Remaining useful life predictions for turbofan engine degradation using semi-supervised deep architecture.

•State-of-the-art results on the C-MAPSS dataset.•Genetic algorithm effectively tunes hyper-parameters in deep architectures.•Unsupervised pre-training extracts degradation related features.•Semi-supervised learning improves the remaining useful life prediction accuracy.