Journal of Manufacturing and Materials Processing

28 pages, 1673 KiB

Open AccessReview

Advancement of 3D Bioprinting Towards 4D Bioprinting for Sustained Drug Delivery and Tissue Engineering from Biopolymers

by Maryam Aftab, Sania Ikram, Muneeb Ullah, Shahid Ullah Khan, Abdul Wahab and Muhammad Naeem

J. Manuf. Mater. Process. 2025, 9(8), 285; https://doi.org/10.3390/jmmp9080285 - 21 Aug 2025

Abstract

The transition from three-dimensional (3D) to four-dimensional (4D)-bioprinting marks a significant advancement in tissue engineering and drug delivery. 4D-bioprinting offers the potential to more accurately mimic the adaptive qualities of living tissues due to its dynamic flexibility. Structures created with 4D-bioprinting can change [...] Read more.

The transition from three-dimensional (3D) to four-dimensional (4D)-bioprinting marks a significant advancement in tissue engineering and drug delivery. 4D-bioprinting offers the potential to more accurately mimic the adaptive qualities of living tissues due to its dynamic flexibility. Structures created with 4D-bioprinting can change shape in response to internal and external stimuli. This article reviews the background, key concepts, techniques, and applications of 4D-bioprinting, focusing on its role in tissue scaffolding and drug delivery. We discuss the limitations of traditional 3D-bioprinting in providing customized and sustained medication release. Shape memory polymers and hydrogels are examples of new responsive materials enabled by 4D-bioprinting that can enhance drug administration. Additionally, we provide a thorough analysis of various biopolymers used in drug delivery systems, including cellulose, collagen, alginate, and chitosan. The use of biopolymers in 4D-printing significantly increases material responsiveness, allowing them to react to stimuli such as temperature, light, and humidity. This capability enables complex designs with programmable shape and function changes. The expansion and contraction of hydrogels in response to temperature changes offer a practical method for controlled drug release. 4D-bioprinting has the potential to address significant challenges in tissue regeneration and medication administration, spurring ongoing research in this technology. By providing precise control over cell positioning and biomaterial integration, traditional 3D-bioprinting has evolved into 4D-bioprinting, enhancing the development of tissue constructs. 4D-bioprinting represents a paradigm shift in tissue engineering and biomaterials, offering enhanced possibilities for creating responsive, adaptive structures that address clinical needs. Researchers can leverage the unique properties of biopolymers within the 4D-printing framework to develop innovative approaches for tissue regeneration and drug delivery, leading to advanced treatments in regenerative medicine. One potential future application is in vivo tissue regeneration using bioprinted structures that can enhance the body’s natural healing capabilities. Full article

(This article belongs to the Special Issue Advances in 3D Printing Technologies: Materials, Processes, and Applications)

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56 pages, 25615 KiB

Open AccessReview

Recent Progress and Scientific Challenges in Wire-Arc Additive Manufacturing of Metallic Multi-Material Structures

by Sainand Jadhav, Sambhaji Kusekar, Akash Belure, Satyavan Digole, Abhijeet Mali, Muralimohan Cheepu, Manoj Mugale, Suhas Alkunte and Duckbong Kim

J. Manuf. Mater. Process. 2025, 9(8), 284; https://doi.org/10.3390/jmmp9080284 (registering DOI) - 21 Aug 2025

Abstract

Metallic multi-material structures are heterogeneous structures characterized by changing composition, microstructures, and site-specific characteristics, advantageous for numerous applications where multifunctionality is desired. Metallic multi-material structures are known as bimetallic structures (BSs), which are functionally graded materials (FGMs). In recent years, wire-arc additive manufacturing [...] Read more.

Metallic multi-material structures are heterogeneous structures characterized by changing composition, microstructures, and site-specific characteristics, advantageous for numerous applications where multifunctionality is desired. Metallic multi-material structures are known as bimetallic structures (BSs), which are functionally graded materials (FGMs). In recent years, wire-arc additive manufacturing (WAAM) advanced as a promising additive manufacturing process to realize the fabrication of these structures due to its high deposition rate, cost-effectiveness, and material utilization efficiency. This review presents a comprehensive overview of the recent progress, processing strategies, and scientific challenges in WAAM of multi-material structures. The paper begins with an introduction to multi-material structures, followed by a bibliometric analysis of the current research landscape. Conventional and additive manufacturing fabrication approaches are presented. The review highlights key developments in processing strategies and critically evaluates research studies on WAAM of BS and FGMs. Major scientific challenges, including porosity, lack of fusion, residual stresses, cracking, material compatibility, and brittle intermetallic phase formation, are critically analyzed. Additionally, modeling, simulation, and process automation issues are discussed as barriers to industrial-scale implementation. The paper concludes with an outlook on future research directions to address existing challenges and accelerate the adoption of WAAM for complex multi-material components. Full article

