Flight safety assessment based on a modified human error risk quantification approach.

Area of Science:

• Aviation Safety
• Risk Management
• Human Factors Engineering

Background:

• Current aviation risk assessments prioritize hardware/software failures over human errors.
• Human errors represent a critical, yet often underestimated, risk in aviation systems.
• Lack of precise methods hinders effective assessment and mitigation of human error risks.

Purpose of the Study:

• To propose a novel method, Fuzzy Risk Assessment of Human Errors (FRAHE), for identifying and assessing human error risks in aviation.
• To develop a risk assessment model that integrates human error probability, impact, and consequences.
• To address uncertainty and imprecision in human error data using a fuzzy inference approach.

Main Methods:

• Development of the Fuzzy Risk Assessment of Human Errors (FRAHE) method.
• Application of fuzzy inference to handle uncertainty and scarce data in risk assessment.
• Creation of a risk assessment model linking input indicators (human error probability, impact, consequence) to output risk severity.

Main Results:

• The proposed FRAHE method effectively identifies critical human error types and determines their risk severity.
• The developed risk assessment model precisely describes the relationship between risk indicators and overall risk severity.
• A case study demonstrated the model's availability and reasonability in assessing approach tasks.

Conclusions:

• The FRAHE method provides valuable insights for reducing critical human errors in aviation.
• The risk-based modeling approach supports prospective analyses to prevent aviation incidents and accidents.
• This methodology enhances the comprehensiveness of aviation safety risk assessments by focusing on human factors.