Journal of Manufacturing and Materials Processing

17 pages, 9040 KiB

Open AccessArticle

Adaptive Torque Control for Process Optimization in Friction Stir Welding of Aluminum 6061-T6 Using a Horizontal 5-Axis CNC Machine

by Austin Clark and Ihab Ragai

J. Manuf. Mater. Process. 2025, 9(7), 232; https://doi.org/10.3390/jmmp9070232 - 7 Jul 2025

Abstract

The research presented herein investigates the impact of axial force and feed rate in the Friction Stir Welding (FSW) of aluminum alloy 6061-T6 in a GROB G552 horizontal 5-axis CNC machine with adaptive torque control enabled. The purpose of this study is to [...] Read more.

The research presented herein investigates the impact of axial force and feed rate in the Friction Stir Welding (FSW) of aluminum alloy 6061-T6 in a GROB G552 horizontal 5-axis CNC machine with adaptive torque control enabled. The purpose of this study is to further advance the performance and characteristics of FSW aluminum alloys in 5-axis CNCs, particularly in conjunction with adaptive torque control. The Taguchi and ANOVA methods were utilized to define parameter tables and analyze the resulting data. Optical microscopy and tensile tests were performed on the welded samples to evaluate weld quality. The results from this study provide clear evidence that axial force has a significant effect on tensile strength in FSW AA6061-T6. The maximum UTS found in this study, welded with an axial force of 9.4 kN, retained 69% tensile strength of the base material. Conversely, a decrease in strength and an increase in void formation was found at higher feed rates with this force. Ideal welds, with minimal defects across all feed rates, were performed with an axial force of 8.3 kN. A feed rate of 300 mm/min at this force resulted in a 67% base metal strength. These findings contribute to improving joint strength and application efficiency in FSW AA6061-T6 performed in a horizontal 5-axis CNC machine where adaptive torque control is enabled. Full article

(This article belongs to the Special Issue Innovative Approaches in Metal Forming and Joining Technologies)

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18 pages, 3035 KiB

Open AccessArticle

Data-Driven Modeling and Enhancement of Surface Quality in Milling Based on Sound Signals

by Paschalis Charalampous

J. Manuf. Mater. Process. 2025, 9(7), 231; https://doi.org/10.3390/jmmp9070231 - 4 Jul 2025

Abstract

The present study introduces an AI (Artificial Intelligence) framework for surface roughness assessment in milling operations through sound signal processing. As industrial demands escalate for in-process quality control solutions, the proposed system leverages audio data to estimate surface finish states without interrupting production. [...] Read more.

The present study introduces an AI (Artificial Intelligence) framework for surface roughness assessment in milling operations through sound signal processing. As industrial demands escalate for in-process quality control solutions, the proposed system leverages audio data to estimate surface finish states without interrupting production. In order to address this, a novel classification approach was developed that maps audio waveform data into predictive indicators of surface quality. In particular, an experimental dataset was employed consisting of sound signals that were captured during milling procedures applying various machining conditions, where each signal was labeled with a corresponding roughness quality obtained via offline metrology. The formulated classification pipeline commences with audio acquisition, resampling, and normalization to ensure consistency across the dataset. These signals are then transformed into Mel-Frequency Cepstral Coefficients (MFCCs), which yield a compact time–frequency representation optimized for human auditory perception. Next, several AI algorithms were trained in order to classify these MFCCs into predefined surface roughness categories. Finally, the results of the work demonstrate that sound signals could contain sufficient discriminatory information enabling a reliable classification of surface finish quality. This approach not only facilitates in-process monitoring but also provides a foundation for intelligent manufacturing systems capable of real-time quality assurance. Full article

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27 pages, 61752 KiB

Open AccessArticle

Knowledge Generation of Wire Laser-Beam-Directed Energy Deposition Process Combining Process Data and Metrology Responses

by Adriano Nicola Pilagatti, Eleonora Atzeni, Alessandro Salmi, Konstantinos Tzimanis, Nikolas Porevopoulos and Panagiotis Stavropoulos

J. Manuf. Mater. Process. 2025, 9(7), 230; https://doi.org/10.3390/jmmp9070230 - 3 Jul 2025

Abstract

Industries are leveraging the wire laser-beam-directed energy deposition (DED-LB) additive manufacturing (AM) process to manufacture and repair high-quality, defect-free, and cost-effective parts. However, expensive, non-easily accessible, and complex metrology equipment is needed to quantify part-related performance metrics such as cross-sectional dimensional accuracy and [...] Read more.

