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Assembly Complexity Index (ACI) for Modular Robotic Systems: Validation and Conceptual Framework for AR/VR-Assisted Assembly
A Review of Artificial Intelligence-Driven Active Vibration and Noise Control

Journal Description

Machines

Machines is an international, peer-reviewed, open access journal on machinery and engineering published monthly online by MDPI. The IFToMM is affiliated with Machines and its members receive a discount on the article processing charges.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, SCIE (Web of Science), Inspec, and other databases.
Journal Rank: JCR - Q2 (Engineering, Mechanical) / CiteScore - Q1 (Control and Optimization)
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.9 days after submission; acceptance to publication is undertaken in 2.4 days (median values for papers published in this journal in the first half of 2025).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Journal Cluster of Mechanical Manufacturing and Automation Control: Aerospace, Automation, Drones, Journal of Manufacturing and Materials Processing, Machines, Robotics and Technologies.

Impact Factor: 2.5 (2024); 5-Year Impact Factor: 2.6 (2024)

Imprint Information Journal Flyer Open Access ISSN: 2075-1702

Latest Articles

16 pages, 3621 KB

Open AccessArticle

A Woven Soft Wrist-Gripper Composite End-Effector with Variable Stiffness: Design, Modeling, and Characterization

by Pan Zhou, Yangzuo Liu, Junxi Chen, Haoyuan Chen, Haili Li and Jiantao Yao

Machines 2025, 13(11), 1042; https://doi.org/10.3390/machines13111042 - 11 Nov 2025

Soft robots often suffer from insufficient load capacity due to the softness of their materials. Existing variable stiffness technologies usually introduce rigid components, resulting in decreased flexibility and complex structures of soft robots. To address these challenges, this work proposes a novel wrist-gripper [...] Read more.

Soft robots often suffer from insufficient load capacity due to the softness of their materials. Existing variable stiffness technologies usually introduce rigid components, resulting in decreased flexibility and complex structures of soft robots. To address these challenges, this work proposes a novel wrist-gripper composite soft end-effector based on the weaving jamming principle, which features a highly integrated design combining structure, actuation, and stiffness. This end-effector is directly woven from pneumatic artificial muscles through weaving technology, which has notable advantages such as high integration, strong performance designability, lightweight construction, and high power density, effectively reconciling the technical trade-off between compliance and load capacity. Experimental results demonstrate that the proposed end-effector exhibits excellent flexibility and multi-degree-of-freedom grasping capabilities. Its variable stiffness function enhances its ability to resist external interference by 4.77 times, and its grasping force has increased by 1.7 times, with a maximum grasping force of 102 N. Further, a grasping force model for this fiber-reinforced woven structure is established, providing a solution to the modeling challenge of highly coupled structures. A comparison between theoretical and experimental data indicates that the modeling error does not exceed 7.8 N. This work offers a new approach for the design and analysis of high-performance, highly integrated soft end-effectors, with broad application prospects in unstructured environment operations, non-cooperative target grasping, and human–robot collaboration. Full article

(This article belongs to the Section Robotics, Mechatronics and Intelligent Machines)

20 pages, 3141 KB

Open AccessArticle

Solid Lubricants for the Wheel–Rail Interface: Practical Experience and Computational Estimation of Their Effects

by Tomáš Michálek, Petr Voltr, Stanislava Liberová and Jiří Šlapák

Machines 2025, 13(11), 1041; https://doi.org/10.3390/machines13111041 - 11 Nov 2025

This paper deals with solid lubricants for the wheel–rail interface; the topic is viewed from two different but complementary perspectives. By means of simulations, the potential contribution of these lubricants, applied for purposes of wheel flange lubrication on curved tracks, to the reduction [...] Read more.

This paper deals with solid lubricants for the wheel–rail interface; the topic is viewed from two different but complementary perspectives. By means of simulations, the potential contribution of these lubricants, applied for purposes of wheel flange lubrication on curved tracks, to the reduction in the wheel–rail wear level is estimated. Further, the relationship between frictional work in wheel–rail contact and guiding forces is investigated. The aim of this paper is to contribute to the knowledge of a physical basis for this relationship and to help understand the capability of these quantities to quantify the damaging effects of running vehicles on curved tracks. The mechanism of the observed increase in quasi-static guiding force on the leading wheel with lubricated wheel flanges is described in detail, using different quantities characterizing the steady running of a vehicle through a curve. The limitation of the contribution of wheel flange lubrication to the reduction in total frictional power on all wheels of the vehicle is also explained. In the second part, attention is paid to a practical assessment of the performance of solid lubricant samples using the testing methodology of the European standards EN 15427-2-1 and EN 16028. The aim of this part of the paper is to summarize the authors’ experience with twin-disc machine measurements, showing imperfections in the standardized testing methodology, as well as the significantly different performance of various solid lubricant samples, which is influenced by many factors. Based on their experience, further research on solid lubricant performance using wheel–rail roller rigs is outlined. Full article

