6 papers
Towards Unified and Data-Efficient Prognostics and Health Management with Tabular Foundation Models
Raffael Theiler, Lev Telyatnikov, Leandro Von Krannichfeldt +1
Data-driven Prognostics and Health Management (PHM) uses time-varying condition-monitoring data to diagnose system states and estimate remaining useful life in engineered assets. T…
From paper to benchmark: agentic, framework-based reproduction of under-specified methods in machine health intelligence
Raffael Theiler, Ludovico Comito, David Leko +3
Industrial Prognostics and Health Management (PHM) provides a representative case study for a broader challenge in applied machine learning: translating published papers into execu…
Picid: A Modular Evaluation Infrastructure for Reproducible PHM Across Tasks and Domains
Lev Telyatnikov, Raffael Theiler, Leandro Von Krannichfeldt +1
Progress in Prognostics and Health Management (PHM) is hindered by the lack of standardized and reusable evaluation practices across tasks, datasets, and application domains. Repor…
From Physics to Machine Learning and Back: Part II - Learning and Observational Bias in PHM
Olga Fink, Ismail Nejjar, Vinay Sharma +13
Prognostics and Health Management ensures the reliability, safety, and efficiency of complex engineered systems by enabling fault detection, anticipating equipment failures, and op…
Heterogeneous Graph Neural Networks for Short-term State Forecasting in Power Systems across Domains and Time Scales: A Hydroelectric Power Plant Case Study
Raffael Theiler, Olga Fink
Accurate short-term state forecasting is essential for efficient and stable operation of modern power systems, especially in the context of increasing variability introduced by ren…
Integrating the Expected Future in Load Forecasts with Contextually Enhanced Transformer Models
Raffael Theiler, Leandro Von Krannichfeldt, Giovanni Sansavini +2
Accurate and reliable energy forecasting is essential for power grid operators who strive to minimize extreme forecasting errors that pose significant operational challenges and in…