Qinglian Lin

Technische Universität Berlin, Xiamen University

Papers

Total Citations

195

H-Index

About

Qinglian Lin is a leading researcher in multi-criteria decision-making (MCDM) and risk assessment, with a focus on industrial and healthcare robotics. Her pioneering work integrates fuzzy linguistic methods, data envelopment analysis (DEA), and cloud models to solve complex selection and evaluation problems. In her highly cited 2013 paper (101 citations), she developed an interval 2-tuple linguistic MCDM method for robot evaluation and selection, addressing the challenge manufacturers face in choosing optimal robots amid growing production demands and model diversity. More recently, her 2022 study (94 citations) introduced a novel risk assessment framework combining FMEA, DEA, and cloud models, applied to robot-assisted rehabilitation—a critical area for patient safety and device reliability. Lin’s contributions have significantly advanced decision-support tools in engineering, enabling more systematic, data-driven choices in robotics. Her work not only enhances manufacturing efficiency but also improves safety in medical robotics, demonstrating broad interdisciplinary impact. With over 195 citations across her top papers, Lin continues to shape how researchers and practitioners approach complex evaluation problems in robotics and beyond.