(This article belongs to the Section Friction and Tribology)

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23 pages, 2407 KB

Open AccessArticle

Chain-Based Outlier Detection: Interpretable Theories and Methods for Complex Data Scenarios

by Huiwen Dong, Meiliang Liu, Shangrui Wu, Qing-Guo Wang and Zhiwen Zhao

Machines 2025, 13(11), 1040; https://doi.org/10.3390/machines13111040 - 11 Nov 2025

Outlier detection is a critical task in the intelligent operation and maintenance (O&M) of transportation equipment, as it helps ensure the safety and reliability of systems like high-speed trains, aircraft, and intelligent vehicles. Nearest neighbor-based detectors generally offer good interpretability, but often struggle [...] Read more.

Outlier detection is a critical task in the intelligent operation and maintenance (O&M) of transportation equipment, as it helps ensure the safety and reliability of systems like high-speed trains, aircraft, and intelligent vehicles. Nearest neighbor-based detectors generally offer good interpretability, but often struggle with complex data scenarios involving diverse data distributions and various types of outliers, including local, global, and cluster-based outliers. Moreover, these methods typically rely on predefined contamination, which is a critical parameter that directly determines detection accuracy and can significantly impact system reliability in O&M environments. In this paper, we propose a novel chain-based theory for outlier detection with the aim to provide an interpretable and transparent solution for fault detection. We introduce two methods based on this theory: Cascaded Chain Outlier Detection (CCOD) and Parallel Chain Outlier Detection (PCOD). Both methods identify outliers through sudden increases in chaining distances, with CCOD being more sensitive to local data distributions, while PCOD offers higher computational efficiency. Experimental results on synthetic and real-world datasets demonstrate the superior performance of our methods compared to existing state-of-the-art techniques, with average improvements of 11.3% for CCOD and 14.5% for PCOD. Full article

(This article belongs to the Section Machines Testing and Maintenance)

22 pages, 4092 KB

Open AccessArticle

Design and Experiment of a Roller-Brush Type Harvesting Device for Dry Safflower Based on Plant Clamping and Pose Adjustment

by Chunjiao Ma, Haifeng Zeng, Yun Ge, Guotao Li, Botao He and Yangyang Guo

Machines 2025, 13(11), 1039; https://doi.org/10.3390/machines13111039 - 11 Nov 2025

To address the challenges of low efficiency and high damage rates in dryland safflower harvesting, a roller-brush type harvesting device was developed. The design was developed following a detailed analysis of the spatial distribution and mechanical characteristics of safflower plants. The pose adjustment [...] Read more.

To address the challenges of low efficiency and high damage rates in dryland safflower harvesting, a roller-brush type harvesting device was developed. The design was developed following a detailed analysis of the spatial distribution and mechanical characteristics of safflower plants. The pose adjustment process begins with helical grooves clamping and contacting the plant stem. The propulsion action of the helix then forces the stem to undergo a predetermined deflection displacement. The optimal picking pose occurs when the plant’s longitudinal axis is perpendicular to the rotational axis of the picking roller brush. In this position, the picking roller brush shears the filaments at the necking zone through gentle contact with the fruit balls. This mechanism transforms the traditional pull-off separation into a low-damage shear-separation mode. The Box–Behnken test was designed to find the optimal combination of parameters for picking: picking roller brush speed of 282.5 r/min, roller brush spacing of 3.7 mm, and brush bristle diameter of 0.1 mm. Verification tests showed the picking, damage and fruit injury rates were 92.4%, 7.1% and 1.2%, respectively, with standard deviations of 5.42%, 0.51%, and 0.08%. The harvesting efficiency reached 0.053 hm²/h, 8.48 to 12.01 times higher than manual harvesting. Full article

(This article belongs to the Section Machine Design and Theory)

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34 pages, 3270 KB

Open AccessArticle

Design-Orientated Optimization and Motion Planning of a Parallel Platform for Improving Performance of an 8-DOF Hybrid Surgical Robot

by Asna Kalsoom, Muhammad Faizan Shah, Zareena Kausar, Faizan Khan Durrani, Syed Zahid Hussain and Muhammad Umer Farooq

Machines 2025, 13(11), 1038; https://doi.org/10.3390/machines13111038 - 9 Nov 2025

The emergence of surgical robots has revolutionized complex operations, improving precision, lowering operating risks, and shortening recovery periods. Given the merits, an eight degrees of freedom (DOF) hybrid surgical robot (HSR) has been proposed, which leverages the benefits of both serial and parallel [...] Read more.

