Safety, reliability, and maintenance of hydrogen-based equipment, including Risk-Based Maintenance (RBM), have recently gained increasing attention, as hydrogen, while key to decarbonizing hard-to-abate sectors, raises safety concerns. However, two literature gaps limit the development of risk-based strategies for hydrogen technologies. First, existing RBM methodologies do not account for hydrogen-specific components, such as electrolyzers, which differ from conventional equipment. Second, available studies on electrolyzer reliability remain largely qualitative or laboratory-scale. This study addresses these gaps by proposing an adapted RBM methodology tailored to hydrogen-fueled manufacturing facilities. Integrating qualitative tools (e.g., FMEA) with probabilistic models (e.g., Bayesian Networks) enables comprehensive hazardous scenarios identification and likelihood estimation. A conceptual layout of a glass furnace supplied by a 3 MW PEM electrolyzer is considered as a case study to demonstrate the feasibility of the adapted RBM framework in identifying high-risk components and enabling maintenance prioritization, potentially improving plant safety. • An adapted Risk-Based Maintenance approach for hydrogen application is proposed. • Hazardous scenarios for an industrial electrolyzer are systematically identified. • The probability and impact of forming an explosive H2–O2 mixture are evaluated. • Mapping failure scenarios into a Bayesian Network improves framework flexibility. • The approach enables risk prioritization in H2-fueled glass manufacturing.
Collina et al. (Tue,) studied this question.