Pub Date : 2025-08-01DOI: 10.1016/j.mfglet.2025.06.062
Fengfeng Zhou , Xingyu Fu , Nobin Myeong , Siying Chen , Martin Byung-Guk Jun
This paper introduces a cost-effective laser direct writing method for fabricating flexible electrodes. Micron-sized copper powder is combined with polypropylene (pp-Cu) and Loctite® Extreme Glue (glue-Cu) to create a metal-polymer composite feedstock. A low-power carbon dioxide laser is used to process the feedstock to build conductive pathways along the laser ablation toolpath. The laser-processed electrode made from the pp-Cu composite exhibits a resistance of approximately 20MΩ, while the glue-Cu electrode demonstrates a resistance of around 2kΩ. Further, the bent electrode retains its conductivity at a bending radius of 30 mm, demonstrating its potential for use in flexible sensor applications. This approach enables the fabrication of flexible and conformal electronics without requiring protective gases, using a cost-efficient laser system.
{"title":"Cost-efficient laser direct writing of flexible electrodes using metal matrix composites","authors":"Fengfeng Zhou , Xingyu Fu , Nobin Myeong , Siying Chen , Martin Byung-Guk Jun","doi":"10.1016/j.mfglet.2025.06.062","DOIUrl":"10.1016/j.mfglet.2025.06.062","url":null,"abstract":"<div><div>This paper introduces a cost-effective laser direct writing method for fabricating flexible electrodes. Micron-sized copper powder is combined with polypropylene (pp-Cu) and Loctite® Extreme Glue (glue-Cu) to create a metal-polymer composite feedstock. A low-power carbon dioxide laser is used to process the feedstock to build conductive pathways along the laser ablation toolpath. The laser-processed electrode made from the pp-Cu composite exhibits a resistance of approximately 20MΩ, while the glue-Cu electrode demonstrates a resistance of around 2kΩ. Further, the bent electrode retains its conductivity at a bending radius of 30 mm, demonstrating its potential for use in flexible sensor applications. This approach enables the fabrication of flexible and conformal electronics without requiring protective gases, using a cost-efficient laser system.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 524-531"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926538","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}
Pub Date : 2025-08-01DOI: 10.1016/j.mfglet.2025.06.066
Xuepeng Jiang , Li-Hsin Yeh , Mu’ayyad M. Al-Shrida , Jakob D. Hamilton , Beiwen Li , Iris V. Rivero , Andrea N. Camacho-Betancourt , Weijun Shen , Hantang Qin
Direct energy deposition (DED) is an emerging technology for remanufacturing as it enables fusion and deposition of metallic materials into complex geometries with high quality. The melting pool plays a critical role in quality control during the DED process. Ensuring stable melting pool geometry, temperature, and consistency is essential for producing defect-free components. Thermal imaging combined with unsupervised machine learning (ML) offers significant potential for in-situ defect prediction and quality control in the DED process. Moreover, in-situ thermal imaging generates incremental datasets, allowing for the continuous improvement of ML model predictions without the need for additional labelling as the dataset grows. In this work, we investigate the impact of self-organizing map (SOM)-based incremental learning parameters on in-situ thermal monitoring of the DED process using infrared (IR) imaging. Parameters including map size, neighborhood radius, learning rate, number of components, and the decay rate for neighborhood radius and learning rate were evaluated under low and high settings. Their effects on adjustment time for processing new IR images and final model accuracy, measured by quantization error (QE), were analysed. The findings provide a valuable starting point for researchers aiming to optimize SOM-based incremental learning for real-time defect detection using IR imaging of the DED melt pool.
