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Collaborative optimization for multirobot manufacturing system reliability through integration of SysML simulation and maintenance knowledge graph

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Journal of manufacturing Systems 2025年 80卷 749-775页

作者： Zhou, Jian Zheng, Lianyu Wang, Yiwei School of Mechanical Engineering and Automation Beihang University Beijing100191 China MIIT Key Laboratory of Intelligent Manufacturing Technology for Aeronautics Advanced Equipments Ministry of Industry and Information Technology Beijing100191 China Beijing Key Laboratory of Digital Design and Manufacturing Technology Beijing100191 China

In the rapidly advancing field of industrial automation, the reliability and maintenance of multirobot manufacturing systems are crucial. This paper proposes a collaborative optimization method for the reliability of multirobot system, combining SysML (System Modeling Language) model simulation with an operational and maintenance knowledge graph, aiming to ensure the reliable operation of multirobot manufacturing systems. The SysML model provides a comprehensive framework to represent the system architecture, workflows, and key parameters, identify critical components and potential bottlenecks, and perform detailed reliability analysis. Simultaneously, by embedding intelligent algorithms, the operational and maintenance knowledge graph enables automatic detection of operational anomalies and intelligent generation of maintenance strategies for industrial robots. By integrating the SysML model with the operational and maintenance knowledge graph, a collaborative optimization framework for the reliability of multirobot system is constructed. This framework not only dynamically adjusts key parameters in the simulation model, enhancing the accuracy and real-time performance of system reliability assessments, but also optimizes maintenance strategies based on system simulation indicators to ensure the reliable operation of multirobot system. Case studies validate that the proposed method improves the reliability of multirobot manufacturing systems, demonstrating that the combination of SysML simulation and the operational and maintenance knowledge graph can effectively address the complexity of modern manufacturing systems, offering significant reference value. © 2025 The Society of manufacturing Engineers

关键词： Knowledge graph

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3-D Multiobject Tracking With Radar Data Enhancement for Intelligent Vehicles

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IEEE Sensors Journal 2025年第9期25卷 16310-16320页

作者： Li, Luxing Wei, Chao Sui, Shuxin Hu, Jibin Feng, Fuyong School of Mechanical Engineering Beijing Institute of Technology Beijing100081 China National Key Laboratory of Special Vehicle Design and Manufacturing Integration Technology Beijing100081 China

With the rapid advancement of autonomous driving technology, 3-D multiobject tracking (MOT) has become critical for enhancing the safety of intelligent vehicles. The tracking by detection (TBD) framework improves 3-D tracking performance with simplicity and efficiency. However, existing light detection and ranging (LiDAR)-camera systems struggle in complex scenarios, and millimeter wave radar’s (radar) high-precision motion data remain underutilized. This article presents a multimodal 3-D MOT model that integrates LiDAR, camera, and radar data to overcome these limitations and enhance tracking performance across diverse environments. The proposed model leverages the radar’s high-precision motion data to design an adaptive refinement of confidence scores and adaptive-nonmaximum suppression (A-NMS), improving the accuracy of the preprocessing stage. Additionally, it incorporates LiDAR and camera features to enhance data association and trajectory estimation. A graph attention network (GAT)-based radar modality feature extraction network further improves tracking accuracy by refining motion metrics. Extensive experiments on the nuScenes dataset show that our model achieves a new state-of-the-art (SOTA) tracking accuracy of 74.6% AMOTA, 288 IDS, and 0.514 m AMOTP, along with a real-time performance of 21.8 Hz. Furthermore, in tests of generalizability across various real-vehicle scenarios, our model demonstrates exceptional tracking accuracy, real-time performance, and robustness. © 2001-2012 IEEE.

关键词： Autonomous vehicles

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Analysis of the influence and extent of blockage on the static characteristics of porous aerostatic bearings

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Journal of the Brazilian Society of Mechanical Sciences and Engineering 2025年第6期47卷 1-17页

作者： Chen, Dongju Li, Ping Sun, Kun Pan, Ri Fan, Jinwei Mechanical Industry Key Laboratory of Heavy Machine Tool Digital Design and Testing Faculty of Mechanical and Energy Engineering Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Advanced Manufacturing Technology Faculty of Mechanical and Energy Engineering Beijing University of Technology Beijing100124 China

In the engineering application of porous aerostatic radial bearings, the gas supplied is generally not absolutely clean, and the micropores in porous materials are usually very small. As the aerostatic bearing continues to operate, impurities in the gas gradually accumulate and form blockages at certain points in the porous medium, affecting the bearing performance. Therefore, a systematic study of the impact of blockages in porous media on aerostatic bearings is essential. This paper establishes lubrication models for porous aerostatic radial bearings under both blockage-free and blocked conditions. Through Fluent simulation analysis, the effects of the number, location, and size of blockages on the static characteristics of the bearing are examined. An analysis of the extent of impact of blockages on bearing performance is also conducted, providing a reference basis for judging the operating condition of the bearing and optimizing bearing design in practical applications. © The Author(s), under exclusive licence to The Brazilian Society of Mechanical Sciences and Engineering 2025.

