Yuan Rong
Papers
1
Total Citations
55
H-Index
1
About
Yuan Rong is a prominent researcher in decision science and risk assessment, with a particular focus on fuzzy logic applications in industrial and technological systems. His most influential work, "The FMEA model based on LOPCOW-ARAS methods with interval-valued Fermatean fuzzy information for risk assessment of R&D projects in industrial robot offline programming systems" (2023), has garnered 55 citations, underscoring its impact on advancing failure mode and effects analysis (FMEA) under uncertainty. Rong’s major contributions lie in integrating novel multi-criteria decision-making (MCDM) frameworks—such as LOPCOW and ARAS—with interval-valued Fermatean fuzzy sets to enhance risk evaluation in complex engineering environments. This work has provided a robust methodology for assessing R&D project risks in robotics, offering practical tools for industrial engineers and decision-makers. His research bridges theoretical fuzzy set advancements with real-world applications, particularly in automation and manufacturing. Rong’s achievements include pioneering hybrid MCDM models that improve precision and reliability in risk prioritization, making him a key figure in the evolution of fuzzy decision analysis. His work continues to inspire students and researchers exploring the intersection of uncertainty modeling and industrial risk management.
Research Focus
Key Achievements
Top Papers
- 1