low-code/no-code platforms","authors":"Russel Bradley, Stanley S. Salim, Brian W. Anthony","doi":"10.1016/j.mfglet.2025.09.001","DOIUrl":"10.1016/j.mfglet.2025.09.001","url":null,"abstract":"<div><div>This study demonstrates how low-code/no-code (LCNC) platforms can enable undergraduate students without software development backgrounds to design and build digital manufacturing systems. Students developed an IoT-enabled Manufacturing Execution System using Tulip Interfaces—an LCNC platform, focusing on applications like inventory tracking, machine monitoring, and digital work instructions in the FrED Factory—a learning factory at MIT. Evaluation through a pilot study showed students gained a strong understanding of smart manufacturing concepts while spending most of their time on systems design rather than software development. Individual interviews followed by a post-interview survey highlighted that the average percentage of time split between systems design and debugging the LCNC platform was 70–30% respectively. Additionally, all students responded with “strongly agree” to the question of whether the project enhanced their understanding of smart manufacturing concepts. LCNC platforms offer a practical, accessible approach to teaching digital manufacturing and can accelerate skill development in both educational and industrial settings.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"46 ","pages":"Pages 10-15"},"PeriodicalIF":2.0,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145158856","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":"Technology prediction of a 3D model using neural network","authors":"Grzegorz Miebs , Rafał A. Bachorz","doi":"10.1016/j.mfglet.2025.08.005","DOIUrl":"10.1016/j.mfglet.2025.08.005","url":null,"abstract":"<div><div>Accurate estimation of production times is critical for effective manufacturing scheduling, yet traditional methods relying on expert analysis or historical data often fall short in dynamic or customized production environments. This paper introduces a data-driven approach that predicts manufacturing steps and their durations directly from 3D models of products with exposed geometries. By rendering the model into multiple 2D images and leveraging a neural network inspired by the Generative Query Network, the method learns to map geometric features into time estimates for predefined production steps with a mean absolute error below 3 s making planning across varied product types easier.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"46 ","pages":"Pages 5-9"},"PeriodicalIF":2.0,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019286","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":"Utilizing Taguchi and ANOVA methods to investigate standard deviation of programmed torque for aluminum 6061-T6 friction stir welding with adaptive torque monitoring and control","authors":"Austin Clark , Ihab Ragai","doi":"10.1016/j.mfglet.2025.08.004","DOIUrl":"10.1016/j.mfglet.2025.08.004","url":null,"abstract":"<div><div>A Taguchi L<sub>9</sub> orthogonal array and Analysis of Variance (ANOVA) test for equal variance were used to determine variation in torque when adaptive torque monitoring and control is used in a Friction Stir Welding (FSW) application on AA6061-T6. Standard deviation was analyzed against the parameters of Programmed Torque (PT) and Feed Rate (FR). PT for the Z-axis motor determined the axial force at the tool during welding. PT values of 35, 40 and 45 Nm and FR of 100, 200 and 300 mm/min were studied in this paper. PT values of 35, 40 and 45 Nm correlated to 7.33, 8.38 and 9.43 kN axial force, respectively. It was found that the optimal parameter set with the lowest variation in torque through the entirety of the weld was conducted with a PT (45 Nm/9.43 kN) and an FR of 100 mm/min. These were the maximum and minimum values for PT and FR, respectively. Higher levels of torque variation occurred with higher FR and lower PT. This study offers insight into the effects process parameters have on torque variation when adaptive torque monitoring and control is used.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"46 ","pages":"Pages 1-4"},"PeriodicalIF":2.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019285","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}
Rafael Guerra Silva , Gustavo Morales Pavez , Luis F. Caminos
{"title":"Reliability challenges in additive manufacturing of continuous fiber-reinforced sandwich structures","authors":"Rafael Guerra Silva , Gustavo Morales Pavez , Luis F. Caminos","doi":"10.1016/j.mfglet.2025.08.002","DOIUrl":"10.1016/j.mfglet.2025.08.002","url":null,"abstract":"<div><div>Additive manufacturing of continuous fiber-reinforced polymer composites faces challenges in achieving consistent flexural strength and stiffness. Additively manufactured sandwich structures with continuous fiber reinforcement were produced in different batches and subjected to flexural tests. The production replicated real-world conditions, including filament spool changes, fiber aging, and time gaps between batches. The mechanical properties were consistent in early batches, but variability in flexural strength and stiffness increased from one batch to the next, reaching deviations up to 60% for glass fiber and 70% for carbon fiber in later batches. Although the dual-head additive manufacturing system protects the polymer filament from humidity during the sequential fiber deposition process and waiting periods, similar provisions are also necessary for the reinforcement filament to minimize or eliminate polymer-fiber interlayer debonding.