MSEC2021-63522 Multi-Robotic Disassembly Line Balancing Using Deep Reinforcement Learning

von Mei, Kai
Veröffentlicht in ASME International Manufacturing Science and Engineering Conference (16. : 2021 : Online) Proceedings of the ASME 2021 16th International Manufacturing Science and Engineering Conference (MSEC2021) ; Volume 2: Manufacturing processes - manufacturing systems - nano/micro/meso manufacturing - quality and reliability (2021)

Optimisation of robotic disassembly for remanufacturing

von Laili, Yuanjun
Veröffentlicht 2022

Evolutionary many-objective optimization for mixed-model disassembly line balancing with multi-robotic workstations

von Fang, Yilin
Veröffentlicht in European journal of operational research (2019)

TEMPERATURE MONITORING AND CONTROL OF PAN SOLUTION PIPELINE BASED ON FIBER BRAGG GRATING SENSING

von Cai, Zhigiang Cai. Yijie
Veröffentlicht in International Conference on Computers & Industrial Engineering (49. : 2019 : Peking) 49th International Conference on Computers & Industrial Engineering 2019 (CIE49) ; Volume 2 of 3 (2020)

Xingzheng susongfa xiugai ziliao huizuan : = Xingzheng susongfa xiugai ziliao huizuan

von Jiang, Bixin
Veröffentlicht 20153

MSEC2020-8265 Interval Multi-Objective Evolutionary Optimization for Disassembly Line Balancing With Uncertain Task Time

von Fang, Yilin
Veröffentlicht in ASME International Manufacturing Science and Engineering Conference (15. : 2020 : Online) Proceedings of the ASME 15th International Manufacturing Science and Engineering Conference - 2020 ; Volume 2: Manufacturing processes - manufacturing systems - nano/micro/meso manufacturing - quality and reliability (2020)

MSEC2019-2773 Minimizing Energy Consumption and Line Length of Mixed-Model Multi-Robotic Disassembly Line Systems Using Multi-Objective Evolutionary Optimization

von Fang, Yilin
Veröffentlicht in ASME International Manufacturing Science and Engineering Conference (14. : 2019 : Erie, Pa.) Proceedings of the ASME 14th International Manufacturing Science and Engineering Conference - 2019 ; Volume 1: Additive manufacturing - manufacturing equipment and systems - bio and sustainable manufacturing (2019)