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20 pages, 6471 KiB

Open AccessArticle

Analysis of the Suitability of Additive Technologies for the Production of Stainless Steel Components

by Michal Sajgalik, Miroslav Matus, Peter Spuro, Richard Joch, Andrej Czan and Libor Beranek

J. Manuf. Mater. Process. 2025, 9(8), 283; https://doi.org/10.3390/jmmp9080283 - 18 Aug 2025

Abstract

This study presents a comparative analysis of three metal additive manufacturing processes: selective laser melting (SLM), also known as powder bed fusion (PBF); binder jetting (BJ); and atomic diffusion additive manufacturing (ADAM), a form of Material Extrusion (MEX). It focuses on the geometric [...] Read more.

This study presents a comparative analysis of three metal additive manufacturing processes: selective laser melting (SLM), also known as powder bed fusion (PBF); binder jetting (BJ); and atomic diffusion additive manufacturing (ADAM), a form of Material Extrusion (MEX). It focuses on the geometric and dimensional accuracy of ADAM-fabricated 17-4 PH stainless steel components, while AISI 316L stainless steel is the benchmark material for BJ and SLM technologies. In addition to dimension and geometry inspections, this study also measures the distribution of residual stresses and microstructural features of the printed components. Residual stresses were determined quantitatively to identify the internal state of stress developed because of each processing technology. The results reveal significant differences in dimensional accuracy, residual stress profiles, surface roughness, and microstructural characteristics among the three additive manufacturing technologies. The observed trends and correlations provide valuable guidance for selecting the most appropriate additive manufacturing technique based on required accuracy, mechanical properties, and product complexity. Full article

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16 pages, 5567 KiB

Open AccessArticle

Long-Term Impact of Sterilization Cycles on the Surface and Mechanical Integrity of Medical-Grade Silicone

by Mohsen Barmouz, Bahman Azarhoushang, Wolfram Kintzel and Volker Bucher

J. Manuf. Mater. Process. 2025, 9(8), 282; https://doi.org/10.3390/jmmp9080282 - 16 Aug 2025

Abstract

This study investigates the effects of repeated cleaning, disinfection, and sterilization cycles on the surface and mechanical properties of medical-grade silicone, including both pure silicone and silicone–steel composite samples. Given the critical importance of sterilization for infection control, understanding its long-term impact on [...] Read more.

This study investigates the effects of repeated cleaning, disinfection, and sterilization cycles on the surface and mechanical properties of medical-grade silicone, including both pure silicone and silicone–steel composite samples. Given the critical importance of sterilization for infection control, understanding its long-term impact on material performance is essential. Samples were subjected to up to 1000 cycles, with evaluations at the initial state and after 200, 500, and 1000 cycles. The contact angle initially decreased from 117.1° to 104.0° after 200 cycles, then gradually increased, approaching the original value after 1000 cycles, likely due to the removal of degraded surface layers. Hardness measurements showed a steady increase at each stage, with an approximate 5% rise per cycle group. Notch growth testing revealed a sixfold increase in crack length after 200 cycles and a twofold increase between 500 and 1000 cycles, indicating substantial loss of mechanical integrity. Optical microscopy of the silicone–steel interface revealed progressive deterioration, including crack formation, erosion, and partial debonding, particularly after 1000 cycles. These findings highlight the material and interfacial vulnerabilities of silicone-based medical devices under prolonged sterilization protocols. Full article

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18 pages, 4892 KiB

Open AccessArticle

A Real-Time Anomaly Detection Model of Nomex Honeycomb Composites Disc Tool

by Xuanlin Wang, Peihao Tang, Jie Xu, Xueping Liu and Peng Mou

J. Manuf. Mater. Process. 2025, 9(8), 281; https://doi.org/10.3390/jmmp9080281 - 15 Aug 2025

Abstract

Nomex honeycomb composites (NHCs) are highly sensitive to the abnormal wear state of disc tools during cutting, leading to poor product quality. This paper proposes a real-time anomaly detection method combining a novel CNN–GRU–Attention (CGA) deep learning model with an Exponentially Weighted Moving [...] Read more.