关键词： Micropores

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Probabilistic Assessment of Constitutive Model Parameters:Insight from a Statistical Damage Constitutive Model and a Simple Critical State Hypoplastic Model

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Journal of Earth Science 2025年第2期36卷 685-699页

作者： Yang Xue Fasheng Miao Yiping Wu Linwei Li Daniel Dias Yang Tang Key Laboratory of Smart Earth Beijing 100029China Key Laboratory of Geological Survey and Evaluation of Ministry of Education China University of Geosciences(Wuhan)Wuhan 430074China School of Geosciences Yangtze UniversityWuhan 430100China College of Resources and Environmental Engineering Guizhou UniversityGuiyang 550025China Laboratory 3SR Grenoble Alpes UniversityGrenoble 38000France Engineering Digital Technology Center Central-South Architectural Design Institute Co.LtdWuhan 430071China

The constitutive model is essential for predicting the deformation and stability of rocksoil *** estimation of constitutive model parameters is a necessary and important task for the reliable characterization of mechanical ***,constitutive model parameters cannot be evaluated accurately with a limited amount of test data,resulting in uncertainty in the prediction of stress-strain *** paper proposes a Bayesian analysis framework to address this *** combines the Bayesian updating with the structural reliability and adaptive conditional sampling methods to assess the equation parameter of constitutive *** on the triaxial and ring shear tests on shear zone soils from the Huangtupo landslide,a statistical damage constitutive model and a critical state hypoplastic constitutive model were used to demonstrate the effectiveness of the proposed ***,the parameter uncertainty effects of the damage constitutive model on landslide stability were *** show that reasonable assessments of the constitutive model parameter can be well *** variability of stress-strain curves is strongly related to the model prediction *** estimation uncertainty of constitutive model parameters should not be ignored for the landslide stability *** study provides a reference for uncertainty analysis and parameter assessment of the constitutive model.

关键词： probabilistic back analysis Bayesian approach model parameter estimation constitutive model landslide stability engineering geology

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Against Mobile Collusive Eavesdroppers: Cooperative Secure Transmission and Computation in UAV-Assisted MEC Networks

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IEEE Transactions on Mobile Computing 2025年第6期24卷 5280-5297页

作者： Zhao, Mingxiong Wang, Zirui Guo, Kun Zhang, Rongqian Quek, Tony Q. S. Ministry of Education Engineering Research Center of Integration and Application of Digital Learning Technology Beijing100039 China Ministry of Education Engineering Research Center of Cyberspace Kunming650504 China Yunnan University of Finance and Economics Yunnan Key Laboratory of Service Computing Kunming650221 China Yunnan University Yunnan Key Laboratory of Software Engineering Kunming650091 China East China Normal University Shanghai Key Laboratory of Multidimensional Information Processing School of Communications and Electronics Engineering Shanghai200241 China Yunnan University School of Information Science and Engineering Kunming650500 China Singapore University of Technology and Design Information Systems Technology and Design 487372 Singapore National Pilot School of Software Yunnan University Kunming China

In Unmanned Aerial Vehicle (UAV)-assisted Mobile Edge Computing (MEC) networks, the security of transmission faces significant challenges due to the vulnerabilities of line-of-sight links and potential eavesdropping on two-hop links. This paper addresses these challenges with an innovative Cooperative Secure Transmission and Computation strategy (CSTC), specifically engineered for time-slotted UAV-assisted MEC networks plagued by mobile collusive eavesdroppers. These eavesdroppers significantly bolster their interception capabilities through coordinated and optimized movements, escalating the security threats. To neutralize these risks, the proposed CSTC employs the UAV and remote devices as helper nodes to emit jamming signals, thereby thwarting eavesdropping activities, while simultaneously facilitating the efficient relay of users' tasks to the base station for advanced processing. The CSTC aims to maximize the sum Secrecy Transmission Rate (STR) satisfying task latency constraints. It involves a joint optimization of UAV trajectory, jamming beamformers, transmit power, and data offloading strategy to expedite task transmission. Additionally, a real-time computation scheduling approach is developed based on a newly defined metric, the Urgency Degree of Users (UDoU), to enhance task processing efficiency. Our extensive simulations validate that the CSTC not only elevates the sum STR but also consistently meets latency constraints, demonstrating its robustness against advanced mobile eavesdropping techniques. © 2002-2012 IEEE.