The emergence of surgical robots has revolutionized complex operations, improving precision, lowering operating risks, and shortening recovery periods. Given the merits, an eight degrees of freedom (DOF) hybrid surgical robot (HSR) has been proposed, which leverages the benefits of both serial and parallel manipulators. However, its performance is hindered by the constrained range of motion of its parallel platform. To address the issue, this research presents a systematic approach for designing and optimizing the proposed HSR. The first step is the design of the HSR, followed by a multi-stage design analysis of its parallel platform, concentrating on kinematic, geometrical, and singularity analysis. Higher values of the condition number indicate singular configurations in the platform’s workspace, highlighting the need for an optimized design. For optimization of the platform, performance parameters like global condition number (GCN), actuator forces, and stiffness are identified. Initially, the design is optimized by targeting GCN only through a genetic algorithm (GA). This approach compromised the other parameters and raised the need for simultaneous optimization employing a non-dominated sorting genetic algorithm (NSGA II). It offered a better trade-off between performance parameters. To further assess the working of the optimized parallel platform, workspace analysis and motion planning of a predefined trajectory have been performed. Full article

(This article belongs to the Special Issue Mechanical Design of Parallel Manipulators)

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18 pages, 7174 KB

Open AccessArticle

Stress–Strain Evolution and Multi-Pass Process Optimization in Mandrel-Free Hot Spinning of Wind Tunnel Nozzles

by Piyao Liu, Linsen Song, Zhenhui Li, Wei Liang, Ziwei Jiang, Xiaosha Tang, Qiang Gao and Shuang Guo

Machines 2025, 13(11), 1037; https://doi.org/10.3390/machines13111037 - 9 Nov 2025

Traditional manufacturing methods of wind tunnel nozzles are often cumbersome, time-consuming, and costly. The study of spinning forming technology for wind tunnel nozzles provides a pathway to improve manufacturing efficiency while reducing both cost and production cycle. However, when processing alloy steel (20MnMo), [...] Read more.

Traditional manufacturing methods of wind tunnel nozzles are often cumbersome, time-consuming, and costly. The study of spinning forming technology for wind tunnel nozzles provides a pathway to improve manufacturing efficiency while reducing both cost and production cycle. However, when processing alloy steel (20MnMo), challenges arise due to large deformation, high-temperature loading, and complex wall-thickness control. To address these issues, this work proposes a die-less multi-pass hot spinning process. A three-dimensional dynamic explicit finite element model was developed to simulate the stress–strain evolution during multi-pass spinning. In the first pass, an L9 orthogonal experimental design was applied to analyze the influence of spinning parameters on forming stress and plastic deformation capacity, thereby determining the optimal combination of workpiece rotation speed, axial feed, and radial feed rates. The optimized design strategy was subsequently extended to ten passes. Based on simulation results, hot spinning experiments were conducted, followed by precision machining of the nozzle’s inner and outer surfaces. Inspection results indicated that the deviations in contour and wall thickness between simulation predictions and actual specimens were both less than 0.5%. This study establishes an integrated process route combining numerical simulation, hot spinning, and finishing, providing both theoretical support and practical guidance for the high-precision and high-stability manufacturing of complex thin-walled nozzle structures. Full article

(This article belongs to the Section Machine Design and Theory)

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17 pages, 1030 KB

Open AccessArticle

Genetic Algorithm-Based Optimization of Velocity Profiles for Multi-Robot Collision Avoidance

by Luca Marseglia, Alberto Vale and Giuseppe Di Gironimo

Machines 2025, 13(11), 1036; https://doi.org/10.3390/machines13111036 - 9 Nov 2025

Efficient coordination of multiple mobile robots is essential in automated systems, especially when robots must follow predefined paths while avoiding collisions. This paper proposes a centralized optimization framework using Genetic Algorithms to optimize the velocity profiles of a system of robots without altering [...] Read more.

Efficient coordination of multiple mobile robots is essential in automated systems, especially when robots must follow predefined paths while avoiding collisions. This paper proposes a centralized optimization framework using Genetic Algorithms to optimize the velocity profiles of a system of robots without altering their paths. The goal is to minimize task completion time and energy consumption while ensuring collision avoidance. Three Genetic Algorithm-based methods are introduced: Maximum Velocity Optimization, Slow-Down Segment Single-Objective Optimization and Slow-Down Segment Multi-Objective Optimization. The first method adjusts each robot’s maximum velocity along its entire path, whereas the second introduces a slow-down segment only at the start of its path. While these two approaches only optimize task completion time, the third method contains a multi-objective formulation, producing solutions that balance time and energy. Methods such as Brute-Force and Prioritized Planning were used as baseline methods for comparison. Simulation results indicate that the proposed strategies significantly outperform the baseline methods. Furthermore, the second method achieves better results than the first by introducing more targeted velocity adjustments, while the third further enhances flexibility by offering a range of trade-offs between task completion time and energy consumption. Scalability and computational cost remain critical challenges, especially as the number of robots increases. Full article

(This article belongs to the Section Automation and Control Systems)

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18 pages, 2762 KB

Open AccessArticle

Performance Analysis and Optimization of a Bio-Inspired Spider-Web-Shaped Energy Absorbing Component for Legged Landers

by Xueao Liu, Hui Wang, Kai Yang, Bin Zhang, Xuecong Wang, Kaiting Liu and Shiming Zhou

Machines 2025, 13(11), 1035; https://doi.org/10.3390/machines13111035 - 8 Nov 2025

Inspired by the structural characteristics of natural spider webs, a simplified configuration composed of multi-layer regular polygons was developed to design a novel energy absorbing component for legged landers. To investigate its compressive energy-absorption behavior, a parameterized finite element model (FEM) was established. [...] Read more.

