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    KCI등재 SCOPUS

    DSC 기반 철도위험 관리를 위한 FRAM 모델을 활용한 철도운행 안전 최적 대안 선정 방안 연구 = A Study on Optimal Railway Operation Safety Alternatives Selection Using the FRAM Model for DSC-Based Risk Management

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    https://www.riss.kr/link?id=A109353562

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    Railway accidents can lead to significant human casualties and economic losses, emphasizing the continuous importance of safety management. To ensure the safe operation of railway systems, it is essential to predict risks, monitor and manage key safety indicators in real-time, and implement appropriate maintenance measures as needed. Recently, various digitalized solutions have been developed to address these challenges, and ongoing research continues to explore more advanced and effective technologies and methods. This study proposes a method for identifying key monitoring factors for optimal system safety in railway operations using the Functional Resonance Analysis Method (FRAM) model. To establish a Digital Safety Chain (DSC)-based risk assessment framework, existing Event Sequence Diagram (ESD) scenarios were analyzed to identify target functions and related hazards. The FRAM model was then employed to determine the optimal contributing factors, and the effectiveness of the proposed optimal railway operation safety alternatives was validated through simulation
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    Railway accidents can lead to significant human casualties and economic losses, emphasizing the continuous importance of safety management. To ensure the safe operation of railway systems, it is essential to predict risks, monitor and manage key safet...

    Railway accidents can lead to significant human casualties and economic losses, emphasizing the continuous importance of safety management. To ensure the safe operation of railway systems, it is essential to predict risks, monitor and manage key safety indicators in real-time, and implement appropriate maintenance measures as needed. Recently, various digitalized solutions have been developed to address these challenges, and ongoing research continues to explore more advanced and effective technologies and methods. This study proposes a method for identifying key monitoring factors for optimal system safety in railway operations using the Functional Resonance Analysis Method (FRAM) model. To establish a Digital Safety Chain (DSC)-based risk assessment framework, existing Event Sequence Diagram (ESD) scenarios were analyzed to identify target functions and related hazards. The FRAM model was then employed to determine the optimal contributing factors, and the effectiveness of the proposed optimal railway operation safety alternatives was validated through simulation

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    참고문헌 (Reference)

    1 R. Clay-Williams, "Where the rubber meets the road : Using FRAM to align work-as-imagined with work-as-done when implementing clinical guidelines" 10 (10): 18-, 2015

    2 E. Hollnagel, "Understanding accidents-From root causes to performance variability" 1-6, 2002

    3 S. Dekker, "Safety differently: Human factors for a new era" CRC Press 2014

    4 R. Woltjer, "Resilience Assessment Based on Models of Functional Resonance" 2008

    5 J. Hale, A. R., "Management and culture : the third age of safety. A review of approaches to organizational aspects of safety" 129-165, 1998

    6 G. E. Apostolakis, "How useful is quantitative risk assessment?" 24 (24): 515-520, 2004

    7 R. Patriarca, "Framing the FRAM : A literature review on the functional resonance analysis method" 129 : 104827-, 2020

    8 H. Hollnagel, "FRAM : the Functional Resonance Analysis Method" Ashgate 2012

    9 R. Patriarca, "Defining the functional resonance analysis space : Combining Abstraction Hierarchy and FRAM" 165 : 34-46, 2017

    10 이동훈 ; 탁세현 ; 김상암 ; 여화수, "A Conceptual Study of a Framework for Real-Time Railway Safety Monitoring and Control System Based on Safety Performance Monitoring Indicators" 19 (19): 526-538, 2016

    1 R. Clay-Williams, "Where the rubber meets the road : Using FRAM to align work-as-imagined with work-as-done when implementing clinical guidelines" 10 (10): 18-, 2015

    2 E. Hollnagel, "Understanding accidents-From root causes to performance variability" 1-6, 2002

    3 S. Dekker, "Safety differently: Human factors for a new era" CRC Press 2014

    4 R. Woltjer, "Resilience Assessment Based on Models of Functional Resonance" 2008

    5 J. Hale, A. R., "Management and culture : the third age of safety. A review of approaches to organizational aspects of safety" 129-165, 1998

    6 G. E. Apostolakis, "How useful is quantitative risk assessment?" 24 (24): 515-520, 2004

    7 R. Patriarca, "Framing the FRAM : A literature review on the functional resonance analysis method" 129 : 104827-, 2020

    8 H. Hollnagel, "FRAM : the Functional Resonance Analysis Method" Ashgate 2012

    9 R. Patriarca, "Defining the functional resonance analysis space : Combining Abstraction Hierarchy and FRAM" 165 : 34-46, 2017

    10 이동훈 ; 탁세현 ; 김상암 ; 여화수, "A Conceptual Study of a Framework for Real-Time Railway Safety Monitoring and Control System Based on Safety Performance Monitoring Indicators" 19 (19): 526-538, 2016

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