Predictive maintenance with Bayesian deep learningNabergoj, David (Avtor) Štrumbelj, Erik (Mentor) predictive maintenanceremaining useful lifeBayesian deep learningmodel evaluationWe assess the usability of Bayesian deep learning methods for remaining useful life estimation. To compare Bayesian models to standard deep learning models, we propose a model evaluation method based on simulated device maintenance. We find that Bayesian models outperform their architecturally equivalent deep learning models on synthetic data as well as on two benchmark datasets. The proposed evaluation method is relevant for practical applications and research, as it directly estimates maintenance costs and allows for more easily interpretable model comparisons.20212021-11-12 08:20:14Magistrsko delo/naloga133124sl