ScholarWorks@경상국립대학교

초록

The smart factory has evolved as a key and distinctive idea for Industry 4.0. These industries impart a significant influence on sustainable production because of their consistent industrial evolution/development. Recently, their technological advancements are deemed inevitable to survive in this competitive industry due to increasing market needs. Therefore, technological convergence analysis can provide deep insight into industrial progress and convergence. Consequently, contemporary research trends are centered on evaluating technological convergence. Although various studies are already available on the technological development of the smart factory concerning Industry 4.0, however far less significant work is available on the technological convergence assessment of the smart factory by employing data networks and patents. Therefore, this work is focused on the investigation of reliable data analysis of the smart factory's technologies and its technological convergence. This said methodology assisted in examining the network's hidden linkages using network analysis. A relevant case study of a smart factory is also discussed to evaluate its technological convergence. Thus, data-driven technologies have diverted focus from International Patent Classification (IPC) visual networks using convergence assessment tools. The findings of this study are intended to aid companies and government officials in forecasting future sustainable technological developments and decision making.

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