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About

Guochen Duan is a leading researcher in the field of intelligent mineral processing and robotic crushing technology. His work centers on the design, modeling, and optimal control of the 6-DOF (degree of freedom) robotic crusher, a next-generation machine that promises greater efficiency and precision in rock fragmentation. Duan’s major contributions include establishing the first single-particle compression ratio function for granular materials, which directly informs the prediction of crushed product size distribution and the wear patterns of mantle liners. He has also pioneered multi-objective optimal control methods that simultaneously optimize crushing effect, energy consumption, output, and liner wear. His 2021 paper on compression ratio and wear prediction has garnered 4 citations, while his 2024 work on multi-objective control and his 2014 energy consumption model each have 2 citations, reflecting a steady, foundational influence on the field. Duan’s research is notable for integrating mechanical modeling with real-time control, offering a systematic approach to reducing energy use and extending equipment life in mineral processing. His work is essential reading for engineers and researchers developing autonomous, high-efficiency crushing systems.