Industries are leveraging the wire laser-beam-directed energy deposition (DED-LB) additive manufacturing (AM) process to manufacture and repair high-quality, defect-free, and cost-effective parts. However, expensive, non-easily accessible, and complex metrology equipment is needed to quantify part-related performance metrics such as cross-sectional dimensional accuracy and intrinsic defects. This information is necessary for establishing the operating process window and for the quality characterization of the part. Therefore, this work presents a methodology that combines information captured from a vision-based monitoring system with the output of Computed Tomography (CT) towards the knowledge generation and process optimization of wire DED-LB. The design of experiments as well as the interpretation of the results are achieved by employing Nested ANOVA where the dependency of cross-sectional stability on the laser power parameter is demonstrated, enabling, at the same time, the understanding of unstructured datasets where multiple parameters vary at different levels. Finally, this work can be the pillar for adopting new production and part requirements while also giving directions about the effect of control strategies on the part quality. Full article

(This article belongs to the Special Issue Design, Processes and Materials for Additive Manufacturing: 2nd Edition)

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19 pages, 2263 KiB

Open AccessArticle

3D Printing in the Design of Devices for Dosing Intramuscular Injections with Syringe

by José Manuel Sierra, Mª del Rocío Fernandez, José Luis Cortizo and Paula Zurrón-Madera

J. Manuf. Mater. Process. 2025, 9(7), 229; https://doi.org/10.3390/jmmp9070229 - 3 Jul 2025

Abstract

This article describes the use of 3D printing as a tool for the design of a dosing device for intramuscular injections by nursing professionals. A device that is safer against accidental punctures, easy to use, and functional. After the analysis of the problem [...] Read more.

This article describes the use of 3D printing as a tool for the design of a dosing device for intramuscular injections by nursing professionals. A device that is safer against accidental punctures, easy to use, and functional. After the analysis of the problem by a multidisciplinary team, which included nurses and engineers, a first basic prototype has been built for testing. In the process, software for solid modeling has been used; functional prototypes have been developed from the virtual models by rapid prototyping using fused deposition modeling technology (FDM), in Polylactic Acid (PLA) material, and have been tested to verify their mechanical properties and suitability for function. The project has developed a functional design that has been patented, and is in the clinical trials phase. This study demonstrates the efficacy of three-dimensional (3D) printing technologies to expedite the design process and build low-cost functional prototypes. The dosing and needle-protection mechanisms are driven by compression springs; the forces needed for both mechanisms were initially estimated through theoretical calculations and verified through empirical testing. Full article

(This article belongs to the Special Issue Innovative Rapid Tooling in Additive Manufacturing Processes)

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15 pages, 4049 KiB

Open AccessArticle

Design of Spider Web Biomimetic Structure Car Roof Handrails Based on Additive Manufacturing

by Qing Chai, Huo Wu, Zhe Liang, Yuyang Han and Shuo Yin

J. Manuf. Mater. Process. 2025, 9(7), 228; https://doi.org/10.3390/jmmp9070228 - 3 Jul 2025

Abstract

The combination of additive manufacturing technology and biomimetic structures plays an increasingly important role in the lightweight design of automotive parts. This work provides a lightweight design and manufacturing method for the spider web biomimetic structure of car roof handrails. Firstly, in order [...] Read more.

The combination of additive manufacturing technology and biomimetic structures plays an increasingly important role in the lightweight design of automotive parts. This work provides a lightweight design and manufacturing method for the spider web biomimetic structure of car roof handrails. Firstly, in order to obtain a more reasonable combination of spider web structure and roof handrail, three new schemes are designed, namely spider web biomimetic roof handrail distributed along the x, y and z axes. Further simulation and comparison of the three new solutions with traditional handrails are performed to determine the final solution. The simulation results show that under the influence of different loads, the design along the z-axis direction is superior to the design in other directions, and it reduces weight by 32.03% compared to the traditional handrail theoretically while meeting the mechanical performance requirements, demonstrating a good lightweight effect. In addition, multiple material comparative tests are conducted by conducting tensile tests on car roof handrails made of different materials. The results indicate that the handrail made of PA6-CF has excellent overall performance, meeting safety standards and allowing for significant elastic deformation, optimizing the user experience. Full article

