Comparar métodos

	Análise Híbrida de Confiabilidade	Simulação de Monte Carlo
Área	Delineamento experimental	Tomada de decisão
Família	Process / pipeline	MCDM
Ano de origem	1990s–2000s (consolidated formulation ~2000–2006)	1949
Autor original	Xiaoping Du, Achintya Haldar, and others; synthesized across structural and mechanical engineering communities	Metropolis, N., Ulam, S.
Tipo	Quantitative reliability / uncertainty analysis method	Robustness wrapper — Monte Carlo uncertainty propagation
Fonte seminal	Du, X., Sudjianto, A., & Huang, B. (2006). Reliability-Based Design With the Mixture of Random and Interval Variables. Journal of Mechanical Design, 127(6), 1068–1076.	Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association
Outros nomes	HRA, hybrid uncertainty reliability, combined reliability analysis, probabilistic-possibilistic reliability analysis	—
Relacionados	4	0
Resumo	Hybrid Reliability Analysis (HRA) quantifies the probability that an engineering system will perform its intended function when uncertain inputs are of two fundamentally different kinds: aleatory uncertainties (natural randomness, modelled with probability distributions) and epistemic uncertainties (lack of knowledge, modelled with intervals or fuzzy sets). By treating both uncertainty types simultaneously rather than collapsing them into a single probabilistic framework, HRA produces more truthful reliability estimates in design, structural, and systems engineering problems.	MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.