Article
Engineering, Manufacturing
Xing Zhou, Guosheng Wang, Dexiang Li, Qi Wang, Keming Zhu, Yaya Hao, Yueyang Xu, Neng Li
Summary: This study successfully synthesized polyurethane elastomer by using degraded products from waste PET, and fabricated composites with carbon nanotubes for strain sensors. The composites showed good mechanical and durability performance, indicating a potential method for recycling waste PET into valuable and functional materials.
COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Leonel Rozo, Andras G. Kupcsik, Philipp Schillinger, Meng Guo, Robert Krug, Niels van Duijkeren, Markus Spies, Patrick Kesper, Sabrina Hoppe, Hanna Ziesche, Mathias Buerger, Kai O. Arras
Summary: Robotic manipulation is undergoing a profound paradigm shift due to increasing demand for flexible manufacturing systems and advancements in sensing, learning, optimization, and hardware. This shift requires robots to observe and reason about their workspace and possess the skills to complete various assembly processes in weakly-structured settings. Enabling on-site teaching of robots while managing the complexity of perception, control, motion planning, and reaction to unexpected situations remains a significant challenge.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Engineering, Manufacturing
Xiaohua Lv, Yufei Ling, Kaiyou Tang, Changyu Qiao, Lihua Fu, Chuanhui Xu, Baofeng Lin, Yen Wei
Summary: In this study, a new type of hydrogel with high matched skin modulus, strong adhesion, and long-lasting antibacterial properties was developed. The hydrogel maintained high sensing performance even under extreme conditions. This research provides a new approach for the development of next-generation skin-like hydrogel sensors.
COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Changchun Liu, Dunbing Tang, Haihua Zhu, Qingwei Nie, Wei Chen, Zhen Zhao
Summary: Industrial robots play a vital role in intelligent manufacturing equipment, but often require pre-programmed motion planning schemes. This research proposes an augmented reality-assisted interaction approach using deep reinforcement learning and cloud-edge orchestration for user-friendly robot teaching.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Jiawei Wu, Xiaowei Tang, Shihao Xin, Chenyang Wang, Fangyu Peng, Rong Yan
Summary: This research investigates the end dynamic characteristics of a milling robot in vibration control and chatter avoidance. The directional distribution of the end dynamic characteristics is studied by proving the directionality of the end modal vibration and modeling the distribution of the end dynamic compliance. The research provides a new theoretical basis for studying the robotic end dynamic characteristics and their applications.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Engineering, Manufacturing
N. Lorenz, P. Hennes, K. Fischer, Ch. Hopmann
Summary: This study aims to understand the formation of surface waviness during cooling and post-curing of GFRP. Experimental and numerical results show that the viscoelastic behavior of the resin plays a crucial role in the formation of surface waviness.
COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING
(2024)
Article
Engineering, Manufacturing
Alex Arbogast, Andrzej Nycz, Mark W. Noakes, Peter Wang, Christopher Masuo, Joshua Vaughan, Lonnie Love, Randall Lind, William Carter, Luke Meyer, Derek Vaughan, Alex Walters, Steven Patrick, Jonathan Paul, Jason Flamm
Summary: This paper presents a new approach to multi-robot collaborative manufacturing using a multi-agent control paradigm. The method allows multiple robots to work together on a rotating platform, resulting in increased deposition rate and productivity.
ADDITIVE MANUFACTURING LETTERS
(2024)
Article
Computer Science, Interdisciplinary Applications
Xuewu Wang, Jin Gao, Xin Zhou, Xingsheng Gu
Summary: This article proposes an improved RRT* algorithm for autonomous path planning of welding robots with a large gantry structure. The method introduces the sampling pool mechanism, effectively shortens the search path length, and adopts the strategy of limiting the nearest node to improve efficiency.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Shenglin Wang, Jingqiong Zhang, Peng Wang, James Law, Radu Calinescu, Lyudmila Mihaylova
Summary: In Industry 5.0, Digital Twins provide flexibility and efficiency for smart manufacturing. Deep learning techniques are used to enhance the Digital Twin framework, enabling the detection and classification of human operators and robots during the manufacturing process. The framework shows promising results in accurately detecting and classifying actions of human operators and robots in various scenarios.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Jie Li, Zili Wang, Shuyou Zhang, Yaochen Lin, Lanfang Jiang, Jianrong Tan
Summary: This paper proposes a task incremental learning-based approach for digital-twin predictive modeling, which establishes a DT framework and information model, fine-tunes the model with pre-trained models and new task data, and achieves accurate prediction of customized metal tube bending forming process.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Engineering, Manufacturing
Yin Tao, Peishi Yu, Xin Zhang, Maoyang Li, Tao Liu, Junhua Zhao
Summary: This study aims to achieve displacement reconstruction through structure-sensing integration technology. A rapid iterative solution is proposed to cover the entire process from sensor-layout optimization to structure-sensing integrated fabrication then to displacement-reconstruction realization.
COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING
(2024)
Article
Engineering, Manufacturing
Shota Kawasaki, Kimiyoshi Naito, Osuke Ishida, Takehiro Shirai, Kiyoshi Uzawa
Summary: This study investigated the temperature distribution during ultrasonic welding of carbon fiber-reinforced polypropylene (CF/PP) using a thermographic camera. Single lap shear tests were performed on the welded joints. The experiments confirmed that the sonotrode amplitude affects the temperature distribution and joint quality, which in turn affects the failure mode. The half-width method was applied to assess the spread of the high-temperature region centered on the welding interface.
COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING
(2024)
Review
Engineering, Manufacturing
Mingyang Chen, Chi Zhang, Liao-Liang Ke
Summary: By employing a multi-scale modeling scheme, researchers have successfully resolved the stress distributions within the S2 layer at different moisture levels. They found that the shear stress on the fibril-matrix interface is smaller due to the heterogeneous nature of the microfibrils. Additionally, they demonstrated that the stress developed during dehydration is larger than during hydration, attributed to the softening of the amorphous polymers in the matrix upon water adsorption.
COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING
(2024)
Article
Engineering, Manufacturing
Fei Peng, Tingting Shan, Rongrui Chen, Jiulong Shi, Di Liu, Guoqiang Zheng, Chaojun Gao, Kun Dai, Chuntai Liu, Changyu Shen
Summary: Janus polymer films with distinct surface performance and potential applications were successfully prepared by vacuum-assisted hot-compressing method and spray coating. These films exhibit decent actuation performance and rapid selfpowered sensing property, and can be used for real-time acetone monitoring system.
COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING
(2024)
Article
Engineering, Industrial
Jing Huang, Zhifen Zhang, Rui Qin, Yanlong Yu, Guangrui Wen, Wei Cheng, Xuefeng Chen
Summary: In this study, a deep learning framework that combines interpretability and feature fusion is proposed for real-time monitoring of pipeline leaks. The proposed method extracts abstract feature details of leak acoustic emission signals through multi-level dynamic receptive fields and optimizes the learning process of the network using a feature fusion module. Experimental results show that the proposed method can effectively extract distinguishing features of leak acoustic emission signals, achieving higher recognition accuracy compared to typical deep learning methods. Additionally, feature map visualization demonstrates the physical interpretability of the proposed method in abstract feature extraction.
JOURNAL OF MANUFACTURING SYSTEMS
(2024)
Article
Engineering, Industrial
Yu Du, Jun-qing Li
Summary: This study investigates the group scheduling of a distributed flexible job shop problem using the concrete precast process. The proposed solution utilizes three coordinated double deep Q-networks (DQN) as a learn-to-improve reinforcement learning approach. The algorithm shows superiority in minimizing costs and energy consumption.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Manufacturing
Wenwu Zhang, Helezi Zhou, Bin Huang, Huamin Zhou, Xiongqi Peng
Summary: This paper investigates the tool-ply friction behavior of jute/PLA biocomposites in thermoforming. A pull-through friction testing device was developed to characterize the tool-ply friction behavior of jute/PLA prepreg at elevated temperature. The effects of alkali treatment, fiber orientation, normal force, and slipping velocity were studied, and a quantitative definition of tool-ply friction behavior was achieved. The results indicate a strong relationship between tool-ply friction behavior and woven and fiber structures, indicating hydrodynamic lubrication.
COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Yongxue Chen, Yaoan Lu, Ye Ding
Summary: This paper presents an optimization method for directly generating a six-degree-of-freedom toolpath for robotic flank milling. By optimizing the smoothness of the toolpath and the stiffness of the robot, the efficiency, accuracy, and finish of the machining are improved.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Engineering, Manufacturing
Oliver Nelson-Dummett, Geoffrey Rivers, Negar Gilani, Marco Simonelli, Christopher J. Tuck, Ricky D. Wildman, Richard J. M. Hague, Lyudmila Turyanska
Summary: The study presents a novel printing strategy, Off-the-Grid (OtG), which allows for refined positioning of individual droplets and enhanced resolution. It can be applied to different materials and has potential applications in electronics, wearable electronics, medical devices, and metamaterials.
ADDITIVE MANUFACTURING LETTERS
(2024)
Article
Engineering, Manufacturing
Congcong Lou, Bing Liu, Xufeng Cao, Liang Gao, Shouhu Xuan, Huaxia Deng, Xinglong Gong
Summary: The article introduces a magnetorheological metamaterial (MRM) with negative regulation and low-frequency bandgaps fabricated using dual-modulus 3D printing technology. Theoretical analysis and experimental results show that the bandgaps of this metamaterial can be adjusted under an external magnetic field, making it potentially applicable in the field of vibration isolation.
COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING
(2024)