{"title":"Impact of self organizing map based incremental learning parameters on in-situ IR melting pool imaging for direct energy deposition","authors":"Xuepeng Jiang , Li-Hsin Yeh , Mu’ayyad M. Al-Shrida , Jakob D. Hamilton , Beiwen Li , Iris V. Rivero , Andrea N. Camacho-Betancourt , Weijun Shen , Hantang Qin","doi":"10.1016/j.mfglet.2025.06.066","DOIUrl":"10.1016/j.mfglet.2025.06.066","url":null,"abstract":"<div><div>Direct energy deposition (DED) is an emerging technology for remanufacturing as it enables fusion and deposition of metallic materials into complex geometries with high quality. The melting pool plays a critical role in quality control during the DED process. Ensuring stable melting pool geometry, temperature, and consistency is essential for producing defect-free components. Thermal imaging combined with unsupervised machine learning (ML) offers significant potential for in-situ defect prediction and quality control in the DED process. Moreover, in-situ thermal imaging generates incremental datasets, allowing for the continuous improvement of ML model predictions without the need for additional labelling as the dataset grows. In this work, we investigate the impact of self-organizing map (SOM)-based incremental learning parameters on in-situ thermal monitoring of the DED process using infrared (IR) imaging. Parameters including map size, neighborhood radius, learning rate, number of components, and the decay rate for neighborhood radius and learning rate were evaluated under low and high settings. Their effects on adjustment time for processing new IR images and final model accuracy, measured by quantization error (QE), were analysed. The findings provide a valuable starting point for researchers aiming to optimize SOM-based incremental learning for real-time defect detection using IR imaging of the DED melt pool.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 559-565"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926542","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}
Pub Date : 2025-08-01DOI: 10.1016/j.mfglet.2025.06.068
Ross Zameroski , Michael Gomez , Tony Schmitz
This paper describes drill wear monitoring using the combination of a constrained-motion drilling dynamometer (CMDD) and aluminum witness sample. The drill wear state is assessed using the increase in torque and thrust force measured by the CMDD while drilling an aluminum witness sample. The drill is worn using the selected workpiece material and holes are intermittently drilled in the aluminum witness sample to determine the wear state. The hypothesis is that there is a direct link between the wear state and witness sample torque and thrust force increase, independent of the workpiece material. Therefore, a single model that relates tool wear to torque and thrust force increase can be calibrated and implemented for other drills and materials. The witness sample approach demonstrates good agreement between the predicted increase in force magnitude and the experimental results. A mechanistic drilling torque and thrust model is also described and a linear regression approach is defined to obtain the coefficients. The growth in these coefficients with drill wear state is examined and it is observed that one coefficient was highly sensitive to the wear state.
{"title":"Drill wear monitoring using a constrained-motion drilling dynamometer and aluminum witness sample","authors":"Ross Zameroski , Michael Gomez , Tony Schmitz","doi":"10.1016/j.mfglet.2025.06.068","DOIUrl":"10.1016/j.mfglet.2025.06.068","url":null,"abstract":"<div><div>This paper describes drill wear monitoring using the combination of a constrained-motion drilling dynamometer (CMDD) and aluminum witness sample. The drill wear state is assessed using the increase in torque and thrust force measured by the CMDD while drilling an aluminum witness sample. The drill is worn using the selected workpiece material and holes are intermittently drilled in the aluminum witness sample to determine the wear state. The hypothesis is that there is a direct link between the wear state and witness sample torque and thrust force increase, independent of the workpiece material. Therefore, a single model that relates tool wear to torque and thrust force increase can be calibrated and implemented for other drills and materials. The witness sample approach demonstrates good agreement between the predicted increase in force magnitude and the experimental results. A mechanistic drilling torque and thrust model is also described and a linear regression approach is defined to obtain the coefficients. The growth in these coefficients with drill wear state is examined and it is observed that one coefficient was highly sensitive to the wear state.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 576-587"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926544","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}
Pub Date : 2025-08-01DOI: 10.1016/j.mfglet.2025.06.071
Sujan Khadka , Rizwan Abdul Rahman Rashid , John Navarro-Devia , Angelo Papageorgiou , Guy Stephens , Suresh Palanisamy
