Research Projects

The research aims to develop an AI-based computational method using combined Artificial Neural Networks (ANN) and hierarchical Genetic Algorithms (GA) for predicting Remaining Useful Life (RUL) of complex machinery at the system level. The method aims to minimize uncertainties in RUL prediction and apply the developed AI method to predict RUL of mobile machinery from historical breakdown and vibration data. The research is part of the "SAMARTH Udyog Bharat 4.0" initiative in India, which aims to minimize wasteful processes and optimize industrial inputs. The research aims to bridge the research gap by applying intelligent computation and addressing the critical research gaps in predicting machinery RUL at the system level and managing uncertainties in RUL prediction. A new hybrid AI-based computational method is being developed to predict the Remaining Useful Life (RUL) of machinery system levels with better accuracy. The method aims to estimate the incipient multi-stage degradation of machinery, optimize signal features for faults, and determine the optimal artificial neural network model for accurate RUL prediction. The method is planned to be validated in an ongoing research project funded by the RD Board of Coal India Limited.