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When Embodied AI Meets Industry 5.0:Human-Centered smart manufacturing

IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 485-501页

作者： Jing Xu Qiyu Sun Qing-Long Han Yang Tang IEEE the Key Laboratory of smart manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology the School of Science Computing and Engineering Technologies Swinburne University of Technology

As embodied intelligence(EI), large language models(LLMs), and cloud computing continue to advance, Industry5.0 facilitates the development of industrial artificial intelligence(Ind AI) through cyber-physical-social systems(CPSSs) with a human-centric focus. These technologies are organized by the system-wide approach of Industry 5.0, in order to empower the manufacturing industry to achieve broader societal goals of job creation, economic growth, and green production. This survey first provides a general framework of smart manufacturing in the context of Industry 5.0. Wherein, the embodied agents, like robots, sensors, and actuators, are the carriers for Ind AI, facilitating the development of the self-learning intelligence in individual entities, the collaborative intelligence in production lines and factories(smart systems), and the swarm intelligence within industrial clusters(systems of smart systems). Through the framework of CPSSs, the key technologies and their possible applications for supporting the single-agent, multi-agent and swarm-agent embodied Ind AI have been reviewed, such as the embodied perception, interaction, scheduling, multi-mode large language models, and collaborative training. Finally, to stimulate future research in this area, the open challenges and opportunities of applying Industry 5.0 to smart manufacturing are identified and discussed. The perspective of Industry 5.0-driven manufacturing industry aims to enhance operational productivity and efficiency by seamlessly integrating the virtual and physical worlds in a human-centered manner, thereby fostering an intelligent, sustainable, and resilient industrial landscape.

关键词： Embodied AI human-centered manufacturing Industry 5.0 internet of things large multi-mode language models

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Recent advancements of nonlinear dynamics in mode coupled microresonators: a review

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Applied Mathematics and Mechanics(English Edition) 2025年第2期46卷 209-232页

作者： Xuefeng WANG Zhan SHI Qiqi YANG Yuzhi CHEN Xueyong WEI Ronghua HUAN Department of Engineering Mechanics MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University Department of Mechanics Key Laboratory of Soft Machines and Smart Devices of Zhejiang Province Zhejiang University State Key Laboratory for manufacturing Systems Engineering Xi'an Jiaotong University

Due to scale effects, micromechanical resonators offer an excellent platform for investigating the intrinsic mechanisms of nonlinear dynamical phenomena and their potential applications. This review focuses on mode-coupled micromechanical resonators,highlighting the latest advancements in four key areas: internal resonance, synchronization, frequency combs, and mode localization. The origin, development, and potential applications of each of these dynamic phenomena within mode-coupled micromechanical systems are investigated, with the goal of inspiring new ideas and directions for researchers in this field.

关键词： mode coupling micro-electro-mechanical system (MEMS) resonator nonlinear dynamics O32

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Lightweight multifunctional metamaterial with low-frequency vibroacoustic reduction and load-bearing performances

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Applied Mathematics and Mechanics(English Edition) 2025年第3期46卷 403-422页

作者： Qi JIA Dianlong YU Donghai HAN Jihong WEN National Key Laboratory of Equipment State Sensing and smart Support College of Intelligence Science and Technology National University of Defense Technology

Metamaterials can control and manipulate acoustic/elastic waves on a subwavelength scale using cavities or additional components. However, the large cavity and weak stiffness components of traditional metamaterials may cause a conflict between vibroacoustic reduction and load-bearing capacity, and thus limit their ***, we propose a lightweight multifunctional metamaterial that can simultaneously achieve low-frequency sound insulation, broadband vibration reduction, and excellent load-bearing performance, named as vibroacoustic isolation and bearing metamaterial(VIBM). The advent of additive manufacturing technology provides a convenient and reliable method for the fabrication of VIBM samples. The results show that the compressive strength of the VIBM is as high as 9.71 MPa, which is nearly 87.81% higher than that of the conventional grid structure(CGS) under the same volume fraction. Moreover, the vibration and sound transmission are significantly reduced over a low and wide frequency range, which agrees well with the experimental data, and the reduction degree is obviously larger than that obtained by the CGS. The design strategy can effectively realize the key components of metamaterials and improve their application scenarios.