关键词： Jamming

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Multi-process digital twin closed-loop machining through shape-feature state update and error propagation knowledge graph

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Advanced Engineering Informatics 2025年 65卷

作者： Lin, Zhiwen Zhang, Yueze Chen, Chuanhai Guo, Jinyan Qi, Baobao Yan, Jun Liu, Zhifeng Key Laboratory of CNC Equipment Reliability Ministry of Education Jilin University Jilin Province Changchun130025 China Jilin Provincial Key Laboratory of Advanced Manufacturing and Intelligent Technology for High-end CNC Equipment Jilin University Jilin Province Changchun130025 China School of Mechanical and Aerospace Engineering Jilin University Jilin Province Changchun130025 China Beijing Key Laboratory of Advanced Manufacturing Technology Beijing University of Technology Beijing100124 China Machinery Industry Key Laboratory of Heavy Machine Tool Digital Design and Testing Technology Beijing University of Technology Beijing100124 China

Machining digital twin systems represent a novel platform for achieving full autonomy in machine tools. However, in multi-process machining, error propagation between different processes presents significant challenges to current digital twin systems: real-time model updates, error evolution analysis and optimization. To address these issues, this study proposes a method for rapid state updates of shape features and the construction of an error propagation knowledge graph, enabling dynamic control in a multi-process machining digital twin system. First, a state update method based on multi-level voxel computation is introduced, utilizing the transformation relationship between cutter-workpiece engagement (CWE) and voxels to ensure rapid updates of multi-process digital twin models. Second, digital threads for multi-process machining are developed to identify machining states and track errors. To analyze error evolution and implement effective control measures, an error propagation knowledge graph based on Taylor expansion model is constructed, enabling closed-loop control. Finally, the proposed system was validated for its advancement in error control and closed-loop optimization through the machining of typical multi-process components in the transportation field. The results of comparative experiments and ablation experiments indicate that the error updating efficiency based on multi-level voxel computation threads improved by an average of 59.26% compared to other benchmarks. The error propagation knowledge graph based on the Taylor model achieved a 42.75% improvement in reasoning accuracy compared to the ablated Taylor model. The developed digital twin closed-loop optimization system successfully ensured that the errors in 1280 processes of the case study remained within the tolerance range. © 2025 Elsevier Ltd

关键词： Machining centers

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Combined anisotropic and cyclic constitutive model for laser powder bed fusion fabricated aluminum alloy

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Chinese Journal of Aeronautics 2025年第1期38卷 165-184页

作者： Fei-Fan LI Jihong ZHU Weihong ZHANG Shifeng WEN Jingwen SONG Jun MA Gang FANG State IJR Center of Aerospace Design and Additive Manufacturing School of Mechanical EngineeringNorthwestern Polytechnical UniversityXi’an 710072China Research&Development Institute of Northwestern Polytechnical University in Shenzhen Shenzhen 518063China School of Materials Science and Engineering Northwestern Polytechnical UniversityXi'an 710072China Department of Mechanical and Industrial Engineering Norwegian University of Science and TechnologyTrondheim 7491Norway State Key Laboratory of Tribology in Advanced Equipment Department of Mechanical EngineeringTsinghua UniversityBeijing 100084China

This study presents new methods to effectively model the anisotropic yielding and hardening behavior of laser powder bed fusion fabricated aluminum alloy under both monotonic and cyclic loading *** proposed model combines the yield surface-interpolation method to accurately describe the anisotropic hardening rates in various directions,with the Chaboche kinematic hardening rule to precisely reflect the cyclic *** numerical implementation of the combined anisotropic and cyclic constitutive model,a fully implicit stress integration algorithm based on return mapping method is ***,the multiple parameters associated with the model are categorized and identified in an uncoupled *** isotropic and cyclic hardening parameters are determined by an inverse method,and the stability of the optimization outcomes is validated by applying different starting points for the ***,the back-stress effect on the identification of anisotropic parameters associated with the stress invariant-based Hill48 yield function is considered for the first *** consideration leads to an improved prediction accuracy compared to the identification of anisotropic parameters without considering back-stress *** combined anisotropic and cyclic constitutive model,along with the calibrated parameters,are proven capable of accurately reproducing the intricate deformation behavior of laser powder bed fusion fabricated AlSi10Mg.

