Skip to main content

Publications

Publications within Sustainable Production Systems

[1]
Q. Ji et al., "Optimal shape morphing control of 4D printed shape memory polymer based on reinforcement learning," Robotics and Computer-Integrated Manufacturing, vol. 73, 2022.
[3]
S. Li et al., "Toward Proactive Human-Robot Collaborative Assembly : A Multimodal Transfer-Learning-Enabled Action Prediction Approach," IEEE transactions on industrial electronics (1982. Print), vol. 69, no. 8, pp. 8579-8588, 2022.
[4]
T. K. Agrawal et al., "Demonstration of a blockchain-based framework using smart contracts for supply chain collaboration," International Journal of Production Research, pp. 1-20, 2022.
[5]
J. Jiang et al., "The state of the art of search strategies in robotic assembly," Journal of Industrial Information Integration, vol. 26, 2022.
[6]
S. Liu, L. Wang and X. V. Wang, "Multimodal Data-Driven Robot Control for Human-Robot Collaborative Assembly," Journal of manufacturing science and engineering, vol. 144, no. 5, 2022.
[7]
P. Wang et al., "The Existence of Autonomous Chaos in EDM Process," Machines, vol. 10, no. 4, 2022.
[8]
Y. Shi et al., "A Cognitive Digital Twins Framework for Human-Robot Collaboration," in 3Rd International Conference On Industry 4.0 And Smart Manufacturing, 2022, pp. 1867-1874.
[9]
X. Li et al., "Systematic review on tool breakage monitoring techniques in machining operations," International journal of machine tools & manufacture, vol. 176, 2022.
[10]
S. Liu, "Multimodal Human-Robot Collaboration in Assembly," Doctoral thesis Brinellvägen 68, 114 28 Stockholm, Sweden : KTH Royal Institute of Technology, TRITA-ITM-AVL, 2022:12, 2022.
[11]
A. Zhang et al., "Velocity effect sensitivity analysis of ball-end milling Ti-6Al-4 V," The International Journal of Advanced Manufacturing Technology, vol. 118, no. 11-12, pp. 3963-3982, 2022.
[12]
Q. Ji et al., "Customized protective visors enabled by closed loop controlled 4D printing," Scientific Reports, vol. 12, no. 1, 2022.
[13]
C. Yang et al., "Cloud-edge-device collaboration mechanisms of deep learning models for smart robots in mass personalization," Robotics and Computer-Integrated Manufacturing, vol. 77, pp. 102351, 2022.
[14]
H. Liu and L. Wang, "Collision-free human-robot collaboration based on context awareness," Robotics and Computer-Integrated Manufacturing, vol. 67, 2021.
[15]
H. Liang et al., "Logistics-involved QoS-aware service composition in cloud manufacturing with deep reinforcement learning," Robotics and Computer-Integrated Manufacturing, vol. 67, 2021.
[16]
K. Kang et al., "Auction-based cloud service allocation and sharing for logistics product service system," Journal of Cleaner Production, vol. 278, 2021.
[17]
C. Yang et al., "Transforming Hong Kong's warehousing industry with a novel business model : A game-theory analysis," Robotics and Computer-Integrated Manufacturing, vol. 68, 2021.
[18]
S. Treber et al., "Robust optimization of information flows in global production networks using multi-method simulation and surrogate modelling," CIRP - Journal of Manufacturing Science and Technology, vol. 32, pp. 491-506, 2021.
[19]
F. Tao et al., "Digital twin towards smart manufacturing and industry 4.0," Journal of manufacturing systems, vol. 58, pp. 1-2, 2021.
[21]
Y. Liu et al., "Industrial Internet for Manufacturing," Robotics and Computer-Integrated Manufacturing, vol. 70, 2021.
[22]
X.-C. Xi et al., "Velocity planning in multi-axis EDM based on a coder-player architecture," Journal of manufacturing systems, vol. 59, pp. 299-309, 2021.
[24]
S. Gu et al., "Gaze Estimation via a Differential Eyes' Appearances Network with a Reference Grid," ENGINEERING, vol. 7, no. 6, pp. 777-786, 2021.
[25]
X. Xu et al., "Smart and resilient manufacturing in the wake of COVID-19," Journal of manufacturing systems, vol. 60, pp. 707-708, 2021.
[26]
Y. Wang et al., "Digital twin enhanced fault prediction for the autoclave with insufficient data," Journal of manufacturing systems, vol. 60, pp. 350-359, 2021.
