Abstract
Machine learning (ML) and the adoption of Industry 4.0 have a huge impact on the manufacturing sector. The use of ML in industrial environments has the potential to completely transform the way choices are made and processes are optimized. However, a number of issues need to be resolved before the potential of ML in the industrial sector can be fully realized. In order to identify key issues and unmet research needs, this study aims to assess the current state of ML in the manufacturing industry. The article discusses the uses, advantages and disadvantages of machine learning (ML) in production and industrial systems. The study also addresses the need to combine various ML techniques and create more scalable and generalizable models. Finally, this research provides a detailed overview of the current state of ML in the manufacturing industry and identifies areas for future research.