关键词： broadband vibration reduction load bearing low-frequency sound insulation multifunctional metamaterial O321

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Reinforcement learning method for machining deformation control based on meta-invariant feature space

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Visual Computing for Industry,Biomedicine,and Art 2022年第1期5卷 323-339页

作者： Yujie Zhao Changqing Liu Zhiwei Zhao Kai Tang Dong He College of Mechanical and Electrical Engineering/National Key Laboratory of Science and Technology on Helicopter Transmission Nanjing University of Aeronautics and AstronauticsNanjing 210016China The smart manufacturing thrust Hong Kong University of Science and Technology(GZ)Guangzhou 511458China

Precise control of machining deformation is crucial for improving the manufacturing quality of structural aerospace *** the machining process,different batches of blanks have different residual stress distributions,which pose a significant challenge to machining deformation *** this study,a reinforcement learning method for machining deformation control based on a meta-invariant feature space was *** proposed method uses a reinforcement-learning model to dynamically control the machining process by monitoring the deformation ***,combined with a meta-invariant feature space,the proposed method learns the internal relationship of the deformation control approaches under different stress distributions to achieve the machining deformation control of different batches of ***,the experimental results show that the proposed method achieves better deformation control than the two existing benchmarking methods.

关键词： Machining deformation Residual stress Deformation control Meta-invariant feature space Reinforcement learning

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Bioinspired smart dual-layer hydrogels system with synchronous solar and thermal radiation modulation for energy-saving all-season temperature regulation

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Journal of Energy Chemistry 2025年第2期101卷 175-190页

作者： Meng-Chen Huang Chao-Hua Xue Zhongxue Bai Jun Cheng Yong-Gang Wu Chao-Qun Ma Li Wan Long Xie Hui-Di Wang Bing-Ying Liu Xiao-Jing Guo College of Bioresources Chemical and Materials Engineering Shaanxi University of Science & Technology School of Manufacture Science and Engineering Key Laboratory of Testing Technology for Manufacturing Process Ministry of Education Southwest University of Science and Technology School of Life Science and Engineering Southwest University of Science and Technology Northwest Institute for Nonferrous Metal Research Shaanxi Key Laboratory of Biomedical Metal Materials

All-season thermal management with zero energy consumption and emissions is more crucial to global decarbonization over traditional energy-intensive cooling/heating ***,the static single thermal management for cooling or heating fails to self-regulate the temperature in dynamic seasonal temperature ***,inspired by the dual-temperature regulation function of the fur color changes on the backs and abdomens of penguins,a smart thermal management composite hydrogel(PNA@H-PM Gel) system was subtly created though an "on-demand" dual-layer structure design *** PNA@H-PM Gel system features synchronous solar and thermal radiation modulation as well as tunable phase transition temperatures to meet the variable seasonal thermal requirements and energy-saving demands via self-adaptive radiative cooling and solar heating ***,this system demonstrates superb modulations of both the solar reflectance(ΔR=0.74) and thermal emissivity(ΔE=0.52) in response to ambient temperature changes,highlighting efficient temperature regulation with average radiative cooling and solar heating effects of 9.6℃ in summer and 6.1℃ in winter,***,compared to standard building baselines,the PNA@H-PM Gel presents a more substantial energy-saving cooling/heating potentials for energy-efficient buildings across various regions and *** novel solution,inspired by penguins in the real world,will offer a fresh approach for producing intelligent,energy-saving thermal management materials,and serve for temperature regulation under dynamic climate conditions and even throughout all seasons.