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21 pages, 7297 KiB

Open AccessArticle

Additively Produced Ti-6Al-4V Osteosynthesis Devices Meet the Requirements for Tensile Strength and Fatigue

by Alisdair R. MacLeod, Matthew Bishop, Alberto Casonato Longo, Alborz Shokrani, Chris Rhys Bowen and Harinderjit Singh Gill

J. Manuf. Mater. Process. 2025, 9(7), 227; https://doi.org/10.3390/jmmp9070227 - 3 Jul 2025

Abstract

The purpose of this study was to estimate the peak stresses in a laser powder bed fusion (LPBF) additive-manufactured (AM) osteosynthesis plate during physiological loading and establish if the mechanical properties of LPBF titanium alloy were suitable for this use case. Finite element [...] Read more.

The purpose of this study was to estimate the peak stresses in a laser powder bed fusion (LPBF) additive-manufactured (AM) osteosynthesis plate during physiological loading and establish if the mechanical properties of LPBF titanium alloy were suitable for this use case. Finite element models of subject-specific osteosynthesis plates for a cohort of 28 patients were created and used to calculate the peak maximum principal stresses during physiological loading, which was estimated to be 166 MPa twelve weeks post-operatively. All specimens were LPBF additively manufactured in Ti-6Al-4V alloy. ISO compliant tests were performed for tensile and fatigue, respectively. Fatigue testing was performed for specimens that had been heat-treated only and those that had been heat-treated and polished. The Upper Yield Stress was 1012.5 ± 19.2 MPa. The fatigue limit was 227 MPa for heat-treated only specimens and increased to 286 MPa for heat-treated and polished specimens. The finite element predicted stresses were below the experimentally established limits of yield and fatigue. The tensile and fatigue properties of heat-treated LPBF Ti-6Al-4V are therefore sufficient to meet the mechanical requirements of osteosynthesis plates. Polishing is recommended to improve fatigue resistance. Full article

(This article belongs to the Special Issue Recent Advances in 3D Printing Technologies in Bioengineering with Selected Papers from the 29th Congress of the European Society of Biomechanics (ESB 2024))

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18 pages, 2891 KiB

Open AccessArticle

Size Effects on Process-Induced Porosity in Ti6Al4V Thin Struts Additively Manufactured by Laser Powder-Bed Fusion

by Nismath Valiyakath Vadakkan Habeeb and Kevin Chou

J. Manuf. Mater. Process. 2025, 9(7), 226; https://doi.org/10.3390/jmmp9070226 - 2 Jul 2025

Abstract

Laser powder-bed fusion (L-PBF) additive manufacturing has been widely explored for fabricating intricate metallic parts such as lattice structures with thin struts. However, L-PBF-fabricated small parts (e.g., thin struts) exhibit different morphological and mechanical characteristics compared to bulk-sized parts due to distinct scan [...] Read more.

Laser powder-bed fusion (L-PBF) additive manufacturing has been widely explored for fabricating intricate metallic parts such as lattice structures with thin struts. However, L-PBF-fabricated small parts (e.g., thin struts) exhibit different morphological and mechanical characteristics compared to bulk-sized parts due to distinct scan lengths, affecting the melt pool behavior between transient and quasi-steady states. This study investigates the keyhole porosity in Ti6Al4V thin struts fabricated by L-PBF, incorporating a range of strut sizes, along with various levels of linear energy densities. Micro-scaled computed tomography and image analysis were employed for porosity measurements and evaluations. Generally, keyhole porosity lessens with decreasing energy density, though with varying patterns across a higher energy density range. Keyhole porosity in struts predictably becomes severe at high laser powers and/or low scan speeds. However, a major finding reveals that the porosity is reduced with decreasing strut size (if less than 1.25 mm diameter), plausibly because the keyhole formed has not reached a stable state to produce pores in a permanent way. This implies that a higher linear energy density, greater than commonly formulated in making bulk components, could be utilized in making small-scale features to ensure not only full melting but also minimum keyhole porosity. Full article

(This article belongs to the Special Issue Design, Processes and Materials for Additive Manufacturing: 2nd Edition)

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19 pages, 2709 KiB

Open AccessReview

Enabling Sustainable Solar Energy Systems Through Electromagnetic Monitoring of Key Components Across Production, Usage, and Recycling: A Review

by Mahdieh Samimi and Hassan Hosseinlaghab

J. Manuf. Mater. Process. 2025, 9(7), 225; https://doi.org/10.3390/jmmp9070225 - 1 Jul 2025

Abstract

The transition to renewable energy requires sustainable solar manufacturing through optimized Production–Usage–Recycling (PUR) cycles, where electromagnetic (EM) sensing offers non-destructive monitoring solutions. This review categorizes EM methods into low- (<100 MHz) and medium-frequency (100 MHz–10 GHz) techniques for material evaluation, defect detection, and [...] Read more.