[27]
S. Li et al., "Towards proactive human-robot collaboration : A foreseeable cognitive manufacturing paradigm," Journal of manufacturing systems, vol. 60, pp. 547-552, 2021.
[29]
J. Franke et al., "Electronic module assembly," CIRP annals, vol. 70, no. 2, pp. 471-493, 2021.
[31]
Q. Ji et al., "Feedback control for the precise shape morphing of 4D printed shape memory polymer," IEEE transactions on industrial electronics (1982. Print), pp. 12698-12707, 2021.
[32]
S. Thorapalli Muralidharan et al., "A soft quadruped robot enabled by continuum actuators," in 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE), 2021, pp. 834-840.
[33]
N. A. Theissen et al., "Quasi-Static Compliance Calibration ofSerial Articulated Industrial Manipulators," International Journal of Automation Technology, no. 5, pp. 590-598, 2021.
[35]
X. Xu et al., "Industry 4.0 and Industry 5.0-Inception, conception and perception," Journal of manufacturing systems, vol. 61, pp. 530-535, 2021.
[36]
X. Liu et al., "Feature extraction of milling chatter based on optimized variational mode decomposition and multi-scale permutation entropy," The International Journal of Advanced Manufacturing Technology, vol. 114, no. 9-10, pp. 2849-2862, 2021.
[37]
S. Liu et al., "Leveraging multimodal data for intuitive robot control towards human-robot collaborative assembly," in Procedia CIRP of the 54th Conference on Manufacturing Systems, 2021, pp. 206-211.
[38]
[39]
B. Meng et al., "Research Progress on the Architecture and Key Technologies of Machine Tool Intelligent Control System," Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, vol. 57, no. 9, pp. 147-166, 2021.
[40]
P. Troll, K. Szipka and A. Archenti, "Performance evaluation of LiDAR-based position measurement system," in Proceedings of the 21st International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2021, 2021, pp. 325-326.
[41]
N. A. Theissen et al., "Measurementand identification of dynamic translational stiffness matrix on machine tools understatic preloads," in European Society for Precision Engineering and Nanotechnology: 21stInternational Conference and Exhibition 7th – 11th June 2021., 2021.
[42]
A. Haghighi, A. Mohammed and L. Wang, "Energy efficient multi-robotic 3d printing for large-scale construction - Framework, challenges, and a systematic approach," in Proceedings of the ASME 2021 16th International Manufacturing Science and Engineering Conference, MSEC 2021, 2021.
[43]
J. Yao et al., "Robotic grasping training using deep reinforcement learning with policy guidance mechanism," in Proceedings of the ASME 2021 16th International Manufacturing Science and Engineering Conference, MSEC 2021, 2021.
[44]
X. Liu et al., "Intelligent Management and Control Technology of Cutting Tool Life-cycle for Intelligent Manufacturing," Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, vol. 57, no. 10, pp. 196-219, 2021.
[45]
S. Liu, L. Wang and X. V. Wang, "Sensorless haptic control for human-robot collaborative assembly," CIRP - Journal of Manufacturing Science and Technology, vol. 32, pp. 132-144, 2021.
[46]
S. Liu, L. Wang and X. V. Wang, "Function block-based multimodal control for symbiotic human-robot collaborative assembly," Journal of manufacturing science and engineering, vol. 143, no. 9, pp. 1-10, 2021.
[47]
S. Liu, L. Wang and X. V. Wang, "Sensorless force estimation for industrial robots using disturbance observer and neural learning of friction approximation," Robotics and Computer-Integrated Manufacturing, vol. 71, pp. 1-11, 2021.
[49]
C. Zhao, L. Wang and X. Zhang, "Service agent networks in cloud manufacturing : Modeling and evaluation based on set-pair analysis," Robotics and Computer-Integrated Manufacturing, vol. 65, 2020.
[50]
Y. Lu, X. Xu and L. Wang, "Smart manufacturing process and system automation - A critical review of the standards and envisioned scenarios," Journal of manufacturing systems, vol. 56, pp. 312-325, 2020.
Full list in the KTH publications portal