Methods of Decision-Making Using Artificial Intelligence for Predictive Maintenance

Predictive maintenance (PM) plays a crucial role in optimizing maintenance processes and reducing downtime in various industries. This project focuses on the development of an artificial intelligence (AI) model for predictive maintenance, with the aim of improving efficiency compared to traditional methods. The methodology involves the use of sensors, the Internet of Things (IoT), and other advanced technologies to collect data from a system. These data are then processed, and a suitable AI model is selected and trained to make accurate predictions. The results demonstrate promising predictive capabilities that contribute to enhancing the maintenance process and generating significant benefits compared to conventional approaches. This project highlights the potential of AI-based methods in predictive maintenance, underscoring their superiority in terms of accuracy and efficiency. The successful implementation of this methodology opens up new avenues for leveraging advanced technologies to optimize maintenance practices across various industries.