关键词： Energy-saving Radiative cooling Self-adaptive thermal management Spectral modulation Thermochromic hydrogel

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Efficient cutting path planning for a non-spherical tool based on an iso-scallop height distance field

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Chinese Journal of Aeronautics 2024年第7期37卷 496-510页

作者： Jiancheng HAO Dong HE Zhaoyu LI Pengcheng HU Yuanzhi CHEN Kai TANG Department of Mechanical and Aerospace Engineering Hong Kong University of Science and TechnologyHong Kong 999077China The Hong Kong University of Science and Technology(Guangzhou) Smart Manufacturing ThrustNanshaGuangzhou 511400China HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute Shenzhen 518057China HKUST Shenzhen Research Institute Shenzhen 518057China

Iso-scallop height machining means,when machining a freeform surface,the scallop height between any two neighboring tool paths on the surface will be a constant(i.e.,the given threshold),which is preferable among various freeform surface machining strategies due to its high machining efficiency as well as better machine tool’s ***,all the existing iso-scallop height path planning methods pertain to only the ball-end or flat-end types of *** recent years,the non-spherical cutting tool has become more and more popular,especially for five-axis machining of complex freeform surfaces,majorly owing to its non-constant curvature which can be utilized to adaptively fit the tool to the surface to both avoid the local gouging and enlarge the cutting ***,there have been no reported works on iso-scallop height five-axis tool path generation for a non-spherical tool,and,in this paper,we present ***,we first define and construct two fields on the surface to be machined-the collision-free tool orientation field(vector)and the iso-scallop height distance field(scalar).The iso-lines of the scalar field and their associated tool orientation field vectors then naturally serve as potential iso-scallop height five-axis tool paths,and we present a propagation-based algorithm to construct the desired tool path from the *** computer simulation and physical cutting experiments confirm that everywhere on the surface,except maybe near the saddle curves of the scalar filed,the scallop height is exactly the given *** adding the saddle curves as extra tool paths,the final machined surface then is assured of the required scallop height requirement.

关键词： Freeform surface machining Iso-scallop tool path Customized tool Five-axis tool path Computer aided manufacturing

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An artificial intelligence-assisted digital microfluidic system for multistate droplet control

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Microsystems & Nanoengineering 2024年第5期10卷 191-202页

作者： Kunlun Guo Zerui Song Jiale Zhou Bin Shen Bininggyong Yan Zhen Gu Huifeng Wang Key Laboratory of smart manufacturing in Energy Chemical Process Ministry of Education East China University of Science and TechnologyShanghaiChina

Digital microfluidics(DMF)is a versatile technique for parallel and field-programmable control of individual *** the high level of variability in droplet manipulation,it is essential to establish self-adaptive and intelligent control methods for DMF systems that are informed by the transient state of droplets and their ***,most related studies focus on droplet localization and shape *** this study,we develop the Al-assisted DMF frameworkμDropAl for multistate droplet control on the basis of droplet *** semantic segmentation model is integrated into our custom-designed DMF system to recognize the droplet states and their interactions for feedback control with a state *** proposed model has strong flexibility and can recognize droplets of different colors and shapes with an error rate of less than 0.63%;it enables control of droplets without user *** coeffcient of variation(CV)of the volumes of split droplets can be limited to 2.74%,which is lower than the CV of traditional dispensed droplets,contributing to an improvement in the precision of volume control for droplet *** proposed system inspires the development of semantic-driven DMF systems that can interface with multimodal large language models(MLLMs)for fully automatic control.

关键词： system state versatile

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A deep reinforcement learning approach to gasoline blending real-time optimization under uncertainty

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Chinese Journal of Chemical Engineering 2024年第7期71卷 183-192页

作者： Zhiwei Zhu Minglei Yang Wangli He Renchu He Yunmeng Zhao Feng Qian Key Laboratory of smart manufacturing in Energy Chemical Process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China

The gasoline inline blending process has widely used real-time optimization techniques to achieve optimization objectives,such as minimizing the cost of ***,the effectiveness of real-time optimization in gasoline blending relies on accurate blending models and is challenged by stochastic ***,we propose a real-time optimization algorithm based on the soft actor-critic(SAC)deep reinforcement learning strategy to optimize gasoline blending without relying on a single blending model and to be robust against *** approach constructs the environment using nonlinear blending models and feedstocks with *** algorithm incorporates the Lagrange multiplier and path constraints in reward design to manage sparse product *** abstracted states facilitate algorithm convergence,and the normalized action vector in each optimization period allows the agent to generalize to some extent across different target production *** these well-designed components,the algorithm based on the SAC outperforms real-time optimization methods based on either nonlinear or linear *** even demonstrates comparable performance with the time-horizon based real-time optimization method,which requires knowledge of uncertainty models,confirming its capability to handle uncertainty without accurate *** simulation illustrates a promising approach to free real-time optimization of the gasoline blending process from uncertainty models that are difficult to acquire in practice.