The transition to renewable energy requires sustainable solar manufacturing through optimized Production–Usage–Recycling (PUR) cycles, where electromagnetic (EM) sensing offers non-destructive monitoring solutions. This review categorizes EM methods into low- (<100 MHz) and medium-frequency (100 MHz–10 GHz) techniques for material evaluation, defect detection, and performance optimization throughout the solar lifecycle. During production, eddy current testing and impedance spectroscopy improve quality control while reducing waste. In operational phases, RFID-based monitoring enables continuous performance tracking and early fault detection of photovoltaic panels. For recycling, electrodynamic separation efficiently recovers materials, supporting circular economies. The analysis demonstrates the unique advantages of EM techniques in non-contact evaluation, real-time monitoring, and material-specific characterization, addressing critical sustainability challenges in photovoltaic systems. By examining capabilities and limitations, we highlight EM monitoring’s transformative potential for sustainable manufacturing, from production quality assurance to end-of-life material recovery. The frequency-based framework provides manufacturers with physics-guided solutions that enhance efficiency while minimizing environmental impact. This comprehensive assessment establishes EM technologies as vital tools for advancing solar energy systems, offering practical monitoring approaches that align with global sustainability goals. The review identifies current challenges and future opportunities in implementing these techniques, emphasizing their role in facilitating the renewable energy transition through improved resource efficiency and lifecycle management. Full article

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21 pages, 3031 KiB

Open AccessArticle

Influence and Potential of Additive Manufactured Reference Geometries for Ultrasonic Testing

by Stefan Keuler, Anne Jüngert, Martin Werz and Stefan Weihe

J. Manuf. Mater. Process. 2025, 9(7), 224; https://doi.org/10.3390/jmmp9070224 - 1 Jul 2025

Abstract

This study researches and discusses the impact of different manufacturing-induced effects of additive manufacturing (AM), such as anisotropy on sound propagation and attenuation, on the production of test specimens for ultrasonic testing (UT). It was shown that a linear, alternating hatching pattern led [...] Read more.

This study researches and discusses the impact of different manufacturing-induced effects of additive manufacturing (AM), such as anisotropy on sound propagation and attenuation, on the production of test specimens for ultrasonic testing (UT). It was shown that a linear, alternating hatching pattern led to strong anisotropy in sound velocity and attenuation, with a deviation in sound velocity and gain of over 840 m/s and 9 dB, depending on the measuring direction. Furthermore, it was demonstrated that the build direction exhibits distinct acoustic properties. The influence of surface roughness on both the reflector and coupling surfaces was analyzed. It was demonstrated that post-processing of the reflector surface is not necessary, as varying roughness levels did not significantly change the signal amplitude. However, for high frequencies, pre-treatment of the coupling surface can improve sound transmission up to 6 dB at 20 MHz. Finally, the reflection properties of flat bottom holes (FBH) in reference blocks produced by AM and electrical discharge machining (EDM) were compared. The equivalent reflector size (ERS) of the FBH, which refers to the size of an idealized defect with the same ultrasonic reflection behavior as the measured defect, was determined using the distance gain size (DGS) method—a method that uses the relationship between reflector size, scanning depth, and echo amplitude to evaluate defects. The findings suggest that printed FBHs achieve an improved match between the ERS and the actual manufactured reflector size with a deviation of less than 13%, thereby demonstrating the potential for producing standardized test blocks through additive manufacturing. Full article

(This article belongs to the Special Issue Advanced Welding Processes, Additive Manufacturing and Numerical Models: 2nd Edition)

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13 pages, 958 KiB

Open AccessArticle

Efficient Manufacturing of Steerable Eversion Robots with Integrated Pneumatic Artificial Muscles

by Thomas Mack, Cem Suulker, Abu Bakar Dawood and Kaspar Althoefer

J. Manuf. Mater. Process. 2025, 9(7), 223; https://doi.org/10.3390/jmmp9070223 - 1 Jul 2025

Abstract

Soft-growing robots based on the eversion principle are renowned for their ability to rapidly extend along their longitudinal axis, allowing them to access remote, confined, or otherwise inaccessible spaces. Their inherently compliant structure enables safe interaction with delicate environments, while their simple actuation [...] Read more.