Nomex honeycomb composites (NHCs) are highly sensitive to the abnormal wear state of disc tools during cutting, leading to poor product quality. This paper proposes a real-time anomaly detection method combining a novel CNN–GRU–Attention (CGA) deep learning model with an Exponentially Weighted Moving Average (EWMA) control chart to monitor sensor data from the disc tool. The CGA model integrates an improved CNN layer to extract multidimensional local features, a GRU layer to capture long-term temporal dependencies, and a multi-head attention mechanism to highlight key information and reduce error accumulation. Trained solely on normal operation data to address the scarcity of abnormal samples, the model predicts cutting force time series with an RMSE of 0.5012, MAE of 0.3942, and R² of 0.9128, outperforming mainstream time series data prediction models. The EWMA control chart applied to the prediction residuals detects abnormal tool wear trends promptly and accurately. Experiments on real NHC cutting datasets demonstrate that the proposed method effectively identifies abnormal machining conditions, enabling timely tool replacement and significantly enhancing product quality assurance. Full article

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25 pages, 3250 KiB

Open AccessArticle

A Thermoelastic Plate Model for Shot Peen Forming Metal Panels Based on Effective Torque

by Conor Rowan

J. Manuf. Mater. Process. 2025, 9(8), 280; https://doi.org/10.3390/jmmp9080280 - 15 Aug 2025

Abstract

A common technique used in factories to shape metal panels is shot peen forming, where the panel is sprayed with a high-velocity stream of small steel pellets called “shot.” The impacts between the hard steel shot and the softer metal of the panel [...] Read more.

A common technique used in factories to shape metal panels is shot peen forming, where the panel is sprayed with a high-velocity stream of small steel pellets called “shot.” The impacts between the hard steel shot and the softer metal of the panel cause localized plastic deformation, which is used to improve the fatigue properties of the material’s surface. The residual stress distribution imparted by impacts also results in bending, which suggests that a torque is associated with it. In this paper, we model shot peen forming as the application of spatially varying torques to a Kirchhoff plate, opting to use the language of thermoelasticity in order to introduce these torque distributions. First, we derive the governing equations for the thermoelastic thin plate model and show that only a torque-type resultant of the temperature distribution shows up in the bending equation. Next, to calibrate from the shot peen operation, an empirical “effective torque” parameter used in the thermoelastic model, a simple and non-invasive test is devised. This test relies only on measuring the maximum displacement of a uniformly shot peened plate as opposed to characterizing the residual stress distribution. After discussing how to handle the unconventional fully free boundary conditions germane to shot peened plates, we introduce an approach to solving the inverse problem whereby the peening distribution required to obtain a specified plate contour can be obtained. Given that the relation between shot peen distributions and bending displacements at a finite set of points is non-unique, we explore a regularization of the inverse problem which gives rise to shot peen distributions that match the capabilities of equipment in the factory. In order to validate our proposed model, an experiment with quantified uncertainty is designed and carried out which investigates the agreement between the predictions of the calibrated model and real shot peen-forming operations. Full article

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Graphical abstract

20 pages, 10593 KiB

Open AccessArticle

Optimising WC-25Co Feedstock and Parameters for Laser-Directed Energy Deposition

by Helder Nunes, José Nhanga, Luís Regueiras, Ana Reis, Manuel F. Vieira, Bruno Guimarães, Daniel Figueiredo, Cristina Fernandes and Omid Emadinia

J. Manuf. Mater. Process. 2025, 9(8), 279; https://doi.org/10.3390/jmmp9080279 - 14 Aug 2025

Abstract

Laser-Directed Energy Deposition (L-DED) is an additive manufacturing technique used for producing and repairing components, mainly for coating applications, depositing metal matrix composites such as cemented carbides, composed of hard metal carbides and a metallic binder. In this sense, this study evaluated the [...] Read more.