关键词： Deep reinforcement learning Gasoline blending Real-time optimization Petroleum Computer simulation Neural networks

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Graph convolutional network for axial concentration profiles prediction in simulated moving bed

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Chinese Journal of Chemical Engineering 2024年第9期73卷 270-280页

作者： Can Ding Minglei Yang Yunmeng Zhao Wenli Du Key Laboratory of smart manufacturing in Energy Chemical Process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China

The simulated moving bed(SMB)chromatographic separation is a continuous compound separation process based on the differences in adsorption capacity exhibited by distinct constituents of a mixture on the fluid phase and stationary *** prediction of axial concentration profiles along the beds in a unit is crucial for the operating optimization of *** the correlation shared by operating variables of SMB has an enormous impact on the operational state of the device,these correlations have been long overlooked,especially by the data-driven *** study proposes an operating variable-based graph convolutional network(OV-GCN)to enclose the underrepresented correlations and precisely predict axial concentration profiles prediction in *** OV-GCN estimates operating variables with the Spearman correlation coefficient and incorporates them in the adjacency matrix of a graph convolutional network for information propagation and feature *** with Random Forest,K-Nearest Neighbors,Support Vector Regression,and Backpropagation Neural Network,the values of the three performance evaluation metrics,namely MAE,RMSE,and R^(2),indicate that OV-GCN has better prediction accuracy in predicting five essential aromatic compounds'axial concentration profiles of an SMB for separating p-xylene(PX).In addition,the OV-GCN method demonstrates a remarkable ability to provide high-precision and fast predictions in three industrial case *** the goal of simultaneously maximizing PX purity and yield,we employ the non-dominated sorting genetic algorithm-II optimization method to perform multi-objective optimization of the PX purity and *** outcome suggests a promising approach to extracting and representing correlations among operating variables in data-driven process modeling.

关键词： Chromatography Prediction Operating variables Graph convolutional network Optimization

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A stochastic reconstruction strategy based on a stratified library of structural descriptors and its application in the molecular reconstruction of naphtha

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Chinese Journal of Chemical Engineering 2022年第11期51卷 153-167页

作者： Guangyao Zhao Minglei Yang Wenli Du Feifei Shen Feng Qian Key Laboratory of smart manufacturing in Energy Chemical Process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China

Molecular reconstruction is a rapid and reliable way to provide molecular detail of petroleum fractions,which is required in the kinetic modeling of petroleum conversation processes at the molecular *** the typical stochastic reconstruction method,the estimation of properties of pseudo molecules that are generated by Monte Carlo sampling depends on the building of predefined molecular libraries,which is expensive and inaccessible for certain petroleum *** this paper,a novel stochastic reconstruction strategy is proposed,which is based on a stratified library of structural *** of pseudo molecules generated in the novel strategy can be directly estimated by group contribution method in the condition of lacking predefined molecular *** this strategy,the molecular building diagram comprises two ***,the ring structure is configured by determining the number of *** from the length of chain adopted in the traditional stochastic reconstruction method,in the second step,number of structural descriptors(SDs)for binding site and chain were determined sequentially for the configuration of binding site and saturated acyclic hydrocarbon *** structural descriptors for binding site and chain were selected from group contribution *** count the number of partial overlapping sections between structural descriptors for chain,two supplementary structural descriptors were *** possible saturated structures of hydrocarbon chains can be represented by structural descriptors at the scale of property *** strategy separates the building of a predefined molecule library from the stochastic reconstruction *** exact structures of pseudo molecules represented by structural descriptors in this work can be determined with sufficient chemical *** naphtha samples are tested independently to demonstrate the performance of the proposed strategy and the results show that the estimated prop

关键词： Novel stochastic reconstruction strategy Stratified library of structural descriptors Group contribution method

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