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Publikationer

Här visas de 50 senaste publikationerna från institutionen för Produktionsutveckling.

[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 och M. Kalverkamp, "Reflections on the Usage of a Commercial-Off-The-Shelf Game in Teaching Logistics," i 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, s. 217-232.
[6]
S. Wiesner, J. Baalsrud Hauge och K. D. Thoben, "Enabling Circular Business Models and Digital Transformation for Sustainable Value Creation in European Manufacturing SMEs," i 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, s. 550-564.
[7]
Y. Jeong, C. Kober och M. Fette, "Integrating Large Language Models and Digital Twins in Manufacturing : Opportunities and Challenges for Production Logistics and Assembly Environments," i 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, s. 528-542.
[8]
K. Cho et al., "Graph Attention Network Based Deep Reinforcement Learning Approach for Dynamic Human Order Picking," i 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, s. 450-465.
[9]
J. Baalsrud Hauge och I. A. Stefan, "The Contribution of Cybersecurity for Improving the Resilience of Supply Chains – The Need of Employee Training," i 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, s. 246-262.
[10]
S. E. Birkie, Z. Chavez och R. Laurenti, "Green Design Methodology in Production Equipment Design and Acquisition: State of Practice and Way Forward," i 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, s. 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, s. 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, s. 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," i Games and Learning Alliance - 13th International Conference, GALA 2024, Proceedings, 2025, s. 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, s. 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 och A. Archenti, "Enhancing reliability in advanced manufacturing systems : A methodology for the assessment of detection and monitoring techniques," Journal of manufacturing systems, vol. 79, s. 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]
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.
[30]
Z. Wang et al., "Industrial Robots Energy Consumption Modeling, Identification and Optimization Through Time-Scaling," IEEE Transactions on robotics, vol. 41, s. 1456-1475, 2025.
[31]
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.
[32]
E. Fjällström och L. Edwall, "Konsekvenserna bristen på dataregistrering har för spårbarheten av medicintekniska engångsartiklar i operationssalen : En studie om patientsäkerhet, vårdkvalitet och effektivitet," , 2025.
[33]
C. Zhang et al., "Transfer learning and augmented data-driven parameter prediction for robotic welding," Robotics and Computer-Integrated Manufacturing, vol. 95, 2025.
[34]
B. Tiganus, "Defining the Digital Product Passport : Integrating Circular Economy, Digitalization, and Modularisation for Sustainability," , 2025.
[35]
M. Hayek, "Utveckling av en luftflödesbaserad värmekälla för TPU-svetsning," , 2025.
[36]
X. Deng, Z. Wang och Y. Wang, "Practical Research on Intelligent Upgrading Management of Building Steel Structure Manufacturing Factory," i Proceedings of the 14th International Conference on Logistics and Systems Engineering, 2025, s. 268-278.
[37]
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, s. 140-156, 2025.
[38]
Y. Ibrahim, "Optimera återtillverkningsstrategier för elmotor i tillverkningsprocessen," , 2025.
[39]
N. D. P. Jönsson, "Grundstruktur för Lean-implementering : En fallstudie på Platt AB," , 2025.
[40]
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, s. 1898-1932, 2025.
[41]
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.
[42]
M. Zafarzadeh et al., "A framework and system architecture for value-oriented digital services in data-driven production logistics," International Journal of Production Research, s. 1-21, 2025.
[43]
P. Dunaj et al., "Stiffness-controlled lathe spindle for varying operating conditions," The International Journal of Advanced Manufacturing Technology, vol. 137, no. 9-10, s. 4521-4535, 2025.
[44]
J. Byström och M. M. Sharifi, "Optimering av inbound-processen hos DeLavals fabrik i Tumba," , 2025.
[45]
M. K. Gonzalez Bassante, "On the Accuracy of Articulated Robots : A Comprehensive Approach to Evaluate and Improve Robot Accuracy for Contact Applications," Doktorsavhandling Stockholm : KTH Royal Institute of Technology, TRITA-ITM-AVL, 2025:6, 2025.
[46]
E. Izgi, "Alternativ rangeringsgränssnitt mellan rangertruck och lastbil," , 2025.
[47]
T. Alchadaydy, "Study of Influencing Factors in Evaporated Titanium and How Their Control Can Improve Production," , 2025.
[48]
R. Kalaiarasan, "Visibility in Manufacturing Supply Chains: Conceptualisation, Realisation and Implications," Doktorsavhandling Stockholm : KTH Royal Institute of Technology, TRITA-ITM-AVL, 2025:12, 2025.
[49]
K. Käll och K. Rahmani, "LCA-aspekter vid verktygsrekommendationer : Utveckling av stöd för val av verktyg och skärdata," , 2025.
[50]
W. Farzad och N. Malakar, "Predicting Quality of Surface Roughness and Tool Wear by Different Signals and Regression Algorithms," , 2025.
Fullständig lista i KTH:s publikationsportal