• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1997년도 봄 학술발표회 논문집
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• pp.27-34
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• 1997

In this paper, systematic and comprehensive approaches are suggested for the application of quantitative PRA techniques especially for those risk events that cannot be easily evaluated quantitatively In addition, dominant risk events are identified based on their occurrence frequency assessed by both actual survey of construction site conditions and the statistical data related with the probable accidents. Practical FTA(Fault Tree Analysis) and ETA(Event Tree Analysis) models are used for the assessment of the identified risks. When the risk events are lack of statistical data, appropriate Bayesian models incorporating engineering judgement and test results are also introduced in this paper. Moreover, a fuzzy probability technique is used for the quantitative risk assessment of those risk components which are difficult to evaluate quantitatively.

• 산업경영시스템학회지
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• 제35권4호
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• pp.194-201
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• 2012

Because the difference between products and services are getting less and less, service and manufacturing companies' efforts are increasingly focused on utilizing services to satisfy customers' needs under today's competitive market environment. The value of services depends on service reliability that is identified by satisfaction derived from the relationship between customer needs and service providers. In this paper, we extend concepts from the fault tree analysis for reliability analysis of tangible systems to services. We use an event-based process model to facilitate service design and represent the relationships between functions and failures in a service. The objective of this research is to propose a method for evaluating service reliability based on service processes using service blueprint and FTA. We can identify the failure mode of service in a service delivery process with a service blueprint. The fuzzy membership function is used to characterize the probability of failure based on linguistic terms. FTA is employed to estimate the reliability of service delivery processes with risk factors that are represented as potential failure causes. To demonstrate implementation of the proposed method, we use a case study involving a typical automotive service operation.