关键词： Constitutive models Anisotropy Kinematic hardening Laser powder bed fusion Aluminum alloys

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A calculation method of gear tooth surface wear considering the center distance error

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Wear 2025年

作者： Wang, Hongbing Feng, Shicheng Yin, Lairong Hu, Bo Su, Jie Liu, Huihua Zhou, Changjiang Hunan Provincial Key Laboratory of Safety Design and Reliability Technology for Engineering Vehicle Changsha University of Science and Technology Changsha410114 China Xuchang Tobacco Machinery Co. Ltd. Xuchang461000 China Beijing Engineering Research Center of Precision Measurement Technology and Instruments Beijing University of Technology Beijing100124 China State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Hunan University Changsha410082 China

In gear transmission, manufacturing/installation error and bearing radial clearance led to the variation of the center distance, changing the contact characteristic and subsequently affecting the wear behavior and the fatigue life of the tooth surfaces. In this work, a center distance error model of the gears with the manufacturing/installation error and the bearing radial clearance was derived, and a nonlinear dynamic model of the gear pair considering the variation of the center distance was established. The contact pressure distribution on the tooth surfaces under the dynamic load was obtained by combining the gear meshing principle and the Hertzian contact theory. A general calculation model of the sliding distance between the contact points in the meshing process of the gear pair was derived based on the single point observation method, and the wear depths of the tooth surfaces under the quasi-static and the dynamic load considering the center distance error were determined based on the Archard's adhesive wear model. The presented work found that the wear depth of the tooth surface under the dynamic load fluctuates around the wear depth distribution under the quasi-static load. When considering the center distance error caused by the manufacturing/installation error and the bearing radial clearance, the maximum wear depth at the tooth tip of the driving gear increases as the actual center distance increases, while the maximum wear depth at the tooth root decreases. As for the driven gear, the maximum wear depth at the tooth tip decreases as the actual center distance increases, while the maximum wear depth at the tooth root increases with the actual center distance. The conclusions in this research work can provide a basis for the strength enhancement design of the gears which performance is affected by the center distance error such small-modulus gear pair. © 2025 Elsevier B.V.

关键词： Gear teeth

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EFJSP-IBDR: Energy-efficient flexible job shop scheduling under incentive-based demand response via graph reinforcement learning with dual attention mechanism

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Expert Systems with Applications 2025年 280卷

作者： Liu, Mingzhou Rui, Zhangjie Zhang, Xi Ge, Maogen Ling, Lin Wang, Xiaoqiao Liu, Conghu School of Mechanical Engineering Hefei University of Technology Hefei230009 China Anhui Key Laboratory of Digital Design and Manufacturing Hefei University of Technology Hefei230009 China School of Mechanical and Electronic Engineering Suzhou University Suzhou234000 China

As energy demand grows and the penetration of intermittent renewable energy, optimizing energy consumption patterns in industrial production processes has become an increasing challenge for sustainable manufacturing. This study investigates an energy-efficient flexible job shop scheduling problem with incentive-based demand response (EFJSP-IBDR), aiming to enhance energy consumption efficiency and cost-effectiveness. Given the time-sensitive and complex state features of EFJSP-IBDR, we propose an end-to-end graph reinforcement learning (GRL) approach. Initially, we decompose EFJSP-IBDR into a set of preference-based subproblems to facilitate multi-objective optimization. On this basis, a Markov decision process (MDP) with heterogeneous graph states is employed to model these subproblems. Subsequently, we construct graph neural network schedulers that integrate dual attention mechanisms to extract the features necessary for decision-making in each subproblem. Additionally, a similarity-based parameter transfer strategy is designed to accelerate the training process of all schedulers. Empirical results demonstrate that our approach can reduce peak demand by 47.22% and average load by 51.01% during the manufacturing cycle. The effectiveness of the proposed method suggests its potential to improve load-side energy consumption flexibility and grid resilience. © 2025 Elsevier Ltd

关键词： Smart manufacturing

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Preset trajectory based prescribed performance control for active anti-roll of automotives

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Vehicle System Dynamics 2025年

作者： Huang, Kang Wang, Hu Pei, Pengfei Sun, Hao Shao, Ke School of Mechanical Engineering Hefei University of Technology Hefei China Anhui Key Laboratory of Digital Design and Manufacturing Hefei China School of Civil Aviation Northwestern Polytechnical University Xi'an China Jianghuai Advance Technology Center Hefei China

In this paper, our main focus is on the research of Active Stabilizer Bar System (ASBS) for roll control. Prescribed Performance Control (PPC) has garnered significant attention from scholars and researchers in recent years. In mainstream PPC methods, barrier functions are widely adopted, leading to potential singularity issues in control laws during most unexpected scenarios such as sensor failures. In this study, we employ a robust PPC approach that does not rely on barrier functions, thereby completely circumventing singularity problems in control laws. Firstly, we establish a vehicle roll dynamics model incorporating parameter uncertainties and disturbances with ASBS. Subsequently, controller design is performed in three steps: firstly, constructing performance functions based on system performance requirements to form performance envelopes;secondly, designing reference trajectories within the preset performance envelopes;thirdly, designing robust sliding mode control laws to ensure that the actual tracking error of the system evolves within a tubular region containing the reference trajectories and strictly varies within the performance envelopes. Finally, through simulation experiments, we demonstrate the effectiveness and superiority of this control method. © 2025 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Sliding mode control

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