Soft-growing robots based on the eversion principle are renowned for their ability to rapidly extend along their longitudinal axis, allowing them to access remote, confined, or otherwise inaccessible spaces. Their inherently compliant structure enables safe interaction with delicate environments, while their simple actuation mechanisms support lightweight and low-cost designs. Despite these benefits, implementing effective navigation mechanisms remains a significant challenge. Previous research has explored the use of pneumatic artificial muscles mounted externally on the robot’s body, which, when contracting, induce directional bending. However, this method only offers limited bending performance. To enhance maneuverability, pneumatic artificial muscles embedded in between the walls of double-walled eversion robots have also been considered and shown to offer superior bending performance and force output as compared to externally attached muscle. However, their adoption has been hindered by the complexity of the current manufacturing techniques, which require individually sealing the artificial muscles. To overcome this multi-stage fabrication approach in which muscles are embedded one by one, we propose a novel single-step method. The key to our approach is the use of non-heat-sealable inserts to form air channels during the sealing process. This significantly simplifies the process, reducing production time and effort and improving scalability for manufacturing, potentially enabling mass production. We evaluate the fabrication speed and bending performance of robots produced in this manner and benchmark them against those described in the literature. The results demonstrate that our technique offers high bending performance and significantly improves the manufacturing efficiency. Full article

(This article belongs to the Special Issue Advances in Robotic-Assisted Manufacturing Systems)

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14 pages, 3070 KiB

Open AccessArticle

Low–Cost 3D–Printed Standard Gain Horn Antennas for Millimetre–Wave Applications

by Shaker Alkaraki, Zia Ullah Khan, Syeda Fizzah Jilani, Andy Andre Sarker, James R. Kelly and Akram Alomainy

J. Manuf. Mater. Process. 2025, 9(7), 222; https://doi.org/10.3390/jmmp9070222 - 1 Jul 2025

Abstract

This paper presents additively manufactured (3D printed) several standard gain horn antennas which have been designed to ensure simple and low–cost fabrication. In order to validate the proposed manufacturing approach, we have designed a number of antennas covering the entire frequency range from [...] Read more.

This paper presents additively manufactured (3D printed) several standard gain horn antennas which have been designed to ensure simple and low–cost fabrication. In order to validate the proposed manufacturing approach, we have designed a number of antennas covering the entire frequency range from 26 GHz to 110 GHz. The proposed antennas have been prototyped and measured. They were found to yield very good performance when compared to commercially available standard gain horn antennas. Unlike metallic standard gain horns antennas, whose manufacturing cost increases as the frequency goes high due to fabrication challenges, the cost of fabricating 3D–printed antennas goes actually down as the frequency increases (up to 110 GHz). The measured performances, in terms of return loss, radiation patterns and gain, of these fabricated 3D printed antennas agree remarkably well with the measured results for commercially available standard gain horns antennas. Full article

(This article belongs to the Special Issue Next-Generation Material Designs and Processes for Additive Manufacturing)

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24 pages, 4087 KiB

Open AccessArticle

Optimization of Nozzle Diameter and Printing Speed for Enhanced Tensile Performance of FFF 3D-Printed ABS and PLA

by I. S. ELDeeb, Ehssan Esmael, Saad Ebied, Mohamed Ragab Diab, Mohammed Dekis, Mikhail A. Petrov, Abdelhameed A. Zayed and Mohamed Egiza

J. Manuf. Mater. Process. 2025, 9(7), 221; https://doi.org/10.3390/jmmp9070221 - 1 Jul 2025

Abstract

Fused Filament Fabrication (FFF) is a widely adopted additive manufacturing technique, yet its mechanical performance is highly dependent on process parameters, particularly nozzle diameter and printing speed. This study evaluates the influence of these parameters on the tensile behavior of Acrylonitrile Butadiene Styrene [...] Read more.

