In the smart manufacturing era, the dynamics of monitoring and maintenance of the machines are changed. After the 4th industrial revolution, artificial intelligence and machine learning techniques are proven to be beneficial for carrying out predictive maintenance of machines. Internet of Things (IoT) along with the Cyber-Physical Systems (CPS) has made it possible to conduct a data-driven prognosis of a system. Predictive maintenance techniques have been developed in order to monitor an in-service machine for estimating when maintenance should be performed. Big data analysis and machine learning techniques enable the detection of the current health state and the remaining useful life of the equipment.