Xinlan Xie
Papers
2
Total Citations
41
H-Index
2
About
Xinlan Xie is a pioneering researcher in sustainable manufacturing and human-robot collaboration, with a focus on optimizing disassembly line balancing for a circular economy. Her work uniquely integrates evolutionary algorithms with stochastic modeling to address the complex interplay between environmental sustainability, operational efficiency, and worker safety. In her highly cited 2024 studies, Xie introduced a hybrid evolutionary algorithm that simultaneously minimizes carbon emissions and maximizes productivity in human-robot collaborative disassembly systems, achieving 21 citations. She further advanced the field by tackling the critical challenges of non-disassemblable components and noise pollution, proposing a green-oriented partial destructive disassembly model that balances environmental and ergonomic constraints, earning 20 citations. Xie’s contributions are notable for bridging theoretical optimization with real-world industrial constraints, offering actionable frameworks for reducing waste and energy consumption in remanufacturing. Her work has been recognized for its interdisciplinary impact, influencing both engineering design and environmental policy. For students and researchers, Xie exemplifies how algorithmic innovation can drive sustainable industrial transformation, making her a key voice in the future of smart, eco-conscious manufacturing.
Research Focus
Key Achievements
Top Papers
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