Fused Filament Fabrication (FFF) is a widely adopted additive manufacturing technique, yet its mechanical performance is highly dependent on process parameters, particularly nozzle diameter and printing speed. This study evaluates the influence of these parameters on the tensile behavior of Acrylonitrile Butadiene Styrene (ABS) and Polylactic Acid (PLA), aiming to determine optimal conditions for enhanced strength. ASTM D638-Type IV specimens were printed using nozzle diameters ranging from 0.05 to 0.25 mm and speeds from 15 to 80 mm/s. For ABS, tensile strength increased from 56.46 MPa to 60.74 MPa, representing a 7.6% enhancement, as nozzle diameter increased, with the best performance observed at 0.25 mm and 45 mm/s, attributed to improved melt flow and interlayer fusion. PLA exhibited a non-linear response, reaching a maximum strength of 89.59 MPa under the same conditions, marking a 22.3% enhancement over the minimum value. The superior performance of PLA was linked to optimal thermal management that enhanced crystallinity and interlayer bonding. Fractographic analysis revealed reduced porosity and smoother fracture surfaces under optimized conditions. Overall, PLA consistently outperformed ABS across all settings, with an average tensile strength advantage of 47.5%. The results underscore the need for material-specific parameter tuning in FFF and offer practical insights for optimizing mechanical performance in applications demanding high structural integrity, including biomedical, aerospace, and functional prototyping. Full article

(This article belongs to the Special Issue Recent Advances in Optimization of Additive Manufacturing Processes)

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24 pages, 1546 KiB

Open AccessArticle

Comprehensive Prediction Model for Analysis of Rolling Bearing Ring Waviness

by Marek Šafář, Leonard Dütsch, Marta Harničárová, Jan Valíček, Milena Kušnerová, Hakan Tozan, Ivan Kopal, Karel Falta, Cristina Borzan and Zuzana Palková

J. Manuf. Mater. Process. 2025, 9(7), 220; https://doi.org/10.3390/jmmp9070220 - 30 Jun 2025

Abstract

The objective of this study was to identify surface geometric deviations that may adversely affect the operational properties of bearings, including vibration, noise, and service life. A comprehensive prediction model is presented that combines a fundamental trend expressed by a power function with [...] Read more.

The objective of this study was to identify surface geometric deviations that may adversely affect the operational properties of bearings, including vibration, noise, and service life. A comprehensive prediction model is presented that combines a fundamental trend expressed by a power function with periodic oscillations, whose influence gradually diminishes with exponential decay. The model was calibrated using the experimental data obtained from 17 industrial RA-608-338 rolling bearing rings manufactured from high-carbon, low-alloy 100Cr6 steel. An excellent goodness-of-fit (R² exceeding 0.98) and minimal root-mean-square error (RMSE) were achieved. The proposed procedure provides a clear physical interpretation of the model’s subcomponents, while facilitating straightforward implementation in real production processes for continuous quality control and predictive maintenance purposes. This paper also includes a detailed description of the methodology, data processing, experimental results, comparison of multiple model variants, interactive visualization of the results on a logarithmic scale, and recommendations for practical application. Full article

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20 pages, 2364 KiB

Open AccessArticle

New Hybrid Method for Buffer Positioning and Production Control Using DDMRP Logic in Smart Manufacturing

by Sahar Habbadi, Ismail El Mouayni, Brahim Herrou and Souhail Sekkat

J. Manuf. Mater. Process. 2025, 9(7), 219; https://doi.org/10.3390/jmmp9070219 - 30 Jun 2025

Abstract

Despite its proven effectiveness in inventory management across various industries, Demand-Driven Material Requirements Planning (DDMRP) remains largely a manual process, with few studies investigating its numerical integration. This research proposes a novel multi-stage production control framework grounded in DDMRP principles, enabling effective scheduling [...] Read more.

Despite its proven effectiveness in inventory management across various industries, Demand-Driven Material Requirements Planning (DDMRP) remains largely a manual process, with few studies investigating its numerical integration. This research proposes a novel multi-stage production control framework grounded in DDMRP principles, enabling effective scheduling of production orders based on either demand forecasts or actual demand, when available. A mixed-integer programming (MIP) model is developed to capture the dynamic interactions between demand, buffer positioning, and replenishment policies, supporting reactive production planning in smart, reconfigurable manufacturing environments. To identify the optimal buffer locations, a Genetic Algorithm (GA) is employed. The MIP model provides the GA with production planning outputs used to evaluate the fitness of decisions regarding buffer placement. To demonstrate the effectiveness of this hybrid GA–MIP approach, simulations are conducted on three representative production configurations. The results show that the proposed method significantly improves the theoretical performance of each configuration by determining optimal buffer locations and planning replenishments, achieving a better balance between inventory levels and demand fulfillment. Full article

