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Publications

Here are the 50 latest publications from the Department of Production Engineering.

[1]
Z. Zhou et al., "Learning accurate and efficient three-finger grasp generation in clutters with an auto-annotated large-scale dataset," Robotics and Computer-Integrated Manufacturing, vol. 91, 2025.
[2]
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.
[3]
Y. Qin et al., "A tool wear monitoring method based on data-driven and physical output," Robotics and Computer-Integrated Manufacturing, vol. 91, 2025.
[4]
S. Das et al., "Towards gamification for spatial digital learning environments," Entertainment Computing, vol. 52, 2025.
[5]
J. Chen et al., "Fabrication and development of mechanical metamaterials via additive manufacturing for biomedical applications : a review," International Journal of Extreme Manufacturing, vol. 7, no. 1, 2025.
[6]
S. Liu, L. Wang and R. X. Gao, "Cognitive neuroscience and robotics : Advancements and future research directions," Robotics and Computer-Integrated Manufacturing, vol. 85, 2024.
[7]
X. Li et al., "ACWGAN-GP for milling tool breakage monitoring with imbalanced data," Robotics and Computer-Integrated Manufacturing, vol. 85, 2024.
[8]
X. Zhang et al., "Knowledge graph and function block based Digital Twin modeling for robotic machining of large-scale components," Robotics and Computer-Integrated Manufacturing, vol. 85, pp. 102609, 2024.
[9]
B. Wang et al., "Human Digital Twin in the context of Industry 5.0," Robotics and Computer-Integrated Manufacturing, vol. 85, 2024.
[10]
M. Chodnicki et al., "Project-Based Collaborative Research and Training Roadmap for Manufacturing Based on Industry 4.0," in Flexible Automation and Intelligent Manufacturing : Establishing Bridges for More Sustainable Manufacturing Systems, 2024, pp. 708-715.
[11]
Y. Zhang et al., "Skeleton-RGB integrated highly similar human action prediction in human–robot collaborative assembly," Robotics and Computer-Integrated Manufacturing, vol. 86, 2024.
[12]
X. Li et al., "Data-model linkage prediction of tool remaining useful life based on deep feature fusion and Wiener process," Journal of manufacturing systems, vol. 73, pp. 19-38, 2024.
[13]
Z. Zhang et al., "A residual reinforcement learning method for robotic assembly using visual and force information," Journal of manufacturing systems, vol. 72, pp. 245-262, 2024.
[14]
Z. Huang et al., "Cross-domain tool wear condition monitoring via residual attention hybrid adaptation network," Journal of manufacturing systems, vol. 72, pp. 406-423, 2024.
[15]
B. Yao et al., "Virtual data generation for human intention prediction based on digital modeling of human-robot collaboration," Robotics and Computer-Integrated Manufacturing, vol. 87, 2024.
[16]
H. Gajanan Naik, "Effective Digitization in Brownfield Factories : A conceptualized model for technology transfer to brownfield production factories through smart factory lab," , 2024.
[17]
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.
[18]
X. Li et al., "Smart Reconfigurable Manufacturing: Literature Analysis," in 11th CIRP Global Web Conference, CIRPe 2023, 2024, pp. 43-48.
[19]
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.
[20]
Y. Lu et al., "Smart manufacturing enabled by intelligent technologies," International journal of computer integrated manufacturing (Print), vol. 37, no. 1-2, pp. 1-3, 2024.
[21]
Z. Zhao et al., "Spatial-temporal traceability for cyber-physical industry 4.0 systems," Journal of manufacturing systems, vol. 74, pp. 16-29, 2024.
[22]
J. Fan et al., "An Integrated Hand-Object Dense Pose Estimation Approach With Explicit Occlusion Awareness for Human-Robot Collaborative Disassembly," IEEE Transactions on Automation Science and Engineering, vol. 21, no. 1, pp. 147-156, 2024.
[23]
A. S. Gnaneswaran, "Comparative Study of the Role of Digital Technologies in Implementing Circular Economy Practices in Product-Service Systems (PSS) : An Analysis Across Varying Organizational Scales," , 2024.
