*Result*: Sequence optimization for human-oriented human–robot collaborative disassembly of spent lithium-ion battery.

*With the development of intelligent manufacturing and the implementation of carbon peak, the recycling of spent lithium-ion batteries has become a hot topic in academia and industry. To optimize human–robot collaborative disassembly time and human-factor load of spent lithium-ion batteries, this work carries out research on human–robot collaborative disassembly sequence planning of spent lithium-ion batteries based on sustainable and intelligent manufacturing. Firstly, a human–robot collaborative disassembly sequence optimization model is constructed, namely, a mathematical model considering disassembly completion time and human fatigue. Secondly, an improved artificial bee colony algorithm is proposed, which increases the global search ability by introducing elite retention strategy, improves the local search ability by using learning strategy and filters the crowding distance Pareto solution set, so as to improve the solving efficiency and quality. Finally, the human–robot collaborative disassembly experiment is carried out through a lithium-ion battery pack. To verify the effectiveness of the proposed model and the feasibility of the algorithm, metaheuristic algorithms are selected to carry out comparative analysis of different strategy models and different task scales. The experimental results show that the proposed model and algorithm can ensure the efficiency of disassembly and alleviate the fatigue of workers well. The research results can enrich the technology of intelligent disassembly planning, and have important theoretical reference value for improving the competitiveness and sustainable development of remanufacturing enterprises. [ABSTRACT FROM AUTHOR]*