Аңдатпа
Additive layer manufacturing (ALM) and digital twin (DT) play a vital role in the fourth industrial revolution. Both additive manufacturing (AM) and digitalization have received attention from the research community as independent research areas. AM creates an opportunity for manufacturing intricate shapes, parts consolidation and optimization that is very beneficial for the aerospace industry; however, it has a significant drawback in the repeatability of the process due to many production variables. Process monitoring and supervision through DT could alleviate this problem. Furthermore, there is lack of knowledge about integrating these two technologies. Therefore, this paper aims to formulate the main challenges of developing a digital twin for ALM in the aerospace industry. The paper focuses on the data and physical layer challenges of DT technology. Also, it proposes the implementation process of database HDF5 format and Artificial Intelligence that are part of DT for ALM that can change the certification of aerospace industry products by qualifying the process of production. The paper employs the method of in-situ production process monitoring by comparing the correspondence of apparent and latent characteristics of printed parts with required standards. It would create an opportunity for safety improvement and broader application of ALM in the aerospace industry.