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Publications

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

[1]
Q. Qin et al., "Robot digital twin systems in manufacturing : Technologies, applications, trends and challenges," Robotics and Computer-Integrated Manufacturing, vol. 97, 2026.
[2]
X. Liu et al., "A cloud manufacturing service composition optimization method for fuzzy demands based on improved NSGA-III algorithm," Robotics and Computer-Integrated Manufacturing, vol. 97, 2026.
[3]
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.
[4]
B. Zi et al., "Coating defect detection in intelligent manufacturing: Advances, challenges, and future trends," Robotics and Computer-Integrated Manufacturing, vol. 97, 2026.
[5]
J. Baalsrud Hauge, J. Baalsrud Hauge and M. Kalverkamp, "Reflections on the Usage of a Commercial-Off-The-Shelf Game in Teaching Logistics," in Advances in Production Management Systems. Cyber-Physical-Human Production Systems: Human-AI Collaboration and Beyond - 44th IFIP WG 5.7 International Conference, APMS 2025, Proceedings, 2026, pp. 217-232.
[6]
S. Wiesner, J. Baalsrud Hauge and K. D. Thoben, "Enabling Circular Business Models and Digital Transformation for Sustainable Value Creation in European Manufacturing SMEs," in Advances in Production Management Systems. Cyber-Physical-Human Production Systems: Human-AI Collaboration and Beyond - 44th IFIP WG 5.7 International Conference, APMS 2025, Proceedings, 2026, pp. 550-564.
[7]
Y. Jeong, C. Kober and M. Fette, "Integrating Large Language Models and Digital Twins in Manufacturing : Opportunities and Challenges for Production Logistics and Assembly Environments," in Advances in Production Management Systems. Cyber-Physical-Human Production Systems: Human-AI Collaboration and Beyond - 44th IFIP WG 5.7 International Conference, APMS 2025, Proceedings, 2026, pp. 528-542.
[8]
K. Cho et al., "Graph Attention Network Based Deep Reinforcement Learning Approach for Dynamic Human Order Picking," in Advances in Production Management Systems. : Cyber-Physical-Human Production Systems: Human-AI Collaboration and Beyond - 44th IFIP WG 5.7 International Conference, APMS 2025, Proceedings, Part I, 2026, pp. 450-465.
[9]
J. Baalsrud Hauge and I. A. Stefan, "The Contribution of Cybersecurity for Improving the Resilience of Supply Chains – The Need of Employee Training," in Advances in Production Management Systems. Cyber-Physical-Human Production Systems: Human-AI Collaboration and Beyond - 44th IFIP WG 5.7 International Conference, APMS 2025, Proceedings, 2026, pp. 246-262.
[10]
S. E. Birkie, Z. Chavez and R. Laurenti, "Green Design Methodology in Production Equipment Design and Acquisition: State of Practice and Way Forward," in Advances in Production Management Systems. Cyber-Physical-Human Production Systems: Human-AI Collaboration and Beyond - 44th IFIP WG 5.7 International Conference, APMS 2025, Proceedings, 2026, pp. 566-579.
[11]
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.
[12]
Y. Qin et al., "A tool wear monitoring method based on data-driven and physical output," Robotics and Computer-Integrated Manufacturing, vol. 91, 2025.
[13]
S. Das et al., "Towards gamification for spatial digital learning environments," Entertainment Computing, vol. 52, 2025.
[14]
T. Wang et al., "A human-inspired slow-fast dual-branch method for product quality prediction of complex manufacturing processes with hierarchical variations," Advanced Engineering Informatics, vol. 64, 2025.
[15]
V. Rahawi, "Optimering av VOR-processen i Scanias reservdelslogistik," , 2025.
[16]
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.
[17]
Z. Wang et al., "A novel hybrid LSTM and masked multi-head attention based network for energy consumption prediction of industrial robots," Applied Energy, vol. 383, 2025.
[18]
E. Weber, "Reverse engineering av Embedded Test Systems," , 2025.
[19]
Q. Liu et al., "A method for remaining useful life prediction of milling cutter using multi-scale spatial data feature visualization and domain separation prediction network," Mechanical systems and signal processing, vol. 225, 2025.
[20]
B. Wang et al., "A deep learning-enabled visual-inertial fusion method for human pose estimation in occluded human-robot collaborative assembly scenarios," Robotics and Computer-Integrated Manufacturing, vol. 93, 2025.
[21]
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.
[22]
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.
