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Publikationer inom industriella produktionssystem

Här visas de 50 senaste publikationerna från enheten för industriella produktionssystem.

[1]
B. Zi et al., "Coating defect detection in intelligent manufacturing: Advances, challenges, and future trends," Robotics and Computer-Integrated Manufacturing, vol. 97, 2026.
[2]
D. Wu et al., "Empowering natural human–robot collaboration through multimodal language models and spatial intelligence: Pathways and perspectives," Robotics and Computer-Integrated Manufacturing, vol. 97, 2026.
[3]
Q. Qin et al., "Robot digital twin systems in manufacturing : Technologies, applications, trends and challenges," Robotics and Computer-Integrated Manufacturing, vol. 97, 2026.
[4]
M. Sun et al., "Out-of-order execution enabled deep reinforcement learning for dynamic additive manufacturing scheduling," Robotics and Computer-Integrated Manufacturing, vol. 91, 2025.
[5]
Y. Qin et al., "A tool wear monitoring method based on data-driven and physical output," Robotics and Computer-Integrated Manufacturing, vol. 91, 2025.
[6]
X. Wang et al., "Dynamic multi-tour order picking in an automotive-part warehouse based on attention-aware deep reinforcement learning," Robotics and Computer-Integrated Manufacturing, vol. 94, s. 102959-102959, 2025.
[7]
Q. Wang et al., "A phased robotic assembly policy based on a PL-LSTM-SAC algorithm," Journal of manufacturing systems, vol. 78, s. 351-369, 2025.
[8]
B. Zhang et al., "An imbalanced data learning approach for tool wear monitoring based on data augmentation," Journal of Intelligent Manufacturing, vol. 36, no. 1, s. 399-420, 2025.
[9]
J. Leng et al., "Federated learning-empowered smart manufacturing and product lifecycle management : A review," Advanced Engineering Informatics, vol. 65, 2025.
[10]
B. Wang et al., "Context-aware AR adaptive information push for product assembly: Aligning information load with human cognitive abilities," Advanced Engineering Informatics, vol. 64, 2025.
[11]
S. N. Rea Minango, "Assembly features in collaborative product development : Integrating assembly into product information to enhance stakeholder communication," Doktorsavhandling Stockholm : KTH Royal Institute of Technology, TRITA-ITM-AVL, 2025:1, 2025.
[12]
J. Leng et al., "Review of manufacturing system design in the interplay of Industry 4.0 and Industry 5.0 (Part II) : Design processes and enablers," Journal of manufacturing systems, vol. 79, s. 528-562, 2025.
[13]
H. U. Rehman et al., "Intelligent configuration management in modular production systems : Integrating operational semantics with knowledge graphs," Journal of manufacturing systems, vol. 80, s. 610-625, 2025.
[14]
T. Li et al., "Online inverse solution for deep learning-based prognostics," i Structural Health Monitoring - The 10th Asia-Pacific Workshop on Structural Health Monitoring, 10APWSHM 2024, 2025, s. 119-126.
[15]
F. Mo et al., "Development of a runtime-condition model for proactive intelligent products using knowledge graphs and embedding," Knowledge-Based Systems, vol. 318, 2025.
[16]
Q. Meng et al., "Grinding Chatter Online Monitoring Based on Multi-Sensor Fusion Information and Hybrid Deep Neural Network," IEEE Transactions on Industrial Informatics, 2025.
[17]
Y. Liu et al., "Fusing human action recognition and object detection for human-robot collaborative assembly," International Journal of Modeling, Simulation, and Scientific Computing, vol. 16, no. 03, 2025.
[18]
Z. Liu, F. Davoli och D. Borsatti, "Industrial Internet of Things (IIoT) : Trends and Technologies," Future Internet, vol. 17, no. 5, 2025.
[19]
X. Li et al., "Chatter-free milling of aerospace thin-walled parts," Journal of Materials Processing Technology, vol. 341, 2025.
[20]
J. Cai et al., "Decision-Making in Complementary Products Supply Chain : Game Theory and Sensitivity Analysis," SYSTEMS, vol. 13, no. 5, 2025.
[21]
S. Liu et al., "A Digital Twin-Enabled Approach to Reliable Human–robot Collaborative Assembly," i Human Centric Smart Manufacturing Towards Industry 5 0, : Springer Nature, 2025, s. 281-304.
[22]
G. Wang et al., "Multi-robot collaborative manufacturing driven by digital twins : Advancements, challenges, and future directions," Journal of manufacturing systems, vol. 82, s. 333-361, 2025.
[23]
B. Wang et al., "Future Research Directions on Human-Centric Smart Manufacturing," i Human Centric Smart Manufacturing Towards Industry 5 0, : Springer Nature, 2025, s. 359-369.
[24]
"Human-Centric Smart Manufacturing Towards Industry 5.0," , Springer Nature, Human Centric Smart Manufacturing Towards Industry 5 0, 2025.
[25]
B. Wang et al., "Preface," i Human Centric Smart Manufacturing Towards Industry 5 0, : Springer Nature, 2025.
[26]
J. Leng et al., "Physics-informed machine learning in intelligent manufacturing : a review," Journal of Intelligent Manufacturing, 2025.