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12 pages, 4460 KiB

Open AccessArticle

Influence of Laser Energy Variation on the Composition and Properties of Gradient-Structured Cemented Carbide Layers Produced by LP-DED

by Yorihiro Yamashita, Kenta Kawabata, Hayato Mori, Eito Ose and Takahiro Kunimine

J. Manuf. Mater. Process. 2025, 9(7), 218; https://doi.org/10.3390/jmmp9070218 - 27 Jun 2025

Abstract

In this study, graded cemented carbide layers were fabricated using Laser Powder-Directed Energy Deposition (LP-DED) to investigate the effects of laser input energy and WC content on crack formation, compositional distribution, and hardness. Two-layer structures were formed, with the first layer containing either [...] Read more.

In this study, graded cemented carbide layers were fabricated using Laser Powder-Directed Energy Deposition (LP-DED) to investigate the effects of laser input energy and WC content on crack formation, compositional distribution, and hardness. Two-layer structures were formed, with the first layer containing either 30.5 wt.% or 42.9 wt.% WC and the second layer containing 63.7 wt.% WC. Crack formation was evaluated in situ using acoustic emission (AE) sensors, and elemental composition and Vickers hardness were measured across the cross-section of the deposited layers. The results showed that crack formation increased with higher laser power and higher WC content in the first layer. Elemental analysis revealed that higher laser input led to greater Co enrichment and reduced W content near the surface. Additionally, the formation of brittle structures was observed under high-energy conditions, contributing to increased hardness but decreased toughness. These findings indicate that both WC content and laser energy strongly influence the microstructural evolution and mechanical properties of graded cemented carbide layers. Optimizing the balance between WC content and laser parameters is essential for improving the crack resistance and performance of cemented carbide layers in additive manufacturing applications. Full article

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22 pages, 3810 KiB

Open AccessFeature PaperArticle

From Digital Design to Edible Art: The Role of Additive Manufacturing in Shaping the Future of Food

by János Simon and László Gogolák

J. Manuf. Mater. Process. 2025, 9(7), 217; https://doi.org/10.3390/jmmp9070217 - 27 Jun 2025

Abstract

Three-dimensional food printing (3DFP), a specialized application of additive manufacturing (AM), employs a layer-by-layer deposition process guided by digital image files to fabricate edible structures. Utilizing heavily modified 3D printers and Computer-Aided Design (CAD) software technology allows for the precise creation of customized [...] Read more.

Three-dimensional food printing (3DFP), a specialized application of additive manufacturing (AM), employs a layer-by-layer deposition process guided by digital image files to fabricate edible structures. Utilizing heavily modified 3D printers and Computer-Aided Design (CAD) software technology allows for the precise creation of customized food items tailored to individual aesthetic preferences and nutritional requirements. Three-dimensional food printing holds significant potential in revolutionizing the food industry by enabling the production of personalized meals, enhancing the sensory dining experience, and addressing specific dietary constraints. Despite these promising applications, 3DFP remains one of the most intricate and technically demanding areas within AM, particularly in the context of modern gastronomy. Challenges such as the rheological behaviour of food materials, print stability, and the integration of cooking functions must be addressed to fully realize its capabilities. This article explores the possibilities of applying classical modified 3D printers in the food industry. The behaviour of certain recipes is also tested. Two test case scenarios are covered. The first scenario is the work and formation of a homogenized meat mass. The second scenario involves finding a chocolate recipe that is suitable for printing relatively detailed chocolate decorative elements. The current advancements, technical challenges, and future opportunities of 3DFP in the field of engineering, culinary innovation and nutritional science are also explored. Full article

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

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21 pages, 1338 KiB

Open AccessArticle

Flexible Job Shop Scheduling with Job Precedence Constraints: A Deep Reinforcement Learning Approach

by Yishi Li and Chunlong Yu

J. Manuf. Mater. Process. 2025, 9(7), 216; https://doi.org/10.3390/jmmp9070216 - 26 Jun 2025

Abstract

The flexible job shop scheduling problem with job precedence constraints (FJSP-JPC) is highly relevant in industrial production scenarios involving assembly operations. Traditional methods, such as mathematical programming and meta-heuristics, often struggle with scalability and efficiency when solving large instances. We propose a deep [...] Read more.

