Forecasting Emerging Technologies in Intelligent Machine Tools: A Novel Framework Based on Community Analysis

Abstract

Having emerged as strategic focal points in industrial transformation and technological innovation, intelligent machine tools are pivotal in the field of intelligent manufacturing. Accurately forecasting emerging technologies within this domain is crucial for guiding intelligent manufacturing’s evolution and fostering rapid innovation. However, prevailing research methodologies exhibit limitations, often concentrating on popular topics at the expense of lesser-known yet significant areas, thereby impacting the accurate identification of research priorities. The complex, systemic, and interdisciplinary nature of intelligent machine tool technology challenges traditional research approaches, particularly in assessing technological maturity and intricate interactions. To overcome these challenges, we propose a novel framework that leverages technological communities for a comprehensive analysis. This approach clusters data into specific topics which are reflective of the technology system, facilitating detailed investigations within each area. By refining community analysis methods and integrating structural and interactive community features, our framework significantly improves the precision of emerging technology predictions. Our research not only validates the framework but also projects key emerging technologies in intelligent machine tools, offering valuable insights for business leaders and scholars alike.

Keywords

• intelligent machine tools
• emerging technology forecasting
• community detection
• community classification