Optimizing cutting parameters is essential for reducing tool wear, extending tool life, and ensuring efficient machining processes. This can be achieved using different tool life models, such as Taylor’s tool life model or Extended Taylor’s tool life models or Colding’s tool life model, which can accurately optimize cutting parameters and enable informed decision-making for process improvements. Although Taylor’s tool life model is widely used in both industrial and academic settings, it is not regarded as the most precise model. Therefore, in this study, Taylor’s tool life model along with its extended versions are compared to Colding’s tool life model to assess their respective accuracies in predicting tool wear and optimizing machining parameters while dry machining two different workpiece materials: K1045 and Mild Steel. The Extended Taylor’s equation incorporating equivalent chip thickness demonstrated superior accuracy in predicting tool wear for K1045, with an error percentage of 6.13%. In contrast, Colding’s model exhibited the lowest error percentage (2.88%) for Mild Steel. In comparison, Taylor’s conventional tool life model showed higher deviations in prediction accuracy for both materials, highlighting its limitations in estimating tool wear accurately. The results suggest that incorporating additional machining parameters, such as equivalent chip thickness in the Extended Taylor’s model, enhances predictive accuracy, particularly for harder materials like K1045. Conversely, Colding’s model, which considers a broader range of machining factors, performed better in predicting tool wear for Mild Steel. These findings indicate that no single model consistently outperforms the others across different materials. The Extended Taylor’s model with equivalent chip thickness provided the most accurate predictions for K1045, whereas Colding’s model offered the best accuracy for Mild Steel, as reflected in their respective error percentages. This highlights the importance of selecting a tool life model based on material properties and machining conditions to ensure optimal performance. The study provides valuable insights for machining industries, enabling more informed decision-making when optimizing cutting parameters, reducing tool wear, and improving process efficiency. Future research could explore the integration of empirical models with data-driven approaches, such as AI-based predictive modelling, to further enhance the accuracy and adaptability of tool life estimation in diverse machining environments.
{"title":"Comparative assessment of tool life models for solid end mills in machining applications","authors":"Sujan Khadka , Rizwan Abdul Rahman Rashid , John Navarro-Devia , Angelo Papageorgiou , Guy Stephens , Suresh Palanisamy","doi":"10.1016/j.mfglet.2025.06.071","DOIUrl":"10.1016/j.mfglet.2025.06.071","url":null,"abstract":"<div><div>Optimizing cutting parameters is essential for reducing tool wear, extending tool life, and ensuring efficient machining processes. This can be achieved using different tool life models, such as Taylor’s tool life model or Extended Taylor’s tool life models or Colding’s tool life model, which can accurately optimize cutting parameters and enable informed decision-making for process improvements. Although Taylor’s tool life model is widely used in both industrial and academic settings, it is not regarded as the most precise model. Therefore, in this study, Taylor’s tool life model along with its extended versions are compared to Colding’s tool life model to assess their respective accuracies in predicting tool wear and optimizing machining parameters while dry machining two different workpiece materials: K1045 and Mild Steel. The Extended Taylor’s equation incorporating equivalent chip thickness demonstrated superior accuracy in predicting tool wear for K1045, with an error percentage of 6.13%. In contrast, Colding’s model exhibited the lowest error percentage (2.88%) for Mild Steel. In comparison, Taylor’s conventional tool life model showed higher deviations in prediction accuracy for both materials, highlighting its limitations in estimating tool wear accurately. The results suggest that incorporating additional machining parameters, such as equivalent chip thickness in the Extended Taylor’s model, enhances predictive accuracy, particularly for harder materials like K1045. Conversely, Colding’s model, which considers a broader range of machining factors, performed better in predicting tool wear for Mild Steel. These findings indicate that no single model consistently outperforms the others across different materials. The Extended Taylor’s model with equivalent chip thickness provided the most accurate predictions for K1045, whereas Colding’s model offered the best accuracy for Mild Steel, as reflected in their respective error percentages. This highlights the importance of selecting a tool life model based on material properties and machining conditions to ensure optimal performance. The study provides valuable insights for machining industries, enabling more informed decision-making when optimizing cutting parameters, reducing tool wear, and improving process efficiency. Future research could explore the integration of empirical models with data-driven approaches, such as AI-based predictive modelling, to further enhance the accuracy and adaptability of tool life estimation in diverse machining environments.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 602-609"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926547","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}
Pub Date : 2025-08-01DOI: 10.1016/j.mfglet.2025.06.038
Kazi Owais Ahmed, Masakazu Soshi