Laser-Directed Energy Deposition (L-DED) is an additive manufacturing technique used for producing and repairing components, mainly for coating applications, depositing metal matrix composites such as cemented carbides, composed of hard metal carbides and a metallic binder. In this sense, this study evaluated the preparation of a ready-to-press WC-25Co powder as a reliable feedstock for L-DED process. This powder required pre-heat treatment studies to prevent fragmentation during powder feeding, due to the absence of metallurgical bonding between WC and Co particles. In the current study, the Taguchi methodology was used, varying laser power, powder feed rate, and scanning speed to reach an optimised deposition window. The best bead morphology resulted from 2400 W laser power, 11 mm/s scanning speed, and 9 g/min feed rate. Moreover, defects such as porosity and cracking were mitigated by applying a remelting strategy of 2400 W and 9 mm/s. Therefore, a perfect deposition is obtained using the optimised processing parameters. Microstructural analysis of the optimised deposited line revealed a fine structure, comprising columnar and equiaxed dendrites of complex carbides. The average hardness of the deposited WC-25Co powder on a AISI 1045 steel was 854 ± 37 HV0.2. These results demonstrate the potential of L-DED for processing high-performance cemented carbide coatings. Full article

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20 pages, 7113 KiB

Open AccessArticle

Extrusion 3D-Printed Kaolinite Ceramic Filters for Water Applications

by Rawan Elsersawy, Romina Donyadari and Mohammad Abu Hasan Khondoker

J. Manuf. Mater. Process. 2025, 9(8), 278; https://doi.org/10.3390/jmmp9080278 - 14 Aug 2025

Abstract

Ceramic materials have been utilized for centuries across a range of industries due to their chemical stability and porous microstructure. One prominent application is water filtration, where ceramics offer an effective medium for removing contaminants. Ceramic filters can operate under either pressure-driven or [...] Read more.

Ceramic materials have been utilized for centuries across a range of industries due to their chemical stability and porous microstructure. One prominent application is water filtration, where ceramics offer an effective medium for removing contaminants. Ceramic filters can operate under either pressure-driven or gravity-driven mechanisms. While traditional fabrication techniques, such as pottery, have been historically employed to produce ceramic filters, these methods are limited by user skills, lack of reproducibility, and geometric constraints. In contrast, modern additive manufacturing techniques provide enhanced precision, repeatability, and customization. This study employs extrusion-based 3D printing to fabricate gravity-driven ceramic filters with tailored geometries to meet specific performance requirements. The use of 3D printing allows for efficient production of uniform filters with optimized internal structures. The selected ceramic material, derived from natural sources, offers environmental compatibility, as it is both sustainable and biodegradable. The fabricated filters were evaluated for their effectiveness in treating water. The filtration tests showed significant improvements in water quality, including reduced turbidity, color, iron, manganese, and total and calcium hardness. pH increased from 6.23 to 7.26, and conductivity dropped from 7.43 mS to 4.5 mS, indicating effective ion removal. These findings highlight the potential of 3D-printed ceramic filters as an environmentally friendly and effective solution for decentralized water purification applications. Full article

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34 pages, 11215 KiB

Open AccessArticle

New Approach to High-Speed Multi-Coordinate Milling Based on Kinematic Cutting Parameters and Acoustic Signals

by Petr M. Pivkin, Mikhail P. Kozochkin, Artem A. Ershov, Ludmila A. Uvarova, Alexey B. Nadykto and Sergey N. Grigoriev

J. Manuf. Mater. Process. 2025, 9(8), 277; https://doi.org/10.3390/jmmp9080277 - 13 Aug 2025

Abstract

In this work, a new approach to high-speed multi-coordinate milling was developed. The new approach is based on a new model of trochoidal machining; this is, in turn, based on the theoretical thickness of a chip and its ratio to the cutting edge’s [...] Read more.

In this work, a new approach to high-speed multi-coordinate milling was developed. The new approach is based on a new model of trochoidal machining; this is, in turn, based on the theoretical thickness of a chip and its ratio to the cutting edge’s radius, allowing us to establish the vibroacoustic indicators of cutting efficiency. The new model can be used for the real-time assessment of prevailing cutting mechanisms and chip formation. A set of new indicators and parameters for trochoidal high-speed milling (HSM), which can be used to calculate tool paths during technological preparation of slotting, was determined and verified. The size effect in the multi-coordinate HSM of slots on cast iron was identified based on the dependency of vibroacoustic signals on the cutting tooth’s geometry, HSM’a operational machining modes, theoretical chip thicknesses, the sizes of the cut chips, and the quality/roughness of the surface being machined. Based on the analysis of vibroacoustic signals, a set of the most important indicators for monitoring HSM and determining cutting and crack-formation mechanisms during chip deformation was derived. Based on the new model, recommendations for monitoring HSM and for assigning the tool path relative to the workpiece during production preparation were developed and validated. Full article

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20 pages, 4555 KiB

Open AccessArticle

An Experimental Study on Ultrasonic-Assisted Drilling of CFRP Composites with Minimum Quantity Lubrication

by Ramazan Hakkı Namlu, Mustafa Burak Sağener, Zekai Murat Kılıç, Oguz Colak and Sadık Engin Kılıç

J. Manuf. Mater. Process. 2025, 9(8), 276; https://doi.org/10.3390/jmmp9080276 - 12 Aug 2025

Abstract

The increasing use of carbon fiber reinforced polymer (CFRP) composites in industries such as aerospace, due to its high strength-to-weight ratio, durability, and resistance to corrosion has led to a growing demand for more efficient machining processes. However, the multilayered structure of CFRP [...] Read more.

