IoT-based predictive maintenance using AI/ML: A systematic review.

This paper presents the research on Improvement in OEE for manufacturing industries. The Industrial Revolution was an era of significant technological advancement which begun in the 18th century and transformed the way that goods were produced. The introduction of steam power, mechanization, and mass production led to increased efficiency and productivity, but also had significant social and environmental impacts. Today, we are experiencing another transformation in the way that goods are produced, and services are delivered through the Industrial Internet of Things (IIoT). IIoT combines traditional industrial processes with modern technology such as sensors, data analytics, and machine learning to optimize and automate processes. Like the Industrial Revolution, IIoT is transforming the way that goods are produced, but with some significant differences. The primary focus of IIoT is not just to increase efficiency and productivity, but also to improve quality control, reduce downtime, and optimize resource usage. IIoT enables machines and devices to communicate with one another in real-time, providing valuable insights into the performance of industrial processes. This allows for predictive maintenance, where machines can be repaired or replaced before they fail, reducing downtime and maintenance costs. The use of IIoT also enables companies to collect data on every aspect of the production process, providing insights into the use of energy and resources. This data can be used to optimize processes, reducing waste and improving efficiency. [ABSTRACT FROM AUTHOR]