7 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…
Towards socio-techno-economic power systems with demand-side flexibility
Hanmin Cai, Federica Bellizio, Yi Guo +11
Harnessing the demand-side flexibility in building and mobility sectors can help to better integrate renewable energy into power systems and reduce global CO2 emissions. Enabling t…
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…
Integrating Physics-Based and Data-Driven Approaches for Probabilistic Building Energy Modeling
Leandro Von Krannichfeldt, Kristina Orehounig, Olga Fink
Building energy modeling is a key tool for optimizing the performance of building energy systems. Historically, a wide spectrum of methods has been explored -- ranging from convent…