APPLICATION OF ARTIFICIAL NEURAL NETWORK FOR PREDICTIVE MAINTENANCE ON PLATE HEAT EXCHANGER - MOHAMAD YAKOP, SYER MOHAMAD KHOMAINIE (2017)
Predictive maintenance system is essential to assist the plant engineer to monitor and diagnose the healthiness of the instruments. Several critical analyses on selected literature have been done as the reference for this project. Real-time monitoring need reference point from the prediction on the previous parameter to be more reliable. This is to ensure correct justification of the healthiness of the heat exchanger during the prediction is possible. With the present of big data and prediction algorithm like neural network this research proven and could be improved from time to time. Application of Artificial Neural Network (ANN) to study the healthiness of plate heat exchanger based on the identified key parameters and attributes will be the main objective of this research. The project approach is by forecasting the primary outlet temperature by next 24-hour to be compared to the real reading in the real-time monitoring of the plate heat exchanger.