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A FRAM-based Case Study on Leakage Accidents in Cathode Material Manufacturing Process

초록

영어

In this study, the interrelationships among accident prevention functions targeting leakage accidents in cathode material manufacturing process were analyzed using the FRAM (Functional Resonance Analysis Method) method. 17 system functions of accident prevention were derived from the target accidents. Each function was connected and developed into six aspects such as input, output, prerequisites, resources, control, and time. And, the causes of leakage accidents in complex interactions were analyzed in detail. Results showed that the complex interaction and ripple effects of functional variability were analyzed as the cause of the accident unlike the existing root cause analysis (RCA) that deals with simple cause-effect relationships. Specific response plans were derived, including systematic management of operation plans, continuous monitoring of facilities, and strengthening of worker training and information sharing mechanisms. The FRAM method confirmed that it can serve as an effective tool for accident prevention in considered new chemical processes. It is expected to be used as an important tool that can significantly reduce human casualties, property damage, and environmental accidents in the cathode active material manufacturing process.

목차

ABSTRACT
Introduction
Functional Resonance Analysis Method
Research Design
Research Materials
Research Method
Considered Leakage Accidents
Results of FRAM Analysis
System Function Derivation and Analysis
Characterization of Function and Identification of Functional Variability
Analysis of Functional Volatility Factors and Volatility Ripple Effects
Understanding Accident Occurrence and Cause
Response Measures to Prevent Recurrence of Accidents
Discussion
Conclusion
Acknowledgement
References

저자정보

  • Tae Hyoung Lim Department of Disaster Prevention Engineering, Chungbuk National University
  • Seung-Hyeon Shin Department of Big Data, Chungbuk National University
  • Jeong-Hun Won Department of Big Data, Chungbuk National University, Department of Safety Engineering, Chungbuk National University

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