[27]
S. Zhao et al., "Industrial Foundation Models (IFMs) for intelligent manufacturing : A systematic review," Journal of manufacturing systems, vol. 82, s. 420-448, 2025.
[28]
J. Leng et al., "High-performance manufacturing systems : concepts, performance metrics, enablers, challenges, and research directions," Advanced Engineering Informatics, vol. 68, 2025.
[29]
J. Yan et al., "Human-centric artificial intelligence towards Industry 5.0 : retrospect and prospect," Journal of Industrial Information Integration, vol. 47, 2025.
[30]
Z. Liu et al., "Establishment and Synchronisation of Digital Twins for Multi-robot Systems in Manufacturing," i 58th CIRP Conference on Manufacturing Systems, CMS 2025, 2025, s. 419-424.
[31]
D. Antonelli et al., "Enhancing Industrial Mobile Manipulators Through Cognitive Digital Twins," i Innovations in Industrial Engineering IV, 2025, s. 25-36.
[32]
T. Li et al., "Fusing model-based and data-driven prognostic methods for real-time model updating," Mechanical systems and signal processing, vol. 238, 2025.
[33]
C. Zhang et al., "A digital twin shop-floor construction method towards seamless and resilient control," Journal of manufacturing systems, vol. 82, s. 660-677, 2025.
[34]
M. Urgo et al., "AI-Based Pose Estimation of Human Operators in Manufacturing Environments," i Lecture Notes in Mechanical Engineering, : Springer Nature, 2024, s. 3-38.
[35]
D. Mourtzis et al., "Modelling, Design and Simulation as-a-Service Based on Extended Reality (XR) in Industry 4.0," i CIRP Novel Topics in Production Engineering: Volume 1, : Springer Nature, 2024, s. 99-143.
[36]
Z. Zhao et al., "Spatial-temporal traceability for cyber-physical industry 4.0 systems," Journal of manufacturing systems, vol. 74, s. 16-29, 2024.
[37]
D. Li et al., "An online inference method for condition identification of workpieces with complex residual stress distributions," Journal of manufacturing systems, vol. 73, s. 192-204, 2024.
[38]
F. M. Monetti och A. Maffei, "Towards the definition of assembly-oriented modular product architectures: a systematic review," Research in Engineering Design, vol. 35, no. 2, s. 137-169, 2024.
[39]
Y. Wang et al., "Research on Pharmaceutical Supply Chain Decision-Making Model Considering Output and Demand Fluctuations," IEEE Access, vol. 12, s. 61629-61641, 2024.
[40]
B. Wang et al., "Towards the industry 5.0 frontier: Review and prospect of XR in product assembly," Journal of manufacturing systems, vol. 74, s. 777-811, 2024.
[41]
J. Leng et al., "Unlocking the power of industrial artificial intelligence towards Industry 5.0: Insights, pathways, and challenges," Journal of manufacturing systems, vol. 73, s. 349-363, 2024.
[42]
D. Antonelli et al., "Exploring the limitations and potential of digital twins for mobile manipulators in industry," i 5th International Conference on Industry 4.0 and Smart Manufacturing (ISM 2023), 2024, s. 1121-1130.
[43]
F. M. Monetti, P. Z. Martínez och A. Maffei, "Assessing sustainable recyclability of battery systems: a tool to aid design for disassembly," i Proceedings of the Design Society, Design 2024, 2024, s. 1389-1398.
[44]
K. Y. H. Lim et al., "Graph-enabled cognitive digital twins for causal inference in maintenance processes," International Journal of Production Research, vol. 62, no. 13, s. 4717-4734, 2024.
[45]
D. Zhang et al., "IRS Assisted Federated Learning : A Broadband Over-the-Air Aggregation Approach," IEEE Transactions on Wireless Communications, vol. 23, no. 5, s. 4069-4082, 2024.
[46]
S. Li, P. Zheng och L. Wang, "Self-organizing multi-agent teamwork," i Proactive Human-Robot Collaboration Toward Human-Centric Smart Manufacturing, : Elsevier BV, 2024, s. 121-148.
[47]
S. Li, P. Zheng och L. Wang, "Preface," i Proactive Human-Robot Collaboration Toward Human-Centric Smart Manufacturing, : Elsevier BV, 2024.
[48]
S. Li, P. Zheng och L. Wang, "Deployment roadmap of proactive human–robot collaboration," i Proactive Human-Robot Collaboration Toward Human-Centric Smart Manufacturing, : Elsevier BV, 2024, s. 149-192.
[49]
S. Li, P. Zheng och L. Wang, "Conclusions and future perspectives," i Proactive Human-Robot Collaboration Toward Human-Centric Smart Manufacturing, : Elsevier BV, 2024, s. 265-279.
[50]
S. Li, P. Zheng och L. Wang, "Case studies of proactive human–robot collaboration in manufacturing," i Proactive Human-Robot Collaboration Toward Human-Centric Smart Manufacturing, : Elsevier BV, 2024, s. 229-264.
Fullständig lista i KTH:s publikationsportal