ISBN-13: 9783639134759 / Angielski / Miękka / 2009 / 188 str.
Probabilistic Risk Analysis (PRA) is a methodology, initially introduced in the nuclear industry and enhanced over the past three decades to evaluate the risk associated with complex systems such as nuclear power plants, chemical process installations, space missions, and healthcare. Socio-Technical Risk Analysis extends PRA modeling frameworks to include the effects of human and organizational factors in a more systematic way. As a result of multi- disciplinary effort, this study proposes a set of principles for socio-technical risk analysis. A safety framework, called SoTeRiA, is developed as a unique theoretical foundation for integration of both social (safety culture and safety climate) and structural (safety practice) aspects with the technical system PRA models. In order to operationalize the SoTeRiA framework, this book introduces a hybrid approach that combines deterministic (e.g., System Dynamics) and probabilistic (e.g. Bayesian Belief Network) modeling techniques. An application of the hybrid technique is provided in the aviation safety domain, focusing on airline maintenance systems.
Probabilistic Risk Analysis (PRA) is a methodology, initially introduced in the nuclear industry and enhanced over the past three decades to evaluate the risk associated with complex systems such as nuclear power plants,chemical process installations, space missions, and healthcare. Socio-Technical Risk Analysis extends PRA modeling frameworks to include the effects of human and organizational factors in a more systematic way. As a result of multi-disciplinary effort, this study proposes a set of principles for socio-technical risk analysis. A safety framework, called SoTeRiA, is developed as a unique theoretical foundation for integration of both social (safety culture and safety climate) and structural (safety practice) aspects with the technical system PRA models. In order to operationalize the SoTeRiA framework, this book introduces a hybrid approach that combines deterministic (e.g., System Dynamics) and probabilistic (e.g. Bayesian Belief Network) modeling techniques. An application of the hybrid technique is provided in the aviation safety domain, focusing on airline maintenance systems.