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"45 ","pages":"Pages 112-115"},"PeriodicalIF":2.0,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144902889","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":"Unsupervised anomaly detection in composite manufacturing using autoencoders and cluster-specific thresholding","authors":"Deepak Kumar, Pragathi Chan Agraharam, Sirish Namilae","doi":"10.1016/j.mfglet.2025.08.001","DOIUrl":"10.1016/j.mfglet.2025.08.001","url":null,"abstract":"<div><div>Artificial intelligence (AI) offers promise for advancing composite manufacturing by enhancing process monitoring, efficiency, and quality while mitigating defects. Nevertheless, AI application for anomaly detection is constrained by limited real-world data and reliance on labeled datasets, necessitating frequent retraining. We propose a novel three-stage anomaly detection framework for composite curing. First, an autoencoder is trained on normal data to extract features. Next, K-means clustering groups similar patterns. Finally, a model combining Mahalanobis distance with an elliptic envelope quantifies deviations using cluster-specific thresholds. Evaluation on autoclave data with a Digital Image Correlation setup yielded an impressive detection accuracy of 99.69% overall.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"45 ","pages":"Pages 101-106"},"PeriodicalIF":2.0,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144902875","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}
Abhishek Kumar , Rajan Singh , Soumen Mandal , Gayatri Paul , Barnali Maji , Manab Mallik
{"title":"Structure-property correlation of alumina pyramidoids fabricated by direct ink writing","authors":"Abhishek Kumar , Rajan Singh , Soumen Mandal , Gayatri Paul , Barnali Maji , Manab Mallik","doi":"10.1016/j.mfglet.2025.08.003","DOIUrl":"10.1016/j.mfglet.2025.08.003","url":null,"abstract":"<div><div>The direct ink writing (DIW) technique prints alumina Pyramidoids. Ink formulation included the usage of pure alumina powder, phenolic resin, and deionized water. Alumina ink with a solid loading of 64 vol% provides suitable rheological properties for 3D printing. The synthesized ink was used for 3D printing of a pyramidoid and sintering at different temperatures (1500 °C–1600 °C). The sample sintered at 1600 °C exhibits a dense microstructure (98 %), good flexural strength (308.34 ± 10 MPa), moderate fracture toughness (4.01 ± 0.4 MPa.m<sup>1/2</sup>), and high hardness (1625 HV).</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"45 ","pages":"Pages 107-111"},"PeriodicalIF":2.0,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144902888","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":"Effect of accounting for powder in thermomechanical simulations for laser powder bed fusion","authors":"Erik Denlinger, Zoe Michaleris , Tyler Nelson","doi":"10.1016/j.mfglet.2025.07.007","DOIUrl":"10.1016/j.mfglet.2025.07.007","url":null,"abstract":"<div><div>This study evaluates the effect of accounting for powder in mechanical predictions for laser powder-bed-fusion by comparing: an inherent-strain based mechanical-only analysis, and thermomechanical simulations where the thermal analysis is conducted with and without powder elements. Results on Inconel 718 parts show that the thermal predictions with powder elements have less than 7 % error while the thermal predictions without powder elements could not capture the trend in measurements. In predicting the peak distortion, the thermomechanical model with powder elements has 21 % lower prediction error than the model without powder elements and 30 % lower prediction error than the mechanical-only analysis.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"45 ","pages":"Pages 93-100"},"PeriodicalIF":2.0,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144863842","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":"Continuous 5-axis routing of syringe deposited conductive traces over topology optimized structures","authors":"Matthew Williams , Ashish Jacob , Guha Manogharan","doi":"10.1016/j.mfglet.2025.06.064","DOIUrl":"10.1016/j.mfglet.2025.06.064","url":null,"abstract":"<div><div>Hybrid additive manufacturing can be troublesome when implementing new processes using existing hardware which makes this research field increasingly prominent. Even after the integration of crucial hardware components necessary for Hybrid AM, there is no suitable procedure capable of efficient toolpath planning of multi-material and multi-functional materials. Topology-optimized design would benefit from a planned process using hybrid manufacturing with simple electronics integration because of the need for optimized functional structures in the aerospace and automotive industries. This research takes multi-axis CNC toolpath strategies for syringe-deposited conductive inks over additively manufactured topology-optimized structures and uses a hybrid AM machine utilizing multiple tools for manufacturing curvilinear traces over the drone frame design. Process parameter configuration for machine hardware and CAM toolpath tolerancing with machine simulations are discussed in this paper. The ability to route conductive traces over topologically optimized structures has been studied and implemented using a 5-axis toolpath planning strategy. The challenge lies in the ability to deposit traces seamlessly across conformal surfaces. The study demonstrates that the manufactured traces were seamless with no breakages, and the measured resistances across the trenches varied between 53.5 and 134.04 Ω.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 540-551"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926540","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":"Mathematical modeling and experimental Investigations on forming force during tube spinning of AA6061☆☆","authors":"Ravi Bhatt , Mallika Bhatt , 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 L<sub>36</sub>). 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, 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}