Additive and conventional subtractive hybrid manufacturing has emerged to take advantage of the capabilities of both processes. The confluence of several factors poses pros and cons for manufacturers seeking the most efficient process selection for manufacturing complex parts. The primary difficulty lies in making well-informed decisions incorporating additive and subtractive processes. Machine users employ heuristic judgments to make process selections, often relying on time-consuming trial-and-error methods that produce waste. The proposed research aims to develop an algorithm that can automatically determine the most efficient manufacturing strategy, i.e., purely additive, purely subtractive, or hybrid to make a part, integrating subtractive machining, and laser directed energy deposition (DED). The methodology proposed is that given a boundary-representation model of a part, the algorithm sections and splits the geometry into its sub-features based on various splitting methods. The sectioning of geometry into its sub-features is needed to determine which manufacturing process should be used to make that particular sub-feature, utilizing the hybrid capability of the machine. The machinability of the entire model and each sub-feature is automatically determined using the directional vector approach relative to the z-axis of the machine. The algorithm then performs the efficiency analysis on each sub-feature regarding productivity, material cost, and energy cost. It then recommends the most efficient manufacturing process for the entire part geometry. The algorithm also allows users to input efficiency constants to assign weight to parameters. Subsequently, a user-preferred manufacturing process is then suggested as the output. The software is capable to store databases for selective machines and their parameters, which can be overwritten by the user. The software is developed using Microsoft Foundation Classes (MFC) Visual Studio application in C++, incorporating Siemens Parasolid geometric modeling kernel, Hoops3D Visualize, and Exchange application programming interfaces. The research is still in progress. Future work will expand the algorithm to enable automated sectioning. The proposed equations governing productivity, material cost, and energy costs will be validated through experimentation on the DMG Mori Lasertec 65 DED Hybrid machine.
添加剂和传统减法混合制造已经出现，以利用这两种工艺的能力。对于寻求制造复杂零件的最有效的工艺选择的制造商来说，几个因素的汇合构成了有利和不利的因素。主要的困难在于如何在充分知情的情况下做出决定，其中包括加法和减法过程。机器用户采用启发式判断来选择工艺，通常依赖耗时的试错方法，产生浪费。提出的研究旨在开发一种算法，可以自动确定最有效的制造策略，即纯加法，纯减法或混合制造零件，集成减法加工和激光定向能沉积（DED）。提出的方法是，给定零件的边界表示模型，该算法基于各种分割方法将几何形状分割成其子特征。需要将几何形状分割成其子特征，以确定应使用哪种制造工艺来制造特定的子特征，利用机器的混合能力。使用相对于机器z轴的方向矢量方法自动确定整个模型和每个子特征的可加工性。然后，该算法对生产率、材料成本和能源成本等各个子特征进行效率分析。然后为整个零件几何形状推荐最有效的制造工艺。该算法还允许用户输入效率常数来为参数分配权重。随后，建议用户首选的制造过程作为输出。该软件能够存储选择性机器及其参数的数据库，这些数据库可以由用户覆盖。该软件是使用Microsoft Foundation Classes (MFC) Visual Studio应用程序在c++中开发的，结合了西门子Parasolid几何建模内核、Hoops3D可视化和Exchange应用程序编程接口。这项研究仍在进行中。未来的工作将扩展算法以实现自动切片。提出的控制生产率、材料成本和能源成本的方程将通过DMG Mori Lasertec 65 DED混合动力机器的实验进行验证。
{"title":"Algorithmic optimization of process selection for additive-subtractive hybrid manufacturing","authors":"Kazi Owais Ahmed, Masakazu Soshi","doi":"10.1016/j.mfglet.2025.06.038","DOIUrl":"10.1016/j.mfglet.2025.06.038","url":null,"abstract":"<div><div>Additive and conventional subtractive hybrid manufacturing has emerged to take advantage of the capabilities of both processes. The confluence of several factors poses pros and cons for manufacturers seeking the most efficient process selection for manufacturing complex parts. The primary difficulty lies in making well-informed decisions incorporating additive and subtractive processes. Machine users employ heuristic judgments to make process selections, often relying on time-consuming trial-and-error methods that produce waste. The proposed research aims to develop an algorithm that can automatically determine the most efficient manufacturing strategy, i.e., purely additive, purely subtractive, or hybrid to make a part, integrating subtractive machining, and laser directed energy deposition (DED). The methodology proposed is that given a boundary-representation model of a part, the algorithm sections and splits the geometry into its sub-features based on various splitting methods. The sectioning of geometry into its sub-features is needed to determine which manufacturing process should be used to make that particular sub-feature, utilizing the hybrid capability of the machine. The machinability of the entire model and each sub-feature is automatically determined using the directional vector approach relative to the z-axis of the machine. The algorithm then performs the efficiency analysis on each sub-feature regarding productivity, material cost, and energy cost. It then recommends the most efficient manufacturing process for the entire part geometry. The algorithm also allows users to input efficiency constants to assign weight to parameters. Subsequently, a user-preferred manufacturing process is then suggested as the output. The software is capable to store databases for selective machines and their parameters, which can be overwritten by the user. The software is developed using Microsoft Foundation Classes (MFC) Visual Studio application in C++, incorporating Siemens Parasolid geometric modeling kernel, Hoops3D Visualize, and Exchange application programming interfaces. The research is still in progress. Future work will expand the algorithm to enable automated sectioning. The proposed equations governing productivity, material cost, and energy costs will be validated through experimentation on the DMG Mori Lasertec 65 DED Hybrid machine.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 314-324"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926618","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}
