A fault tree-based approach for aviation risk analysis considering mental workload overload

Haiyang Che,Yueheng Song,Shengkui Zeng,Jianbin Guo,Qidong You

doi:10.17531/ein.2021.4.7

Abstract

Many lives and aircrafts have been lost due to human errors associated with mental workload overload (MWLOL). Human errors are successfully considered in existing Fault Tree Analysis (FTA) methods. However, MWLOL is considered through Performance Shaping Factors indirectly and its information is hidden in FT construction, which is not conducive to analyze the root causes of human errors and risks. To overcome this difficulty, we develop a risk analysis method where Multiple Resources Model (MRM) is incorporated into FTA methods. MRM analyzes mental workload by estimating the resources used during performing concurrent tasks, probably including abnormal situation handling tasks introduced by basic events in FT. Such basic events may cause MWLOL and then trigger corresponding human error events. A MWLOL gate is proposed to describe MWLOL explicitly and add these new relationships to traditional FT. This new method extends previous FTA methods and provides a more in-depth risk analysis. An accident, a helicopter crash in Maryland, is analyzed by the proposed method.

Highlights

Human errors (HEs), defined as that a human diverges from a normative plan or task [12], are regularly cited as the main causes of the majority of accidents in complex systems [3, 12, 25, 31]
To analyze the way MWLOL leads to accidents, the proposed methods are complemented with the utilization of fault tree analysis (FTA) and a new logic gate i.e. MWLOL gate
Based on the minimal cut sets (MCS) above and the probabilities of basic events shown in Table 4, the probability of top event can be calculated by quantitative methods of traditional FT

Summary

Introduction

Human errors (HEs), defined as that a human diverges from a normative plan or task [12], are regularly cited as the main causes of the majority of accidents in complex systems [3, 12, 25, 31] Their pivotal role in aviation accident occurrence has been quantitatively pointed out in many studies: roughly 70% of all accidents in commercial aviation and 80% in general aviation [30]; more than 80% of helicopter accidents [4]. MRM can well interpret the occurrence of MWLOL and decrement of human performance caused by the interference between several concurrent tasks [40]. It has been widely used in workload prediction and assessment in aviation (e.g., commercial aviation [2] and helicopter [8, 19])

Methods

Results

Conclusion