Deep reinforcement learning based preventive maintenance policy for serial production lines J Huang, Q Chang, J Arinez Expert Systems with Applications 160, 113701, 2020 | 144 | 2020 |
Optimizing task scheduling in human-robot collaboration with deep multi-agent reinforcement learning T Yu, J Huang, Q Chang Journal of Manufacturing Systems 60, 487-499, 2021 | 69 | 2021 |
Deep multi-agent reinforcement learning for multi-level preventive maintenance in manufacturing systems J Su, J Huang, S Adams, Q Chang, PA Beling Expert systems with applications 192, 116323, 2022 | 56 | 2022 |
Mastering the working sequence in human-robot collaborative assembly based on reinforcement learning T Yu, J Huang, Q Chang IEEE Access 8, 163868-163877, 2020 | 47 | 2020 |
A real-time maintenance policy for multi-stage manufacturing systems considering imperfect maintenance effects J Huang, Q Chang, J Zou, J Arinez IEEE Access 6, 62174-62183, 2018 | 35 | 2018 |
A maintenance and energy saving joint control scheme for sustainable manufacturing systems J Huang, Q Chang, J Arinez, G Xiao Procedia CIRP 80, 263-268, 2019 | 27 | 2019 |
Product completion time prediction using a hybrid approach combining deep learning and system model J Huang, Q Chang, J Arinez Journal of Manufacturing Systems 57, 311-322, 2020 | 24 | 2020 |
Machine preventive replacement policy for serial production lines based on reinforcement learning J Huang, Q Chang, N Chakraborty 2019 IEEE 15th International Conference on Automation Science and …, 2019 | 17 | 2019 |
First time quality diagnostics and improvement through data analysis: A study of a crankshaft line X Ou, J Huang, Q Chang, S Hucker, JG Lovasz Procedia Manufacturing 49, 2-8, 2020 | 16 | 2020 |
Graph neural network and multi-agent reinforcement learning for machine-process-system integrated control to optimize production yield J Huang, J Su, Q Chang Journal of Manufacturing Systems 64, 81-93, 2022 | 15 | 2022 |
Integrated process-system modelling and control through graph neural network and reinforcement learning J Huang, J Zhang, Q Chang, RX Gao CIRP Annals 70 (1), 377-380, 2021 | 12 | 2021 |
Dynamic robot assignment for flexible serial production systems K Bhatta, J Huang, Q Chang IEEE Robotics and Automation Letters 7 (3), 7303-7310, 2022 | 11 | 2022 |
Data-enabled permanent production loss analysis for serial production systems with variable cycle time machines C Li, J Huang, Q Chang IEEE Robotics and Automation Letters 6 (4), 6418-6425, 2021 | 11 | 2021 |
Effect of formation pattern on schooling energetics in fish-like swimming Y Pan, P Han, J Huang, H Dong Fluids Engineering Division Summer Meeting 83730, V003T05A046, 2020 | 9 | 2020 |
Modeling and dynamic assignment of the adaptive buffer spaces in serial production lines J Huang, Q Chang, J Arinez Journal of Manufacturing Science and Engineering 143 (3), 031005, 2021 | 6 | 2021 |
Distributed production scheduling for multi-product flexible production lines J Huang, Q Chang, J Arinez 2020 IEEE 16th International Conference on Automation Science and …, 2020 | 4 | 2020 |
Modeling and Analysis of Multi-Product Manufacturing Systems With Two Machines and One Buffer J Huang, Q Chang, J Arinez International Manufacturing Science and Engineering Conference 58745 …, 2019 | 3 | 2019 |
Paint shop vehicle sequencing based on quantum computing considering color changeover and painting quality J Huang, HT Fan, G Xiao, Q Chang arXiv preprint arXiv:2206.11204, 2022 | 2 | 2022 |
Real-time Control of Maintenance on Deteriorating Manufacturing System J Huang, Q Chang, J Zou, J Arinez, G Xiao 2018 IEEE 14th International Conference on Automation Science and …, 2018 | 2 | 2018 |
Predicting the Distribution of Product Completion Time in Multi-Product Manufacturing Systems J Huang, Q Chang, J Arinez 2021 IEEE 17th International Conference on Automation Science and …, 2021 | 1 | 2021 |