The scissor mechanism provides a high motion multiplication capacity, as a small displacement at the link level can generate a large displacement at the mechanism level, making it an ideal choice for lifting applications, such as hydraulics lifts, scissor jacks, and industrial machinery. Although the mechanism can provide a uniform extension, it is limited to a single axis, giving a single degree of freedom (DoF). This study presents a novel scissor kinematics-based parallel tri-axial motion system capable of 3 DoF, with one translation, 1 T (Z), and two rotations, 2R (A & B). The enhanced range of motion is achieved by integrating a double universal joint with the standard scissor mechanism. The addition of the universal joints allows the end effector (EE) rotation in two directions. While linear travel is determined by the scissor link lengths (which can be increased by incorporating multiple scissor rings), the rotational tilt is determined by the dimensions of the universal joint. The forward kinematics (FK) is also presented to determine the pose of the EE (Z, A, B) for a given set of scissor lengths (z1, z2, z3). A proof-of-concept (PoC) is fabricated using custom-made 3D-printed parts using an FDM machine. Fundamental motion range analysis in a computational simulation environment showed that the system could have a vertical translation beyond 100 mm and a tile beyond 60° in either direction, making it eligible for multi-axis platforms for space posture adjustment and processes like Additive Manufacturing (AM).
{"title":"Development of a uniaxial scissor unit into a tri-axis motion system via double universal joints","authors":"Dixita A. Yadav , Yash Gopal Mittal , Swapnil Gujarathi , K.P. Karunakaran","doi":"10.1016/j.mfglet.2025.06.012","DOIUrl":"10.1016/j.mfglet.2025.06.012","url":null,"abstract":"<div><div>The scissor mechanism provides a high motion multiplication capacity, as a small displacement at the link level can generate a large displacement at the mechanism level, making it an ideal choice for lifting applications, such as hydraulics lifts, scissor jacks, and industrial machinery. Although the mechanism can provide a uniform extension, it is limited to a single axis, giving a single <em>degree of freedom</em> (DoF). This study presents a novel scissor kinematics-based parallel tri-axial motion system capable of 3 DoF, with one translation, 1 T (<em>Z</em>), and two rotations, 2R (<em>A</em> & <em>B</em>). The enhanced range of motion is achieved by integrating a double universal joint with the standard scissor mechanism. The addition of the universal joints allows the <em>end effector</em> (EE) rotation in two directions. While linear travel is determined by the scissor link lengths (which can be increased by incorporating multiple scissor rings), the rotational tilt is determined by the dimensions of the universal joint. The <em>forward kinematics</em> (FK) is also presented to determine the <em>pose</em> of the EE (<em>Z</em>, <em>A</em>, <em>B</em>) for a given set of scissor lengths (<em>z<sub>1</sub></em>, <em>z<sub>2</sub></em>, <em>z<sub>3</sub></em>). A <em>proof-of-concept</em> (PoC) is fabricated using custom-made 3D-printed parts using an FDM machine. Fundamental motion range analysis in a computational simulation environment showed that the system could have a vertical translation beyond 100 mm and a tile beyond 60° in either direction, making it eligible for multi-axis platforms for space posture adjustment and processes like <em>Additive Manufacturing</em> (AM).</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 80-90"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926663","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}
Pub Date : 2025-08-01DOI: 10.1016/j.mfglet.2025.06.092
Jiaqi Yang, Dehao Liu
This study examines the impact of processing parameters on the joining strength and interfacial characteristics of 316L stainless steel-copper (Cu) interfaces fabricated using laser powder bed fusion. The integration of 316L and copper is critical for engineering applications that require a combination of mechanical strength, thermal conductivity, and corrosion resistance. Systematic experiments are conducted to evaluate the effects of varying laser power and scanning speed on interfacial properties. The 316L-Cu interfaces are characterized using optical microscopy, energy-dispersive X-ray spectroscopy (EDS), and microhardness testing to assess morphological and elemental features. A lap shear test was conducted to evaluate the mechanical strength of the joint, revealing an ultimate shear strength of 42.95 MPa for the sample with the optimal printing parameters in this work. The results indicate that increased volumetric energy density enhances interfacial bonding by promoting elemental diffusion and reducing porosity. However, challenges such as residual stresses and thermal expansion mismatch still affect interface quality. This research provides insights into the optimization of laser powder bed fusion parameters to improve the mechanical performance and reliability of multi-material components, advancing their applicability in diverse industrial sectors.
