Runhua Tan

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About

Runhua Tan is a leading figure in engineering design and innovation methodology, with a focus on systematic approaches to creative problem-solving. His research centers on three key areas: knowledge representation for design, patent-driven product innovation, and rehabilitation robotics. Tan’s most notable contribution is the development of the R-SBF (Representation-State-Behavior-Function) ontology model, which enables analogical stimuli retrieval—a method that systematically mines existing knowledge to inspire novel designs. This work, cited 24 times, provides a foundational framework for computational design support. In the realm of patent strategy, Tan introduced a method for designing around bundle patent portfolios by leveraging technological evolution trends, offering firms a structured way to bypass competitors’ intellectual property while innovating. This approach, with 10 citations, bridges patent analysis and product development. Additionally, Tan contributed to medical robotics by designing a teaching and playback control system for a parallel robot used in ankle joint rehabilitation, demonstrating his versatility in applying design principles to real-world health challenges. With a career spanning both theoretical frameworks and practical implementations, Tan’s work has influenced how engineers systematically approach innovation, making him a key researcher in design theory and applied robotics.