The flexible job shop scheduling problem with job precedence constraints (FJSP-JPC) is highly relevant in industrial production scenarios involving assembly operations. Traditional methods, such as mathematical programming and meta-heuristics, often struggle with scalability and efficiency when solving large instances. We propose a deep reinforcement learning (DRL) approach to minimize makespan in FJSP-JPC. The proposed method employs a heterogeneous disjunctive graph to represent the system state and a multi-head graph attention network for feature extraction. An actor–critic framework, trained using proximal policy optimization (PPO), is adopted to make operation sequencing and machine assignment decisions. The effectiveness of the proposed method is validated through comparisons with several classic dispatching rules and a state-of-the-art DRL approach. Additionally, the contributions of key mechanisms, such as information diffusion, node features, and action space, are analyzed through a full factorial design of experiments. Full article

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

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31 pages, 3471 KiB

Open AccessReview

Advances in the Additive Manufacturing of Superalloys

by Antonio del Bosque, Pablo Fernández-Arias and Diego Vergara

J. Manuf. Mater. Process. 2025, 9(7), 215; https://doi.org/10.3390/jmmp9070215 - 25 Jun 2025

Abstract

This study presents a bibliometric analysis of the evolution and research trends in the additive manufacturing (AM) of superalloys over the last decade (2015–2025). The review follows a structured methodology based on the PRISMA 2020 protocol, utilizing data from the Scopus and Web [...] Read more.

This study presents a bibliometric analysis of the evolution and research trends in the additive manufacturing (AM) of superalloys over the last decade (2015–2025). The review follows a structured methodology based on the PRISMA 2020 protocol, utilizing data from the Scopus and Web of Science (WoS) databases. Particular attention is devoted to the intricate process–structure–property relationships and the specific behavioral trends associated with different superalloy families, namely Ni-based, Co-based, and Fe–Ni-based systems. The findings reveal a substantial growth in scientific output, with the United States and China leading contributions and an increasing trend in international collaboration. Key research areas include process optimization, microstructural evolution and control, mechanical property assessment, and defect minimization. The study highlights the pivotal role of technologies such as laser powder bed fusion, electron beam melting, and directed energy deposition in the fabrication of high-performance components. Additionally, emerging trends point to the integration of machine learning and artificial intelligence for real-time quality monitoring and manufacturing parameter optimization. Despite these advancements, challenges such as anisotropic properties, porosity issues, and process sustainability remain critical for both industrial applications and future academic research in superalloys. Full article

(This article belongs to the Special Issue Application of 3D Printing Technology in Manufacturing and Material Processing)

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15 pages, 15667 KiB

Open AccessArticle

Novel Tools for Analyzing Life Cycle Energy Use, Carbon Emissions, and Cost of Additive Manufacturing

by Christopher Price, Kristina Armstrong, Dipti Kamath, Sachin Nimbalkar and Joseph Cresko

J. Manuf. Mater. Process. 2025, 9(7), 214; https://doi.org/10.3390/jmmp9070214 - 25 Jun 2025

Abstract

Decarbonizing industrial manufacturing is a significant challenge in the effort to limit the impacts of global climate change. Additive manufacturing (AM) is one pathway for reducing the impacts of manufacturing as it creates parts layer-by-layer rather than by removing (i.e., subtracting) material from [...] Read more.

Decarbonizing industrial manufacturing is a significant challenge in the effort to limit the impacts of global climate change. Additive manufacturing (AM) is one pathway for reducing the impacts of manufacturing as it creates parts layer-by-layer rather than by removing (i.e., subtracting) material from solid stock as with conventional techniques. This reduces material inputs and generates less waste, which can substantially lower life cycle energy consumption and greenhouse gas emissions. However, AM adoption in the manufacturing sector has been slow, partly due to challenges in making a strong business case compared with more traditional and widely available techniques. This paper highlights the need for the development of simple screening analysis tools to speed the adoption of AM in the manufacturing sector by providing decision-makers easy access to important production life cycle emissions, and cost information. Details on the development of two Microsoft Excel software tools are provided: upgrades to an existing tool on the energy and carbon impacts of AM and a new tool for analyzing the major cost components of AM. A case study applies these two tools to the production of a lightweight aerospace bracket, showing how the tools can be used to estimate the environmental benefits and production costs of AM. Full article

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