{"title":"Effects of processing parameters on joining strength of 316L-Cu interface in multi-materials laser powder bed fusion","authors":"Jiaqi Yang, Dehao Liu","doi":"10.1016/j.mfglet.2025.06.092","DOIUrl":"10.1016/j.mfglet.2025.06.092","url":null,"abstract":"<div><div>This study examines the impact of processing parameters on the joining strength and interfacial characteristics of 316L stainless steel-copper (Cu) interfaces fabricated using laser powder bed fusion. The integration of 316L and copper is critical for engineering applications that require a combination of mechanical strength, thermal conductivity, and corrosion resistance. Systematic experiments are conducted to evaluate the effects of varying laser power and scanning speed on interfacial properties. The 316L-Cu interfaces are characterized using optical microscopy, energy-dispersive X-ray spectroscopy (EDS), and microhardness testing to assess morphological and elemental features. A lap shear test was conducted to evaluate the mechanical strength of the joint, revealing an ultimate shear strength of 42.95 MPa for the sample with the optimal printing parameters in this work. The results indicate that increased volumetric energy density enhances interfacial bonding by promoting elemental diffusion and reducing porosity. However, challenges such as residual stresses and thermal expansion mismatch still affect interface quality. This research provides insights into the optimization of laser powder bed fusion parameters to improve the mechanical performance and reliability of multi-material components, advancing their applicability in diverse industrial sectors.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 784-791"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926683","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}
Pub Date : 2025-08-01DOI: 10.1016/j.mfglet.2025.06.035
Yanze Chen, Jingyan Dong
Recently, flexible and wearable electronics have received increasing attention with many emerging applications. Compared with traditional electronic devices on the rigid substrates, flexible electronics provide great potential in portable and wearable applications. PEDOT: PSS, as a conductive polymer, has high mechanical flexibility, making it suitable for the fabrication of wearable and deformable electronic devices such as organic transistors, photovoltaics, and wearable sensors. This intrinsic flexibility is crucial in enabling next-generation flexible electronics that are ultrathin, transparent, and wearable. However, the electrical conductivity of pristine PEDOT: PSS is often below 1 S/cm, which is insufficient for many electronic devices such as organic photovoltaics and organic transistors. In this work, we synthesized PEDOT: PSS/ Graphene composite to enhance the electrical performance of PEDOT: PSS. To achieve low-cost and scalable fabrication, we explored a screen-printing process to print the conductive PEDOT: PSS/ Graphene patterns onto various substrates. The PEDOT: PSS/ Graphene composite ink was developed for the screen-printing process with the ink viscosity and flowability adjusted by different ratio of polyethylene oxide (PEO) additive. Different weight ratios of graphene and PEO were studied to achieve stable and printable ink for the device fabrication. The effect of the ink composition on the pattern resolution and electric performance was experimentally characterized to obtain the trade-off between ink printability, electrical properties and printing resolution. Using the synthesized PEDOT: PSS/graphene ink, the printed circuits demonstrated excellent flexibility in the bending tests. The circuits provided stable electrical response under bending and twisting deformation and under hundreds of bending cycles, which provide a promising approach toward scalable fabrication of flexible wearable electronics.