[24]
S. Yi et al., "Safety-aware human-centric collaborative assembly," Advanced Engineering Informatics, vol. 60, 2024.
[25]
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.
[26]
X. Li et al., "Joint scheduling optimisation method for the machining and heat-treatment of hydraulic cylinders based on improved multi-objective migrating birds optimisation," Journal of manufacturing systems, vol. 73, pp. 170-191, 2024.
[27]
X. Li et al., "Knowledge graph based OPC UA information model automatic construction method for heterogeneous devices integration," Robotics and Computer-Integrated Manufacturing, vol. 88, 2024.
[28]
Y. Jeong, E. Flores-García and M. Wiktorsson, "Integrating Smart Production Logisticswith Network Diagrams: A Frameworkfor Data Visualization," in Proceedings of the 11th Swedish Production Symposium, 2024, pp. 601-612.
[29]
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.
[30]
C. Li et al., "Unleashing mixed-reality capability in Deep Reinforcement Learning-based robot motion generation towards safe human–robot collaboration," Journal of manufacturing systems, vol. 74, pp. 411-421, 2024.
[31]
A. Aristeidou, "Development of a Business Model Framework for Collaborative Model-Based Engineering," , 2024.
[32]
D. Bernabeu Fernandez De Liencres, "Machine Learning Demand Forecast for Demand Sensing and Shaping : Combine the existing work done with demand sensing and shaping to achieve a higher customer service level, customer experience and balancing inventory," , 2024.
[33]
F. Lupi, A. Maffei and M. Lanzetta, "CAD-based Autonomous Vision Inspection Systems," in 5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023, 2024, pp. 2127-2136.
[34]
S. Kokare et al., "Life Cycle Assessment of a Jet Printing and Dispensing Machine," in 5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023, 2024, pp. 708-718.
[35]
M. Subasic et al., "Fatigue strength improvement of additively manufactured 316L stainless steel with high porosity through preloading," International Journal of Fatigue, vol. 180, 2024.
[36]
B. Samaan and E. Thunell, "Livscykelanalys av en eldriven båtmotor," , 2024.
[37]
C. Liljencrantz and F. Pettersson, "Konceptframtagning av ett par OTG-goggles," , 2024.
[38]
T. Svendsen, "Syrgasflaskan LIFT," , 2024.
[39]
V. Einarsson, "Advanced forming and welding with seam tracking : effective manufacturing of light weight girderswith corrugated webs," , 2024.
[40]
A. Arvidsson, "CFD-analys med OpenFOAM som konstruktionsverktyg för utvärdering av tidiga iterationer av gasväxlingskomponenter," , 2024.
[41]
S. Tawfiq, "Optimering av en undervattens rengöringsrobot med avseende på viktminskning," , 2024.
[42]
S. Amir et al., "Toward a Circular Economy: A Guiding Framework for Circular Supply Chain Implementation," in Springer Series in Supply Chain Management, : Springer Nature, 2024, pp. 379-404.
[43]
S. Wei et al., "An improved memetic algorithm for multi-objective resource-constrained flexible job shop inverse scheduling problem : An application for machining workshop," Journal of manufacturing systems, vol. 74, pp. 264-290, 2024.
[44]
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.
[45]
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.
[46]
X. Li et al., "Flexible Job Shop Composite Dispatching Rule Mining Approach Based on an Improved Genetic Programming Algorithm," Tsinghua Science and Technology, vol. 29, no. 5, pp. 1390-1408, 2024.
[47]
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.
[48]
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.
[49]
S. Linderson, S. E. Birkie and M. Bellgran, "The Issue of Corporate Mandatory Standards in Production Improvement Programmes," Journal of Industrial Engineering and Management, vol. 17, no. 2, pp. 385-402, 2024.
[50]
J. Persson and J. Raij Montanari, "Förbättrat glidskikt till hjälmar," , 2024.
Full list in the KTH publications portal