Abstract:
Condition Monitoring and Predictive Analysis is very essential part for Industrial machines 4.0. Late 1700s, manufacturing was made by people using hand tools or basic machines. As Industry Revolution Started from 18th century, no doubt life become easy and fast but drawback is that there is no any analysis and monitoring for industry at that time, which is very essential for life of industrial machines. As century passed and industry revolution become more and more advanced also human being’s life become more efficient and advanced. Also, it is advanced time as Real Time system Wi-Fi or Cloud system, so it is need for our save our data. Industrial machines or plants face different problems after a specific time which in not determined but can be improved via condition and predictive analysis via machine learning. Recently, there were launched many different mechanisms for conditioning for machine. We are presenting Portable Condition Monitoring Unit (PCMU), which will monitor and predict health of industry 4.0. The authors are introducing eight (8) different parts of machines which effect health of plant or machine i.e. Temperature, Vibration, Acceleration, Humidity, Pressure, Magnetic Field, Noise and Gyroscope. By applying these methodologies and giving machine learning to industry 4.0 or plants, it can increase maintenance and health as well as efficiency of industry.
