Identifying Gaps in Automating the Assessment of Technology Readiness Levels

Abstract

Crucial in the design process, Technology Readiness Levels are a common form of technology maturity assessment. Studies suggest that the TRL scale can be subjective and biased. Automating the assessment can reduce human bias. This paper highlights important challenges of automation by presenting data collected on 15 technologies from the nanotechnology sector. Our findings show that, contrary to claims from the literature, patent data exists for low maturity technologies and may be useful for automation. We also found that there exists unexpected trends in data publications at TRL 2, 3 and 4.