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Publications in Industrial Production Systems

Here are the 50 latest publications from the Unit of Industrial Production Systems.

[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, pp. 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, pp. 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, pp. 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," Doctoral thesis 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, pp. 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, pp. 610-625, 2025.
[14]
T. Li et al., "Online inverse solution for deep learning-based prognostics," in Structural Health Monitoring - The 10th Asia-Pacific Workshop on Structural Health Monitoring, 10APWSHM 2024, 2025, pp. 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 and 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," in Human Centric Smart Manufacturing Towards Industry 5 0, : Springer Nature, 2025, pp. 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, pp. 333-361, 2025.
[23]
B. Wang et al., "Future Research Directions on Human-Centric Smart Manufacturing," in Human Centric Smart Manufacturing Towards Industry 5 0, : Springer Nature, 2025, pp. 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," in 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, pp. 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," in 58th CIRP Conference on Manufacturing Systems, CMS 2025, 2025, pp. 419-424.
[31]
D. Antonelli et al., "Enhancing Industrial Mobile Manipulators Through Cognitive Digital Twins," in Innovations in Industrial Engineering IV, 2025, pp. 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, pp. 660-677, 2025.
[34]
M. Urgo et al., "AI-Based Pose Estimation of Human Operators in Manufacturing Environments," in Lecture Notes in Mechanical Engineering, : Springer Nature, 2024, pp. 3-38.
[35]
D. Mourtzis et al., "Modelling, Design and Simulation as-a-Service Based on Extended Reality (XR) in Industry 4.0," in CIRP Novel Topics in Production Engineering: Volume 1, : Springer Nature, 2024, pp. 99-143.
[36]
Z. Zhao et al., "Spatial-temporal traceability for cyber-physical industry 4.0 systems," Journal of manufacturing systems, vol. 74, pp. 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, pp. 192-204, 2024.
[38]
F. M. Monetti and A. Maffei, "Towards the definition of assembly-oriented modular product architectures: a systematic review," Research in Engineering Design, vol. 35, no. 2, pp. 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, pp. 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, pp. 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, pp. 349-363, 2024.
[42]
D. Antonelli et al., "Exploring the limitations and potential of digital twins for mobile manipulators in industry," in 5th International Conference on Industry 4.0 and Smart Manufacturing (ISM 2023), 2024, pp. 1121-1130.
[43]
F. M. Monetti, P. Z. Martínez and A. Maffei, "Assessing sustainable recyclability of battery systems: a tool to aid design for disassembly," in Proceedings of the Design Society, Design 2024, 2024, pp. 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, pp. 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, pp. 4069-4082, 2024.
[46]
S. Li, P. Zheng and L. Wang, "Self-organizing multi-agent teamwork," in Proactive Human-Robot Collaboration Toward Human-Centric Smart Manufacturing, : Elsevier BV, 2024, pp. 121-148.
[47]
S. Li, P. Zheng and L. Wang, "Preface," in Proactive Human-Robot Collaboration Toward Human-Centric Smart Manufacturing, : Elsevier BV, 2024.
[48]
S. Li, P. Zheng and L. Wang, "Deployment roadmap of proactive human–robot collaboration," in Proactive Human-Robot Collaboration Toward Human-Centric Smart Manufacturing, : Elsevier BV, 2024, pp. 149-192.
[49]
S. Li, P. Zheng and L. Wang, "Conclusions and future perspectives," in Proactive Human-Robot Collaboration Toward Human-Centric Smart Manufacturing, : Elsevier BV, 2024, pp. 265-279.
[50]
S. Li, P. Zheng and L. Wang, "Case studies of proactive human–robot collaboration in manufacturing," in Proactive Human-Robot Collaboration Toward Human-Centric Smart Manufacturing, : Elsevier BV, 2024, pp. 229-264.
Full list in the KTH publications portal