Inspired by the structural characteristics of natural spider webs, a simplified configuration composed of multi-layer regular polygons was developed to design a novel energy absorbing component for legged landers. To investigate its compressive energy-absorption behavior, a parameterized finite element model (FEM) was established. By integrating optimized Latin hypercube experimental design with the FEM, the energy absorption characteristics under varying structural parameters were evaluated. Based on the FEM results, response surface methodology was employed to construct surrogate models that capture the mapping relationships between design parameters and performance indices. Using these surrogate models, the energy-absorbing component was optimized under three different ranges of average buffering force. Three optimized components with distinct average buffering forces were selected and connected in series, and their force–displacement responses during compression were computed through finite element simulations. The obtained response curves were incorporated into a multibody dynamics model of a Mars lander to verify performance, demonstrating that the lander can achieve effective soft landing. Full article

(This article belongs to the Section Machine Design and Theory)

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21 pages, 5754 KB

Open AccessArticle

Optimization Design of Blade Profile Parameters of Low-Speed and High-Torque Turbodrill Based on GA-LSSVM-MOPSO-TOPSIS Method

by Yulin Gao, Yu Wang, Guosong Chen, Jia Yan, Lingrong Kong and Yuzuo Lu

Machines 2025, 13(11), 1034; https://doi.org/10.3390/machines13111034 - 7 Nov 2025

The exploration and development of deep marine resources are faced with the problems of poor drill ability and serious wellbore instability in high temperature and high-pressure formations. The bottom hole dynamic drilling tool with low vibration characteristics is the best choice for deep [...] Read more.

The exploration and development of deep marine resources are faced with the problems of poor drill ability and serious wellbore instability in high temperature and high-pressure formations. The bottom hole dynamic drilling tool with low vibration characteristics is the best choice for deep well drilling. The output torque of the turbodrill is relatively small, which limits its application potential. In this study, intelligent optimization algorithms are used to improve the blade shape design to improve its output torque. Firstly, based on the moment of momentum theorem, the key blade profile parameters and range affecting the output characteristics of the turbodrill are analyzed and summarized. Subsequently, the five-order polynomial method and UG software (version 10.0) are used to complete the three-dimensional configuration of the bent-twisted blade. Then, based on the GA-LSSVM-MOPSO-TOPSIS intelligent optimization algorithm, the two-dimensional and three-dimensional modeling design parameters under the optimal hydraulic performance are optimized, and the accuracy of the intelligent optimization algorithm and parameters is verified by CFD simulation analysis. The results show that the hydraulic efficiency of only 4.9% is sacrificed, and the output torque is increased by 36.61%, which significantly improves the hydraulic performance of the turbodrill and provides guidance for the design of low-speed and high-torque turbodrills. Full article

(This article belongs to the Section Machines Testing and Maintenance)

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15 pages, 7933 KB

Open AccessArticle

A Framework for Testing and Evaluation of Automated Valet Parking Using OnSite and Unity3D Platforms

by Ouchan Chen, Lei Chen, Junru Yang, Hao Shi, Lin Xu, Haoran Li, Weike Lu and Guojing Hu

Machines 2025, 13(11), 1033; https://doi.org/10.3390/machines13111033 - 7 Nov 2025

Automated valet parking (AVP) is a key component of autonomous driving systems. Its functionality and reliability need to be thoroughly tested before road application. Current testing technologies are limited by insufficient scenario coverage and lack of comprehensive evaluation indices. This study proposes an [...] Read more.

Automated valet parking (AVP) is a key component of autonomous driving systems. Its functionality and reliability need to be thoroughly tested before road application. Current testing technologies are limited by insufficient scenario coverage and lack of comprehensive evaluation indices. This study proposes an AVP testing and evaluation framework using OnSite (Open Naturalistic Simulation and Testing Environment) and Unity3D platforms. Through scenario construction based on field-collected data and model reconstruction, a testing scenario library is established, complying with industry standards. A simplified kinematic model, balancing simulation accuracy and operational efficiency, is applied to describe vehicle motion. A multidimensional evaluation system is developed with completion rate as a primary index and operation performance as a secondary index, which considers both parking efficiency and accuracy. Over 500 AVP algorithms are tested on the OnSite platform, and the testing results are evaluated through the Unity3D platform. The performance of the top 10 algorithms is analyzed. The evaluation platform is compared with CARLA simulation platform and field vehicle testing. This study finds that the framework provides an effective tool for AVP testing and evaluation; a variety of high-level AVP algorithms are developed, but their flexibility in complex dynamic scenarios has limitations. Future research should focus on exploring more sophisticated learning-based algorithms to enhance AVP adaptability and performance in complex dynamic environment. Full article