[23]
Z. Wang et al., "Energy consumption modeling based on operation mechanisms of industrial robots," Robotics and Computer-Integrated Manufacturing, vol. 94, 2025.
[24]
S. R. Kalvakolu et al., "Combining 360° Spaces and Social VR," in Games and Learning Alliance - 13th International Conference, GALA 2024, Proceedings, 2025, pp. 375-380.
[25]
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.
[26]
J. Leng et al., "Federated learning-empowered smart manufacturing and product lifecycle management : A review," Advanced Engineering Informatics, vol. 65, 2025.
[27]
M. Gonzalez, M. J. Coll-Araoz and A. Archenti, "Enhancing reliability in advanced manufacturing systems : A methodology for the assessment of detection and monitoring techniques," Journal of manufacturing systems, vol. 79, pp. 318-333, 2025.
[28]
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.
[29]
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.
[30]
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.
[31]
Z. Wang et al., "Industrial Robots Energy Consumption Modeling, Identification and Optimization Through Time-Scaling," IEEE Transactions on robotics, vol. 41, pp. 1456-1475, 2025.
[32]
B. Ganesh et al., "Towards a Circular Solution for Healthcare Plastic Waste : Understanding the Legal, Operational, and Technological Landscape," Recycling, vol. 10, no. 1, 2025.
[33]
E. Fjällström and L. Edwall, "Konsekvenserna bristen på dataregistrering har för spårbarheten av medicintekniska engångsartiklar i operationssalen : En studie om patientsäkerhet, vårdkvalitet och effektivitet," , 2025.
[34]
C. Zhang et al., "Transfer learning and augmented data-driven parameter prediction for robotic welding," Robotics and Computer-Integrated Manufacturing, vol. 95, 2025.
[35]
B. Tiganus, "Defining the Digital Product Passport : Integrating Circular Economy, Digitalization, and Modularisation for Sustainability," , 2025.
[36]
M. Hayek, "Utveckling av en luftflödesbaserad värmekälla för TPU-svetsning," , 2025.
[37]
X. Deng, Z. Wang and Y. Wang, "Practical Research on Intelligent Upgrading Management of Building Steel Structure Manufacturing Factory," in Proceedings of the 14th International Conference on Logistics and Systems Engineering, 2025, pp. 268-278.
[38]
T. Wang et al., "A design framework for high-fidelity human-centric digital twin of collaborative work cell in Industry 5.0," Journal of manufacturing systems, vol. 80, pp. 140-156, 2025.
[39]
Y. Ibrahim, "Optimera återtillverkningsstrategier för elmotor i tillverkningsprocessen," , 2025.
[40]
N. D. P. Jönsson, "Grundstruktur för Lean-implementering : En fallstudie på Platt AB," , 2025.
[41]
E. Flores-García et al., "Machine learning in smart production logistics : a review of technological capabilities," International Journal of Production Research, vol. 63, no. 5, pp. 1898-1932, 2025.
[42]
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.
[43]
M. Zafarzadeh et al., "A framework and system architecture for value-oriented digital services in data-driven production logistics," International Journal of Production Research, pp. 1-21, 2025.
[44]
P. Dunaj et al., "Stiffness-controlled lathe spindle for varying operating conditions," The International Journal of Advanced Manufacturing Technology, vol. 137, no. 9-10, pp. 4521-4535, 2025.
[45]
J. Byström and M. M. Sharifi, "Optimering av inbound-processen hos DeLavals fabrik i Tumba," , 2025.
[46]
M. K. Gonzalez Bassante, "On the Accuracy of Articulated Robots : A Comprehensive Approach to Evaluate and Improve Robot Accuracy for Contact Applications," Doctoral thesis Stockholm : KTH Royal Institute of Technology, TRITA-ITM-AVL, 2025:6, 2025.
[47]
E. Izgi, "Alternativ rangeringsgränssnitt mellan rangertruck och lastbil," , 2025.
[48]
T. Alchadaydy, "Study of Influencing Factors in Evaporated Titanium and How Their Control Can Improve Production," , 2025.
[49]
R. Kalaiarasan, "Visibility in Manufacturing Supply Chains: Conceptualisation, Realisation and Implications," Doctoral thesis Stockholm : KTH Royal Institute of Technology, TRITA-ITM-AVL, 2025:12, 2025.
[50]
K. Käll and K. Rahmani, "LCA-aspekter vid verktygsrekommendationer : Utveckling av stöd för val av verktyg och skärdata," , 2025.
Full list in the KTH publications portal