{"title":"Fabrication of flexible electronics by screen printing with PEDOT: PSS/graphene composite ink","authors":"Yanze Chen, Jingyan Dong","doi":"10.1016/j.mfglet.2025.06.035","DOIUrl":"10.1016/j.mfglet.2025.06.035","url":null,"abstract":"<div><div>Recently, flexible and wearable electronics have received increasing attention with many emerging applications. Compared with traditional electronic devices on the rigid substrates, flexible electronics provide great potential in portable and wearable applications. PEDOT: PSS, as a conductive polymer, has high mechanical flexibility, making it suitable for the fabrication of wearable and deformable electronic devices such as organic transistors, photovoltaics, and wearable sensors. This intrinsic flexibility is crucial in enabling next-generation flexible electronics that are ultrathin, transparent, and wearable. However, the electrical conductivity of pristine PEDOT: PSS is often below 1 S/cm, which is insufficient for many electronic devices such as organic photovoltaics and organic transistors. In this work, we synthesized PEDOT: PSS/ Graphene composite to enhance the electrical performance of PEDOT: PSS. To achieve low-cost and scalable fabrication, we explored a screen-printing process to print the conductive PEDOT: PSS/ Graphene patterns onto various substrates. The PEDOT: PSS/ Graphene composite ink was developed for the screen-printing process with the ink viscosity and flowability adjusted by different ratio of polyethylene oxide (PEO) additive. Different weight ratios of graphene and PEO were studied to achieve stable and printable ink for the device fabrication. The effect of the ink composition on the pattern resolution and electric performance was experimentally characterized to obtain the trade-off between ink printability, electrical properties and printing resolution. Using the synthesized PEDOT: PSS/graphene ink, the printed circuits demonstrated excellent flexibility in the bending tests. The circuits provided stable electrical response under bending and twisting deformation and under hundreds of bending cycles, which provide a promising approach toward scalable fabrication of flexible wearable electronics.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 287-293"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926695","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}
Pub Date : 2025-08-01DOI: 10.1016/j.mfglet.2025.06.028
Chengjun Jin , Young Kyu Kim , Hyungjum Jang , Xun Lu , Seok-min Kim
Wire grid polarizers (WGPs) are essential in photonic applications such as laser optical systems, imaging systems, and displays due to their high polarization efficiency and durability. Conventional WGPs fabricated on polymer substrates face limitations in optical transmittance, mechanical stability, and thermal durability. This study introduces a cost-effective and scalable method for fabricating WGPs on glass nanograting structures using Vitreous Carbon (VC) molds and oblique angle deposition (OAD) of aluminum. The proposed process addresses the shortcomings of polymer-based WGPs while enabling large-area production. The VC mold was fabricated through a multi-step replication and carbonization process. A silicon master with nanograting features (500 nm pitch, 250 nm height, 50 % duty cycle) was prepared using reactive ion etching and KrF laser photolithography. A polymer template was replicated via UV imprinting, and a furan precursor was replicated from the polymer template through a thermal curing process. A VC mold with a nanograting cavity (400 nm pitch, 140 nm height) was obtained by a carbonization process at 1000 °C in a nitrogen-purged environment. Glass nanogratings were then formed by molding soda-lime glass at 730 °C under 1.84 MPa, with SEM analysis confirming successful nanoscale replication. An aluminum layer was deposited on the glass nanograting using the OAD process, with optimized flux angles (<70°) to minimize sidewall deposition and prevent isolated nanorods. The fabricated WGP exhibited a transverse-magnetic wave transmittance of over 40 % and an extinction ratio of ∼40 at 600 nm, which is similar to the simulation results for the glass WGP model with slight sidewall deposition. Although the pitch of the fabricated WGPs were not suitable for visible light applications, this study demonstrates the feasibility of WGPs with directly molded glass nanograting structures, offering advantages in cost, scalability, and durability. The proposed method is promising for advancing photonic applications.