(This article belongs to the Special Issue Control and Path Planning for Autonomous Vehicles)

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21 pages, 7263 KB

Open AccessArticle

Analysis of Driver Takeover Performance in Autonomous Vehicles Based on Generalized Estimating Equations

by Min Duan, Lian Xie, Jianrong Cai, Junru Yang and Haoran Li

Machines 2025, 13(11), 1032; https://doi.org/10.3390/machines13111032 - 7 Nov 2025

Current autonomous vehicles require human drivers to take over control during emergencies or in environments the system cannot handle. During other periods, drivers are permitted to engage in non-driving-related tasks. It is essential to investigate how the immersion in non-driving-related tasks affects drivers’ [...] Read more.

Current autonomous vehicles require human drivers to take over control during emergencies or in environments the system cannot handle. During other periods, drivers are permitted to engage in non-driving-related tasks. It is essential to investigate how the immersion in non-driving-related tasks affects drivers’ takeover performance under different scenarios. To address this, a mixed-design simulated driving experiment was conducted with 40 participants, incorporating three non-driving-related tasks (no task, watch video, play game), three takeover request lead times (3 s, 5 s, 7 s), and two obstacle types (dynamic, static). The takeover process was divided into three phases: preparation, obstacle avoidance, and recovery. Analysis of the areas of interest showed that engaging in non-driving-related tasks substantially reduced drivers’ visual attention tothe road ahead during the preparation phase. The Generalized Estimating Equations method was employed to investigate the effects of various factors on takeover performance. Model results showed that scenarios with static obstacles and longer takeover request times led to a significant reduction in mean lane deviation but a significant increase in the standard deviation of lane deviation, suggesting improved lateral control performance. A significant interaction was observed between the watch video task and static obstacles, which corresponded to a notable decrease in the mean vehicle speed during obstacle avoidance. Performance in the recovery phase was strongly predicted by that in the obstacle avoidance phase, indicating that the stability of the avoidance maneuver is a critical determinant of the subsequent recovery. These findings offer valuable insights for managing non-driving-related tasks and setting appropriate takeover request timings in automated driving systems. Full article

(This article belongs to the Special Issue Control and Path Planning for Autonomous Vehicles)

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16 pages, 2896 KB

Open AccessArticle

Application of Various Artificial Neural Network Algorithms for Regression Analysis in the Dynamic Modeling of a Three-Link Planar RPR Robotic Arm

by Onur Denizhan

Machines 2025, 13(11), 1031; https://doi.org/10.3390/machines13111031 - 7 Nov 2025

The design, control, simulation and animation of robotic systems heavily depend on dynamic modeling. A variety of studies have explored different dynamic modeling methodologies applied to diverse robotic mechanisms. Artificial neural networks (ANNs) have proven their value in engineering design in recent years, [...] Read more.

The design, control, simulation and animation of robotic systems heavily depend on dynamic modeling. A variety of studies have explored different dynamic modeling methodologies applied to diverse robotic mechanisms. Artificial neural networks (ANNs) have proven their value in engineering design in recent years, enhancing the understanding of complex mechanisms as well as shortening experimental periods and decreasing related expenses. This study investigates the application of various neural network algorithms for the analysis of a custom-designed three-link planar revolute–prismatic–revolute (RPR) robotic arm mechanism. Initially, the Euler–Lagrange equations of motion for the RPR mechanism are derived. Joint accelerations are then computed under different mass configurations of the robotic links, resulting in a dataset comprising 204 joint acceleration samples. Six distinct neural network models are subsequently employed to perform regression analysis on the collected data. The primary objective of this study is to analyze the relationship between joint accelerations and varying link masses under constant joint torques and forces, while its secondary aim is to present a representative application of neural networks as regression learners for the dynamic modeling of robotic mechanisms. The approach outlined in this study allows users to select appropriate neural network algorithms for use in specific applications, considering the wide range of available algorithms. Link mass variations and their effects on joint accelerations are investigated, establishing a basis for the modeling of robotic dynamics using regression-based neural networks. The results indicate that the optimizable neural network algorithm produces the best regression accuracy results, although the other models maintain similar performance levels. Full article

(This article belongs to the Section Machine Design and Theory)

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20 pages, 8241 KB

Open AccessArticle

Prediction of Component Erosion in a Francis Turbine Based on Sediment Particle Size

by Bingning Chen, Yan Jin, Ying Xue, Haojie Liang and Fangping Tang

Machines 2025, 13(11), 1030; https://doi.org/10.3390/machines13111030 - 7 Nov 2025

Erosion caused by sediment-laden flow significantly affects the efficiency and durability of Francis turbines. In this study, the Euler–Lagrange multi-phase flow model was employed to simulate solid-liquid two-phase flow with different sediment particle sizes to analyze erosion characteristics in turbine components. The results [...] Read more.

