Usage-Specific Survival Modeling Based on Operational Data and Neural Networks

arXiv:2403.18739v1 Announce Type: new
Abstract: Accurate predictions of when a component will fail are crucial when planning maintenance, and by modeling the distribution of these failure times, survival models have shown to be particularly useful in this context. The presented methodology is based on conventional neural network-based survival models that are trained using data that is continuously gathered and stored at specific times, called snapshots. An important property of this type of training data is that it can contain more …

abstract arxiv context cs.lg cs.sy data distribution eess.sy failure maintenance methodology modeling network networks neural network neural networks planning predictions stat.ml survival type usage will