Machine Learning Can Maximize Efficiency in an Industrial Process

Abstract

A factory's production line is a series of consecutive processes designed to refine raw materials into a finished product that may be used for further processing. To ensure that the quality of the production process and the goods are met, it is critical to monitor production lines. The total production line process can now create a great deal of data due to the enhanced digitalization.

To improve quality control, evaluate risks, and save money, machine learning algorithms leverage the data provided by the production line. Industrial process monitoring and optimization can benefit greatly from new artificial intelligence (AI) and machine learning (ML) solutions that have arisen as a result of Industry 4.0's rapid development.

The proliferation of hybrid Internet of Things (IoT) architectures supported by polyglot data repositories and big (small) data analytics capabilities is one of the key elements of this new industrial revolution, which is enabled by the hatching of massive process monitoring data from CPS distributed along manufacturing processes.