Erosion caused by sediment-laden flow significantly affects the efficiency and durability of Francis turbines. In this study, the Euler–Lagrange multi-phase flow model was employed to simulate solid-liquid two-phase flow with different sediment particle sizes to analyze erosion characteristics in turbine components. The results show that the maximum erosion rate of the runner blades is positively correlated with particle impact velocity, confirming that impact velocity is the dominant factor influencing local material removal. The total erosion rate of the runner blades, guide vanes, and draft tube corresponds closely with vorticity, indicating that vortex-induced flow separation accelerates particle–wall collisions and intensifies erosion. Both vorticity and erosion exhibit a nonlinear variation with particle size, reaching a minimum at 0.05 mm. These findings establish clear qualitative and quantitative relationships between erosion and key flow parameters, providing theoretical guidance for understanding and mitigating sediment-induced wear in Francis turbines. Full article

(This article belongs to the Special Issue Advanced Research and Development in Fluid Machinery: Design, Optimization, and Applications)

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25 pages, 4543 KB

Open AccessArticle

Anisotropic Plasticity in Sheet Metal Forming: Experimental and Numerical Analysis of Springback Using U-Bending Test

by Lotfi Ben Said, Abir Bouhamed, Mondher Wali, Taoufik Kamoun, Muapper Alhadri, Badreddine Ayadi, Sattam Alharbi and Wajdi Rajhi

Machines 2025, 13(11), 1029; https://doi.org/10.3390/machines13111029 - 7 Nov 2025

Accurate forecasting of springback continues to pose a significant challenge in sheet metal forming processes. The present paper presents a numerical model designed for the precise prediction of springback, allowing for a deeper understanding of plasticity behavior during cold forming operations in sheet [...] Read more.

Accurate forecasting of springback continues to pose a significant challenge in sheet metal forming processes. The present paper presents a numerical model designed for the precise prediction of springback, allowing for a deeper understanding of plasticity behavior during cold forming operations in sheet metals. The key contribution of this model is the introduction of a non-associated anisotropic constitutive model featuring nonlinear mixed isotropic–kinematic hardening. This model is derived from Hill’48 quadratic function and it was implemented into ABAQUS 6.13 software environment through the user defined UMAT subroutine. For improved precision, kinematic hardening parameters specific to 5083 aluminum sheet metal were meticulously derived from cyclic shear experiments. Our results demonstrate the model’s strong capability in predicting springback during the U-bending operation, achieving remarkable accuracy. The design of experiments DOE is used as a statistical method to optimize the number of experiments and analyze the effects of key input factors. In this study, sheet thickness, punch speed, and sampling angle relative to the rolling direction (RD) are examined at different levels to assess their impact on folding force and springback. The strong agreement between experimental results and theoretical predictions confirms the accuracy and reliability of the proposed models in estimating folding force and springback. Full article

(This article belongs to the Special Issue Advanced Technologies for Sheet Metal Forming)

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19 pages, 4979 KB

Open AccessArticle

Pediatric Lower Limb Rehabilitation Training System with Soft Exosuit and Quantitative Partial Body Weight Support

by Dezhi Liang, Shuk-Fan Tong, Hsuan-Yu Lu, Minghao Liu, Zhen Wang, Tian Xing, Hongliu Yu and Raymond Kai-Yu Tong

Machines 2025, 13(11), 1028; https://doi.org/10.3390/machines13111028 - 7 Nov 2025

The pediatric period is a crucial window for motor function learning and growth. Individuals with central nervous system injuries like cerebral palsy commonly display severe crouch gait in the lower limbs. Hyperflexion of the knee joints promotes the forward trunk and increases reliance [...] Read more.

The pediatric period is a crucial window for motor function learning and growth. Individuals with central nervous system injuries like cerebral palsy commonly display severe crouch gait in the lower limbs. Hyperflexion of the knee joints promotes the forward trunk and increases reliance on the handle frame of a walker for support. In this study, we developed a quantitative partial body weight training system integrated with a soft pneumatic exosuit to assist the knee extension during the stance phase of the gait cycle. In the preliminary results for five pediatric cerebral palsy subjects, compared to the baseline condition, excessive knee flexion ameliorated with the assistance of the soft pneumatic exosuit. The peak knee extension and range of motion increased by 19.72° (±3.47°) and 15.46° (±5.06°), respectively. With exosuit assistance, the subjects demonstrated improved gait retraining compared to baseline. They were able to bear significantly more body weight on their affected limb, as evidenced by a 33.3% increase in the fraction of body weight measured by the force plate. Additionally, they relied less on the handrail for support during walking. With more extended knee joints to bear the load over gravity, the pediatric subjects transferred the reliance from external support and upper limbs back to the lower limbs as a more independent status during the loading response to terminal stance. Full article