The increasing use of carbon fiber reinforced polymer (CFRP) composites in industries such as aerospace, due to its high strength-to-weight ratio, durability, and resistance to corrosion has led to a growing demand for more efficient machining processes. However, the multilayered structure of CFRP composites, composed of densely packed fibers, presents significant challenges during machining. Additionally, when cutting fluids are used to improve effective cooling and lubrication, the material tends to absorb the fluid, causing damage and leading to problem of weaking of composite structure. To address these issues, this study compares ultrasonic-assisted drilling (UAD) and minimum quantity lubrication (MQL) techniques with conventional drilling (CD) and dry cutting to improve the performance of CFRP composite drilling. The results show that using UAD and MQL together reduced thrust force by up to 27%, improved surface roughness inside the holes by up to 31%, reduced improved hole diameter, cylindricity, roundness, and delamination. Full article

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16 pages, 9287 KiB

Open AccessArticle

Nanosecond Laser Cutting of Double-Coated Lithium Metal Anodes: Toward Scalable Electrode Manufacturing

by Masoud M. Pour, Lars O. Schmidt, Blair E. Carlson, Hakon Gruhn, Günter Ambrosy, Oliver Bocksrocker, Vinayakraj Salvarrajan and Maja W. Kandula

J. Manuf. Mater. Process. 2025, 9(8), 275; https://doi.org/10.3390/jmmp9080275 - 11 Aug 2025

Abstract

The transition to high-energy-density lithium metal batteries (LMBs) is essential for advancing electric vehicle (EV) technologies beyond the limitations of conventional lithium-ion batteries. A key challenge in scaling LMB production is the precise, contamination-free separation of lithium metal (LiM) anodes, hindered by lithium’s [...] Read more.

The transition to high-energy-density lithium metal batteries (LMBs) is essential for advancing electric vehicle (EV) technologies beyond the limitations of conventional lithium-ion batteries. A key challenge in scaling LMB production is the precise, contamination-free separation of lithium metal (LiM) anodes, hindered by lithium’s strong adhesion to mechanical cutting tools. This study investigates high-speed, contactless laser cutting as a scalable alternative for shaping double-coated LiM anodes. The effects of pulse duration, pulse energy, repetition frequency, and scanning speed were systematically evaluated using a nanosecond pulsed laser system on 30 µm LiM foils laminated on both sides of an 8 µm copper current collector. A maximum single-pass cutting speed of 3.0 m/s was achieved at a line energy of 0.06667 J/mm, with successful kerf formation requiring both a minimum pulse energy (>0.4 mJ) and peak power (>2.4 kW). Cut edge analysis showed that shorter pulse durations (72 ns) significantly reduced kerf width, the heat-affected zone (HAZ), and bulge height, indicating a shift to vapor-dominated ablation, though with increased spatter due to recoil pressure. Optimal edge quality was achieved with moderate pulse durations (261–508 ns), balancing energy delivery and thermal control. These findings define critical laser parameter thresholds and process windows for the high-speed, high-fidelity cutting of double-coated LiM battery anodes, supporting the industrial adoption of nanosecond laser systems in scalable LMB electrode manufacturing. Full article

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19 pages, 4219 KiB

Open AccessArticle

Machine Learning-Based Prediction of EDM Material Removal Rate and Surface Roughness

by Isam Qasem and Amjad Alsakarneh

J. Manuf. Mater. Process. 2025, 9(8), 274; https://doi.org/10.3390/jmmp9080274 - 11 Aug 2025

Abstract

Examining the electrical discharge machining (EDM) process is challenging in manufacturing technology due to the complexity of the physical events that take place in the gaps between electrodes. In this study, we examined the EDM process in detail and developed multiple machine learning [...] Read more.

