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Dynamic Human Error Assessment in Emergency Using Fuzzy Bayesian CREAM.

Marzieh Abbasinia1, Omid Kalatpour1, Majid Motamedzadeh2

  • 1Center of Excellence for Occupational Health, Occupational Health and Safety Research Center, School of Public Health, Hamadan University of Medical Sciences, Hamadan, Iran.

Journal of Research in Health Sciences
|August 21, 2020
PubMed
Summary

This study developed a dynamic model for assessing human error in petrochemical emergencies. The model prioritizes scenarios and quantifies human error probabilities to improve safety management.

Keywords:
Emergency managementFuzzy Bayesian CREAMHuman error

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Area of Science:

  • Petrochemical Industry Safety
  • Risk Management
  • Human Factors Engineering

Background:

  • Human error is a primary cause of accidents in the petrochemical sector.
  • Critical situations exacerbate human error due to complex influencing factors.
  • Effective management of human error is crucial for preventing injuries and losses.

Purpose of the Study:

  • To develop a dynamic model for assessing human error during emergencies in the petrochemical industry.
  • To enhance the reliability and repeatability of human error assessment methods.
  • To provide a framework for managing human error in critical industrial situations.

Main Methods:

  • A cross-sectional study utilizing Fuzzy Bayesian networks and Fuzzy-AHP-TOPSIS.
  • Prioritization of emergency scenarios and assessment of human error for critical conditions.
  • Application of the Bayesian Cognitive Reliability and Error Analysis Method (CREAM) for probability determination.

Main Results:

  • A fire in a chemical storage unit was identified as the highest priority emergency scenario.
  • Seven Common Performance Conditions (CPCs) were established based on expert consensus.
  • Membership functions, fuzzy set parameters, CPC values for 8 tasks, and control mode probabilities were determined.

Conclusions:

  • The developed dynamic model overcomes limitations of traditional assessment methods.
  • It offers a repeatable and systematic approach to human error assessment in industrial emergencies.
  • The model facilitates improved management of human error, enhancing overall safety.