Journal article Open Access

Machine Learning and Deep Learning in smart manufacturing: The Smart Grid paradigm

Kotsiopoulos, Thanasis; Sarigiannidis, Panagiotis; Ioannidis, Dimosthenis; Tzovaras, Dimitrios

Industry 4.0 is the new industrial revolution. By connecting every machine and activity through network sensors to the Internet, a huge amount of data is generated. Machine Learning (ML) and Deep Learning (DL) are two subsets of Artificial Intelligence (AI), which are used to evaluate the generated data and produce valuable information about the manufacturing enterprise, while introducing in parallel the Industrial AI (IAI). In this paper, the principles of the Industry 4.0 are highlighted, by giving emphasis to the features, requirements, and challenges behind Industry 4.0. In addition, a new architecture for AIA is presented. Furthermore, the most important ML and DL algorithms used in Industry 4.0 are presented and compiled in detail. Each algorithm is discussed and evaluated in terms of its features, its applications, and its efficiency. Then, we focus on one of the most important Industry 4.0 fields, namely the smart grid, where ML and DL models are presented and analysed in terms of efficiency and effectiveness in smart grid applications. Lastly, trends and challenges in the field of data analysis in the context of the new Industrial era are highlighted and discussed such as scalability, cybersecurity, and big data.

Files (809.0 kB)
Name Size
[30] Machine_Learning_and_Deep_Learning_in_Smart_Manufacturing_The_Smart_Grid_Paradigm.pdf
md5:0db7ca68655c2a3a926ef2e9cce3a4d6
809.0 kB Download
153
433
views
downloads
Views 153
Downloads 433
Data volume 350.3 MB
Unique views 104
Unique downloads 422

Share

Cite as