Examining the electrical discharge machining (EDM) process is challenging in manufacturing technology due to the complexity of the physical events that take place in the gaps between electrodes. In this study, we examined the EDM process in detail and developed multiple machine learning (ML) models to describe the relationship between the EDM independent (process parameters) and dependent (responses) variables. The collected experimental data was used to train the machine learning models. According to the results, the GPR model outperformed other ML models across different materials, with average RMSE values of 0.9234 and 3.0216 for the material removal rate (MRR) and surface roughness (Sa), respectively, highlighting the effectiveness of ML tools at modeling complex machining processes, such as EDM. In addition, as a practical implication, this study opens the door to employing the developed ML models to predict the EDM process performance. Full article

(This article belongs to the Special Issue Mechanics Analysis and Predictive Modeling of Engineering Materials Involved in the Manufacturing of Parts and Components)

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23 pages, 17405 KiB

Open AccessArticle

Effect of Laser Shock Peening on the Fatigue Performance of Q355D Steel Butt-Welded Joints

by Dongdong You, Yongkang Li, Fenglei Li, Jianhua Wang, Yi Hou, Pengfei Sun and Shengguan Qu

J. Manuf. Mater. Process. 2025, 9(8), 273; https://doi.org/10.3390/jmmp9080273 - 11 Aug 2025

Abstract

This study investigated the effect of laser shock peening (LSP) treatment on the fatigue performance of Q355D steel butt-welded joints. The results demonstrate that LSP sig-nificantly enhances joint fatigue resistance through gradient hardening in surface lay-ers, introduction of high-magnitude residual compressive stress fields, [...] Read more.

This study investigated the effect of laser shock peening (LSP) treatment on the fatigue performance of Q355D steel butt-welded joints. The results demonstrate that LSP sig-nificantly enhances joint fatigue resistance through gradient hardening in surface lay-ers, introduction of high-magnitude residual compressive stress fields, and micro-structural refinement. Specifically, microhardness increased across all joint zones with gradient attenuation of strengthening effects within an approximately 700 μm depth. LSP effectively suppressed residual tensile stress concentration in regions beyond 4 mm on both sides of the weld. Fatigue tests confirmed that LSP substantially extended joint fatigue life: by 113–165% in the high-stress region (250–270 MPa) and 46–63% in the medium-low-stress region (230–240 MPa). Fractographic analysis further revealed reduced fatigue striation spacing and lower microcrack density in LSP-treated speci-mens, reflecting the synergistic effect of residual compressive stress fields and micro-structural refinement in retarding crack propagation. This work substantiates LSP as an effective method for enhancing fatigue resistance in Q355D steel welded joints. Full article

(This article belongs to the Special Issue Progress in Laser Materials Processing)

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18 pages, 2147 KiB

Open AccessArticle

Manufacturing Design and Analysis of Bending Technology by the Variation of the Initial Technological Parameters

by Sándor Bodzás and Gyöngyi Szanyi

J. Manuf. Mater. Process. 2025, 9(8), 272; https://doi.org/10.3390/jmmp9080272 - 11 Aug 2025

Abstract

The aim of this study is a detailed methodological analysis of the bending technology based on literature sources and the analysis of the correlation between the technological parameters. During this research the process of the determination of the technological parameters and their practical [...] Read more.

The aim of this study is a detailed methodological analysis of the bending technology based on literature sources and the analysis of the correlation between the technological parameters. During this research the process of the determination of the technological parameters and their practical interpretation is given special attention. We analyze the technological process in a clear and understandable way using our own prepared figures to assist industrial and educational usage. This work contributes to a deeper understanding of bending technology and supports the basis of the technological decision. Furthermore four experiments will be conducted to find a correlation between the actual variable technological parameter (more variables will be selected) and the received technological parameters to analyze the function between these influential factors. This study can help industrial engineers and university students to understand the complexity of this technology, design all of the technological parameters that are needed to execute this technology for the manufacturing process, and enhance the quality of this metal forming process. Full article

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26 pages, 4117 KiB

Open AccessArticle

Defect Detection via Through-Transmission Ultrasound Using Neural Networks and Domain-Specific Feature Extraction

by Gary LeMay and Enkhsaikhan Boldsaikhan

J. Manuf. Mater. Process. 2025, 9(8), 271; https://doi.org/10.3390/jmmp9080271 - 11 Aug 2025

Abstract

Defect detection in acoustically matched media remains a significant challenge, particularly when defects, such as fiberglass and polyamide residues, exhibit properties that match those of fiber-reinforced composite laminates as the base material. Techniques, such as through-transmission ultrasound (TTU), often miss subtle residues as [...] Read more.