(This article belongs to the Section Robotics, Mechatronics and Intelligent Machines)

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23 pages, 3997 KB

Open AccessArticle

Cutting Tool Remaining Useful Life Prediction Using Multi-Sensor Data Fusion Through Graph Neural Networks and Transformers

by Xin Chen and Kai Cheng

Machines 2025, 13(11), 1027; https://doi.org/10.3390/machines13111027 - 6 Nov 2025

In the context of Industry 4.0 and smart manufacturing, predicting cutting tool remaining useful life (RUL) is crucial for enabling and enhancing the reliability and efficiency of CNC machining. This paper presents an innovative predictive model based on the data fusion architecture of [...] Read more.

In the context of Industry 4.0 and smart manufacturing, predicting cutting tool remaining useful life (RUL) is crucial for enabling and enhancing the reliability and efficiency of CNC machining. This paper presents an innovative predictive model based on the data fusion architecture of Graph Neural Networks (GNNs) and Transformers to address the complexity of shallow multimodal data fusion, insufficient relational modeling, and single-task limitations simultaneously. The model harnesses time-series data, geometric information, operational parameters, and phase contexts through dedicated encoders, employs graph attention networks (GATs) to infer complex structural dependencies, and utilizes a cross-modal Transformer decoder to generate fused features. A dual-head output enables collaborative RUL regression and health state classification of cutting tools. Experiments are conducted on a multimodal dataset of 824 entries derived from multi-sensor data, constructing a systematic framework centered on tool flank wear width (VB), which includes correlation analysis, trend modeling, and risk assessment. Results demonstrate that the proposed model outperforms baseline models, with MSE reduced by 26–41%, MAE by 33–43%, R² improved by 6–12%, accuracy by 6–12%, and F1-Score by 7–14%. Full article

(This article belongs to the Special Issue Artificial Intelligence in Mechanical Engineering Applications)

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23 pages, 2795 KB

Open AccessArticle

Research on Position-Tracking Control Method for Fatigue Test Bed of Absorber Based on SCHO and Fuzzy Adaptive LADRC

by Muzhi Zhu, Zhilei Chen, Xingrong Huang, Xujie Zhang and Chao Xun

Machines 2025, 13(11), 1026; https://doi.org/10.3390/machines13111026 - 6 Nov 2025

A collaborative control strategy combining the hyperbolic sine-cosine optimization (SCHO) algorithm with fuzzy adaptive linear active disturbance rejection control is proposed to address the nonlinearity and uncertainties in the hydraulic position servo system of shock absorber test benches. First, based on the dynamic [...] Read more.

A collaborative control strategy combining the hyperbolic sine-cosine optimization (SCHO) algorithm with fuzzy adaptive linear active disturbance rejection control is proposed to address the nonlinearity and uncertainties in the hydraulic position servo system of shock absorber test benches. First, based on the dynamic characteristics of the shock absorber fatigue test bench and the tested shock absorber, a linearized model of the valve-controlled hydraulic cylinder and its load was established. The coupling mechanism of system parameter perturbation and disturbance was also analyzed. A third-order LADRC (Linear Active Disturbance Rejection Control) was designed considering the linear model characteristics of the test bench hydraulic servo system model to quickly estimate internal system disturbances and perform real-time compensation. Secondly, a multi-objective optimization function was constructed by integrating system performance indicators and incorporating controller and observer bandwidths into the optimization objectives. The SCHO algorithm was used for the global search and optimization of key LADRC parameters. To enhance the controller’s adaptive capability of modeling uncertainties and external disturbances, a fuzzy adaptive module was introduced to adjust control gains online according to errors and their rates of change, further improving system robustness and dynamic performance. The results show that compared with traditional PID, under different working conditions, the proposed method reduced the maximum tracking error, overshoot, and system response time by an average of 45%, from 15% to 5%, and by approximately 30%, respectively. Meanwhile, the parameter combination obtained via SCHO effectively avoids the limitations of manual parameter tuning, significantly improving control accuracy and energy utilization. The simulation results indicate that this method can significantly enhance position-tracking accuracy compared with traditional LADRC, providing an effective solution for position-tracking control in hydraulic servo testing systems. Full article

(This article belongs to the Section Automation and Control Systems)

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29 pages, 6683 KB

Open AccessArticle

A Hybrid Flow Energy Harvester to Power an IoT-Based Wireless Sensor System for the Digitization and Monitoring of Pipeline Networks

by Wahad Ur Rahman and Farid Ullah Khan

Machines 2025, 13(11), 1025; https://doi.org/10.3390/machines13111025 - 6 Nov 2025

This study presents a novel energy harvesting device that combines piezoelectric and electromagnetic transduction to extract energy from fluid flow within pipelines to supply power to wireless sensor nodes for the digital transformation of pipeline networks. The proposed harvester consisted of a permanent [...] Read more.

