Performance degradation/failure detection on a Independent Cart system using ANN

Asset management is a critical area of machine management and maintenance, especially in areas where the cost of asset failure is extremely high and sometimes dangerous. This work explores the use of Artificial Neural Network (ANN) in identifying a mover in independent cart system (ICT) technology, irrespective of the identification assigned to the mover at power up time, and also identify the mover that is having degraded performance, in real-time. With the training data that mimics degraded characteristics of a mover, possibly also predict the cause of degradation of performance/failure, and a time window in which corrective action would be needed on the mover.