Defect detection in acoustically matched media remains a significant challenge, particularly when defects, such as fiberglass and polyamide residues, exhibit properties that match those of fiber-reinforced composite laminates as the base material. Techniques, such as through-transmission ultrasound (TTU), often miss subtle residues as defects with the use of conventional amplitude-based TTU detection alone. There is a noticeable research gap in properly identifying such subtle residues in composites using TTU inspection. This study investigated the use of neural networks (NNs) to identify subtle defects in composites based on domain-specific feature extraction from TTU signals. Each signal waveform of each spatial TTU inspection is used as a discrete sample to obtain a larger dataset for each specimen. Domain-specific features were extracted separately from the time, frequency, and wavelet domains, resulting in independent feature vectors to emphasize the signal characteristics. The NN classification used 70% of the overall dataset for training and 30% for testing. Results reveal the features of the time- and frequency domains perform well, achieving macro-F1 scores of 0.96 and 0.97, respectively, while wavelet domain features perform lower with a macro-F1 score of 0.62. Wavelet-domain features perhaps need machine learning methods like recurrent NNs to correctly recognize subtle time-dependent signal variations. Full article

(This article belongs to the Special Issue Smart Manufacturing in the Era of Industry 4.0, 2nd Edition)

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21 pages, 4954 KiB

Open AccessArticle

Direct Ink Writing and Characterization of ZrC-Based Ceramic Pellets for Potential Nuclear Applications

by Narges Malmir, Guang Yang, Thomas Poirier, Nathaniel Cavanaugh, Dong Zhao, Brian Taylor, Nikhil Churi, Tiankai Yao, Jie Lian, James H. Edgar, Dong Lin and Shuting Lei

J. Manuf. Mater. Process. 2025, 9(8), 270; https://doi.org/10.3390/jmmp9080270 - 11 Aug 2025

Abstract

Developing advanced nuclear fuel technologies is critical for high-performance applications such as nuclear thermal propulsion (NTP). This study explores the feasibility of direct ink writing (DIW) for fabricating ceramic pellets for potential nuclear applications. Zirconium carbide (ZrC) is used as a matrix material [...] Read more.

Developing advanced nuclear fuel technologies is critical for high-performance applications such as nuclear thermal propulsion (NTP). This study explores the feasibility of direct ink writing (DIW) for fabricating ceramic pellets for potential nuclear applications. Zirconium carbide (ZrC) is used as a matrix material and vanadium carbide (VC) is used as a surrogate for uranium carbide (UC) in this study. A series of ink formulations were developed with varying concentrations of VC and nanocrystalline cellulose (NCC) to optimize the rheological properties for DIW processing. Post-sintering analysis revealed that conventionally sintered samples at 1750 °C exhibited high porosity (>60%), significantly reducing the compressive strength compared to dense ZrC ceramics. However, increasing VC content improved densification and mechanical properties, albeit at the cost of increased shrinkage and ink flow challenges. Spark plasma sintering (SPS) achieved near-theoretical density (~97%) but introduced geometric distortions and microcracking. Despite these challenges, this study demonstrates that DIW offers a viable route for fabricating ZrC-based ceramic structures, provided that sintering strategies and ink rheology are further optimized. These findings establish a baseline for DIW of ZrC-based materials and offer valuable insights into the porosity control, mechanical stability, and processing limitations of DIW for future nuclear fuel applications. Full article

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52 pages, 5052 KiB

Open AccessReview

A Comprehensive Review of Sustainable and Green Additive Manufacturing: Technologies, Practices, and Future Directions

by Sudip Dey Dipta, Md. Mahbubur Rahman, Md. Jonaet Ansari and Md. Nizam Uddin

J. Manuf. Mater. Process. 2025, 9(8), 269; https://doi.org/10.3390/jmmp9080269 - 9 Aug 2025

Abstract

Additive manufacturing (AM), commonly known as 3D printing, has emerged as a transformative technology across various industries due to its potential for design flexibility, material efficiency, and reduced production lead times. As global attention increasingly shifts toward environmental sustainability, there is a growing [...] Read more.

