Jinliang Zhang

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About

Jinliang Zhang is a leading researcher in remanufacturing engineering, with a focused expertise in robotic disassembly sequence planning and the intelligent handling of end-of-life products. His work directly addresses a critical challenge in sustainable manufacturing: the inherent uncertainty of parts quality in discarded products. Zhang’s major contribution lies in developing advanced planning frameworks that account for parts with failure features—such as wear, fracture, deformation, and corrosion—enabling robotic systems to adapt disassembly strategies in real time. His highly cited 2023 paper, "Robotic disassembly sequence planning considering parts failure features," has garnered 18 citations, establishing a foundational approach for improving disassembly efficiency and automation reliability. By integrating failure feature recognition into sequence optimization, Zhang’s research significantly enhances the viability of robotic remanufacturing, reducing waste and resource consumption. His work is pivotal for students and researchers exploring the intersection of robotics, artificial intelligence, and circular economy principles, offering practical solutions for the sustainable management of complex, damaged product streams.