In many industrial fields, maintenance workers play a crucial role in ensuring the smooth operation of complex machinery and infrastructure. However, due to rapid technological advancements and increasing system complexity in recent years, workers are required to adapt to these changes. Furthermore, a decline in the number of skilled workers is anticipated in the future, necessitating measures to maintain and strengthen operational structures. On the other hand, the remarkable progress in generative AI technology suggests possibilities for automating routine tasks that can be handled with general knowledge and for implementing diagnostic agents that mimic expert judgment. Then this study proposed an architecture that integrates generative AI technology into maintenance operations and suggested possibilities for reducing human risk prediction tasks by about 50%.
HISHIKAWA et al. (Wed,) studied this question.