Additive manufacturing (AM), commonly known as 3D printing, has emerged as a transformative technology across various industries due to its potential for design flexibility, material efficiency, and reduced production lead times. As global attention increasingly shifts toward environmental sustainability, there is a growing need to evaluate the ecological implications and opportunities associated with AM. This comprehensive review explores the current state of sustainable and green additive manufacturing (SGAM) technologies and practices, highlighting innovations that reduce energy consumption, minimize material waste, and incorporate renewable or recyclable materials. This study focuses on the utilization of recyclable thermoplastics combined with biodegradable polymers, exploring sustainable source materials, cold fabrication techniques, and cyclic lifecycle strategies integrated with renewable energy systems. Despite its potential, SGAM faces key challenges such as material compatibility, scalability of manufacturing processes, mechanical property optimization, and the need for standardized production protocols. Nevertheless, this work finds that SGAM devices are effective in minimizing environmental impact across the entire manufacturing process, aligning with predominant research trends that emphasize strategic predictive models to guide future developments in AM system implementation. The review concludes with future directions and research opportunities to enhance the environmental performance of AM technologies, ultimately contributing to a more sustainable manufacturing landscape. Full article

(This article belongs to the Special Issue High-Performance Metal Additive Manufacturing, 2nd Edition)

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9 pages, 1119 KiB

Open AccessArticle

Effects of Ultrasonic Vibration Intensity and Initial Powder Amount in the Hopper on Powder Dispensing Rate in Binder Jetting Additive Manufacturing

by Mostafa Meraj Pasha, Zhijian Pei, Yi-Tang Kao and Ken Dubovick

J. Manuf. Mater. Process. 2025, 9(8), 268; https://doi.org/10.3390/jmmp9080268 - 9 Aug 2025

Abstract

In binder jetting additive manufacturing (BJAM), parts are fabricated layer by layer by depositing a liquid binder on selected regions of the powder bed. Powder particles in the hopper of the printer are dispensed onto the powder bed to form a layer of [...] Read more.

In binder jetting additive manufacturing (BJAM), parts are fabricated layer by layer by depositing a liquid binder on selected regions of the powder bed. Powder particles in the hopper of the printer are dispensed onto the powder bed to form a layer of powder. Powder dispensing rate affects material usage and print quality. Too high dispensing rates can cause excessive powder dispensing, increasing powder waste, while too low dispensing rates may result in incomplete layer formation, leading to reduced density of printed parts. The present study investigates how ultrasonic vibration intensity and initial powder amount in the hopper affect powder dispensing rate in BJAM when using a bimodal powder. A set of experiments with full factorial design were conducted using three levels of ultrasonic vibration intensity (50%, 75%, and 100%) and three levels of initial powder amount (600 g, 1000 g, and 1400 g) in the hopper. The results show that both ultrasonic vibration intensity and initial powder amount, as well as their interaction, significantly influence powder dispensing rate. Powder dispensing rate was higher when ultrasonic vibration intensity was higher or initial powder amount was smaller. Increasing initial powder amount from 600 to 1400 g, resulted in a much bigger decrease in powder dispensing rate when ultrasonic vibration intensity was 50% than when ultrasonic vibration intensity was 100%. Full article

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18 pages, 10856 KiB

Open AccessArticle

Influence of Structural Components on Thermal Deformations in Large Machine Tools

by Álvaro Sáinz de la Maza García, Leonardo Sastoque Pinilla and Luis Norberto López de Lacalle Marcaide

J. Manuf. Mater. Process. 2025, 9(8), 267; https://doi.org/10.3390/jmmp9080267 - 8 Aug 2025

Abstract

In sectors that require large components with tight tolerances, the control of machine thermal deformations as a result of ambient temperature variations, motor consumption, and heating of moving components is essential. There are many alternatives for modelling and trying to compensate for this [...] Read more.

In sectors that require large components with tight tolerances, the control of machine thermal deformations as a result of ambient temperature variations, motor consumption, and heating of moving components is essential. There are many alternatives for modelling and trying to compensate for this deformation, but structural components are rarely analysed independently to study their influence on positioning errors. This study analysed component temperature and deformation measurements using 49 thermocouples and 14 integral deformation sensors (IDS) installed on a large-scale machine tool. The effect of each heat source on component deformations was studied and those with a predominant effect were identified. The results can ease thermal effect prediction models development and new machine design process to maximise accuracy by focusing effort on the most critical components and most important heat sources. It was found that ambient temperature variations lead to greater but more uniform deformations than internal heat sources, reaching a 60% of total deformations with smaller temperature changes (8.7 °C, against 15–35 °C due to internal heat sources). These deformations are localized mainly in the machine bed (100

μ

m in X direction and 170

μ

m in the Y direction) and column (150

μ

m in the Z direction) and in the axis ball screw bearings (reaching 55 °C). Consequently, it is concluded that improving bearing and motor refrigeration could significantly reduce thermally-induced deformations. Full article

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