Predictive system maintenance model based on machine learning

Abstract

In an example embodiment, a predictive system maintenance module is created based on machine learning. The predictive system maintenance module achieves an improvement in predicting condition-based maintenance decision-making through a cloud-based approach, using a wide variety of information. Factors that influence downtime loss are identified and a generalized loss function, known as the downtime loss function, is defined. A prediction model is then built based on a multi-step forecasting time series model. The prediction model is then used to forecast a window that minimizes downtime loss. The predictive maintenance module uses historical data to foresee when and how to implement the seamless upgrading at a proper time so that it could have minimum downtime loss on the customer.