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A fuzzy causal relational mapping and rough set-based model for context-specific human error rate estimation.

Suprakash Gupta1, Pramod Kumar2, Gunda Yuga Raju1

  • 1Department of Mining Engineering, Indian Institute of Technology (BHU), India.

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|February 19, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces a fuzzy rule-based approach to map work context to human error rates. This method helps predict human error and develop targeted safety interventions in high-risk systems.

Keywords:
context describing factorfuzzy relational mappinghuman error ratehuman reliability analysisrough setunderground coal mining

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Area of Science:

  • Human Factors Engineering
  • System Safety
  • Cognitive Psychology

Background:

  • Human error is a critical factor in high-risk system accidents.
  • Accurate assessment of human error rates is challenging but essential for safety.
  • Work context significantly influences human performance and error rates.

Purpose of the Study:

  • To develop a method for investigating human error rate variability based on work context.
  • To create a predictive model for human error rates in different operational environments.
  • To aid in identifying safety issues and designing countermeasures.

Main Methods:

  • Utilized a fuzzy rule-based causal relational mapping approach.
  • Mapped various work contexts to human error rates derived from accident data.
  • Developed a causal relational diagram for context-based error prediction.

Main Results:

  • Demonstrated a method to link specific work contexts to human error rates.
  • Created a causal relational diagram for predicting human error variability.
  • Provided a framework for understanding context-dependent human error.

Conclusions:

  • The fuzzy rule-based mapping approach effectively models human error rate variability.
  • The developed causal relational diagram can predict human error rates across different contexts.
  • This approach supports the identification of safety vulnerabilities and the development of targeted interventions.