{"title":"Fabrication of wire-grid polarizer with glass molded nanograting structure","authors":"Chengjun Jin , Young Kyu Kim , Hyungjum Jang , Xun Lu , Seok-min Kim","doi":"10.1016/j.mfglet.2025.06.028","DOIUrl":"10.1016/j.mfglet.2025.06.028","url":null,"abstract":"<div><div>Wire grid polarizers (WGPs) are essential in photonic applications such as laser optical systems, imaging systems, and displays due to their high polarization efficiency and durability. Conventional WGPs fabricated on polymer substrates face limitations in optical transmittance, mechanical stability, and thermal durability. This study introduces a cost-effective and scalable method for fabricating WGPs on glass nanograting structures using Vitreous Carbon (VC) molds and oblique angle deposition (OAD) of aluminum. The proposed process addresses the shortcomings of polymer-based WGPs while enabling large-area production. The VC mold was fabricated through a multi-step replication and carbonization process. A silicon master with nanograting features (500 nm pitch, 250 nm height, 50 % duty cycle) was prepared using reactive ion etching and KrF laser photolithography. A polymer template was replicated via UV imprinting, and a furan precursor was replicated from the polymer template through a thermal curing process. A VC mold with a nanograting cavity (400 nm pitch, 140 nm height) was obtained by a carbonization process at 1000 °C in a nitrogen-purged environment. Glass nanogratings were then formed by molding soda-lime glass at 730 °C under 1.84 MPa, with SEM analysis confirming successful nanoscale replication. An aluminum layer was deposited on the glass nanograting using the OAD process, with optimized flux angles (<70°) to minimize sidewall deposition and prevent isolated nanorods. The fabricated WGP exhibited a transverse-magnetic wave transmittance of over 40 % and an extinction ratio of ∼40 at 600 nm, which is similar to the simulation results for the glass WGP model with slight sidewall deposition. Although the pitch of the fabricated WGPs were not suitable for visible light applications, this study demonstrates the feasibility of WGPs with directly molded glass nanograting structures, offering advantages in cost, scalability, and durability. The proposed method is promising for advancing photonic applications.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 233-236"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926728","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}
Pub Date : 2025-08-01DOI: 10.1016/j.mfglet.2025.06.090
Bo Zhao , Kateland Hutt , Zilong Zhao , Pai Wang , Hitomi Yamaguchi , Shuaihang Pan
This study investigates the influence of scanning speed on surface roughness and its impact on the corrosion resistance of IN718 fabricated using Laser Powder Bed Fusion (LPBF). Three scanning speeds (760 mm/s, 800 mm/s, and 840 mm/s) were applied, and the surface roughness, microhardness, and electrochemical properties were analyzed. The results reveal a significant discrepancy between the optimal scanning speed for achieving superior mechanical properties and that required for maximizing the LPBF-fabricated alloy’s corrosion resistance performance. More specifically, this study highlights the critical role of scanning speed on the corrosion behavior of LPBF IN718, providing practical guidance and insights for achieving the simultaneous enhancement of both mechanical properties and corrosion resistance by printing parameter optimization in LPBF-fabricated materials.
{"title":"Scanning speed-induced surface roughness change and its impact on the corrosion resistance of IN718 fabricated by laser powder bed fusion","authors":"Bo Zhao , Kateland Hutt , Zilong Zhao , Pai Wang , Hitomi Yamaguchi , Shuaihang Pan","doi":"10.1016/j.mfglet.2025.06.090","DOIUrl":"10.1016/j.mfglet.2025.06.090","url":null,"abstract":"<div><div>This study investigates the influence of scanning speed on surface roughness and its impact on the corrosion resistance of IN718 fabricated using Laser Powder Bed Fusion (LPBF). Three scanning speeds (760 mm/s, 800 mm/s, and 840 mm/s) were applied, and the surface roughness, microhardness, and electrochemical properties were analyzed. The results reveal a significant discrepancy between the optimal scanning speed for achieving superior mechanical properties and that required for maximizing the LPBF-fabricated alloy’s corrosion resistance performance. More specifically, this study highlights the critical role of scanning speed on the corrosion behavior of LPBF IN718, providing practical guidance and insights for achieving the simultaneous enhancement of both mechanical properties and corrosion resistance by printing parameter optimization in LPBF-fabricated materials.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"44 ","pages":"Pages 770-777"},"PeriodicalIF":2.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926752","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}
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