Monitoring and Predictive Maintenance using Machine Learning for Industrial Machine

In recent years, the fourth industrial revolution has drawn interest from all across the world. Many concepts emerged from this new revolution, one of which being predictive maintenance. Predictive maintenance can be achieved for industrial machines through implementation of machine learning techniques to monitor real-time operational data. It can analyze sensor data for early prediction of equipment failures and to reduce downtime and optimizes scheduled maintenance. The purpose of this investigation is to look into developments in academic failure prediction. Predicting failures involves taking into account ideas such as design support systems and predictive maintenance decision support systems. The research gap is identified by analyzing the existing literature studies by exploring optimization strategies through integration of predictive maintenance in industrial environment in smart factories.