A review of research on extension strategy generation technology for the field of intelligent manufacturing engineering

Extension theory introduces new aspects in the modern technological environment with the use and development of artificial intelligence, ChatGPT, and data mining technologies. This paper summarizes the intelligent extension strategy generation method, clarifies the new decision-making method combining artificial intelligence and extension theory, and summarizes the principle, application, and trend analysis of extension strategy in the field of manufacturing engineering to further realize the mechanical integration of human-machine multi-information dynamic processing and physical systems. The Expandable Policy Generation (EPG) and the Extension Data Warehouse are specifically discussed in this paper, along with their relationship and generation processes. Additionally, a method to extract and store the extension knowledge used to resolve the contradiction problem in the extensive knowledge base is suggested. The core principles and processes from data-driven technology, data storage, and extended knowledge representation to optimal scheme generation are further elaborated upon in this study, which also highlights the actual implementation of EPG in the field of industrial engineering. This study concludes by summarizing the benefits and drawbacks of EPG and suggesting future research areas to advance the advancement of technology in the realm of intelligent manufacturing.