This study presents a novel energy harvesting device that combines piezoelectric and electromagnetic transduction to extract energy from fluid flow within pipelines to supply power to wireless sensor nodes for the digital transformation of pipeline networks. The proposed harvester consisted of a permanent magnet, an unimorph circular piezoelectric plate, an adjustable housing, two wound coils, and a coil holder. In laboratory tests, the harvester demonstrated an ability to produce 831.7 µW of AC power and 680 µW of DC power at a flow pressure of 2.90 kPa and a flow rate of 11.083 L/s. The energy harvester charged a power backup from 1.01 V to 4.49 V in a time duration of 120 min. Additionally, a low-power wireless system for monitoring pipeline pressure was developed and integrated with this energy harvesting system. By incorporating this technology into the digitization of pipeline systems, continuous power generation is possible, ensuring the reliable and autonomous operation of sensors for real-time data collection and monitoring of the pipeline network. The hybrid flow energy harvester surpasses both earlier standalone electromagnetic and piezoelectric flow energy harvesters. Full article

(This article belongs to the Special Issue Recent Progress on Vibration-Based Energy Harvesting and Its Related Applications)

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15 pages, 15245 KB

Open AccessArticle

Impact of Static Rotor Eccentricity on the NVH Behavior of Electric Permanent Magnet Synchronous Machines

by Julius Müller, Georg Jacobs, Rasim Dalkiz and Stefan Wischmann

Machines 2025, 13(11), 1024; https://doi.org/10.3390/machines13111024 - 6 Nov 2025

In comparison to internal combustion engines, which usually have low frequency, broadband excitations, in electric vehicles, tonal excitations from the electric drivetrain are noticeable and disturbing. As the acoustic and structural dynamic behavior, often referred to as noise, vibration, and harshness (NVH), strongly [...] Read more.

In comparison to internal combustion engines, which usually have low frequency, broadband excitations, in electric vehicles, tonal excitations from the electric drivetrain are noticeable and disturbing. As the acoustic and structural dynamic behavior, often referred to as noise, vibration, and harshness (NVH), strongly influences customers’ quality perceptions, optimizing it is a key challenge in development. This study investigates the influence of static rotor–stator eccentricity on the NVH behavior of an electric drivetrain using a transient elastic multibody simulation (eMBS) model incorporating non-linear gear meshing, bearing contact, and electromagnetic forces. The analysis identifies the 36th order excitation of the electric machine as the dominant source, leading to a maximum total acceleration level of 152 dB. Two specific excitation directions were found to reduce this amplitude most effectively. However, varying the amount of static eccentricity in these directions resulted in only minor vibration reductions (<1.5 dB). The findings indicate that the symmetric mode shapes of the cylindrical housing govern the response, indicating that addressing the excitability of housing modes by developing asymmetric housing designs could offer a more effective approach for NVH optimizations of electric drivetrains. Full article

(This article belongs to the Special Issue Active Vibration Control System)

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16 pages, 2221 KB

Open AccessArticle

A Comparative Study of Natural and Exact Elastic Balancing Methods for the RR-4R-R Manipulator

by Luca Bruzzone, Matteo Verotti and Pietro Fanghella

Machines 2025, 13(11), 1023; https://doi.org/10.3390/machines13111023 - 6 Nov 2025

If elastic elements are introduced into the mechanical architecture of a robotic manipulator, a free vibration response (Natural Motion) arises that can be exploited to reduce energy consumption in cyclic motions, such as pick-and-place tasks. In this work, this approach is applied to [...] Read more.

If elastic elements are introduced into the mechanical architecture of a robotic manipulator, a free vibration response (Natural Motion) arises that can be exploited to reduce energy consumption in cyclic motions, such as pick-and-place tasks. In this work, this approach is applied to the RR-4R-R manipulator, which is derived from the SCARA robot by replacing the prismatic joint that drives the vertical motion of the end-effector with a four-bar mechanism. This mechanical modification lowers friction and facilitates the introduction of a balancing elastic element. If the elastic element is designed to provide indifferent equilibrium at any position (exact elastic balancing), the actuators need only to overcome the inertial forces; this approach is convenient for slow motions. Conversely, if the elastic element balances gravity exactly only in the median vertical position of the end-effector, Natural Motion around this position arises, and it can be exploited to reduce energy consumption in fast cyclic motions, where inertial forces become prevalent. The threshold of convenience between exact balancing and natural balancing has been evaluated for the RR-4R-R robot by means of a multibody model, assessing different performance indices: the maximum torque of the four-bar actuator, the integral control effort, and the mechanical energy. The simulation campaign was carried out considering different trajectory shapes and the influence of finite stop phases, highlighting the potential benefits of exploiting Natural Motion in robotized manufacturing lines. Full article

(This article belongs to the Special Issue Mechanism and Machine Science for Sustainable Development Goals: Contributions from the I4SDG 2025 Conference)

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