A breakthrough research integrated human factors concepts into safety management system, and proved quantitatively the causality between human factors and safety

1. 1
A Human Factors-Based
Safety Management Model for
Aviation Maintenance Safety
Yu-Lin Hsiao, PhD
Department of Industrial and Systems Engineering

2. 2
How do we manage safety?
• The way we currently do
– Reactive way: Accident & Incident Investigation
– Proactive way
• Daily- or Periodic-Based: Audit, LOSA, FOQA
• Behavior-Oriented: ASAP, LOSA
• Event- or Consequence-Based: MEDA, Risk Matrix
• Each system has its own advantages, but
also probably goes its own and unique way

3. 3
How do we manage safety?
• If there is a integrated method to manage safety from
a macro-system viewpoint?
– According to the purpose and philosophy of the ICAO Safety
Management System (SMS) as well
• Can we integrate all these safety programs or
methods by using the same language?
– Based on the same common concepts
– Quantitative and Data-driven Method

4. 4
How do we manage safety?
• Furthermore, can we use these safety data to
evaluate the safety status and manage the risk?
– To assist upper-level management and decision-making
– For long-term and continued safety management
– But not just focus on single event analysis or case by case

5. 5
Answer: Human Factors (HF)
• It is the major cause of flight accidents
– Implicated in most accidents and incidents
• Most safety programs are related to
human factors in some way
• Connected with current risk and safety
management concepts
– To eliminate or mitigate specific human error

6. 6
Steps to establish the HF model
• 1. Data Transformation
– From Qualitative Documents
• audit, investigation, or voluntary reports
– To Quantitative Data
• Human Factors Rates
• Use the Human Factors Analysis and Classification
System – Maintenance Audit (HFACS-MA)
– Set up an internal review board
• To analyze data sourced from various systems
• Extract consensus results to calculate the quantitative
rates

7. 7

8. 8

9. 9
Human Factors Rates
• Each error type was accumulated for monthly period
• Multiply by the weights of severity degree
– Weights were developed by aviation authority
– Based on Analytic Hierarchy Process (AHP) method
• Human Factors Rate =
W : The highest weight of severity degree (W = 11, the designated weight of Finding )
wi : The weight of the severity degree, i={I, R, C, F}
n : The sum of the human failures with all severity degree per month
ni : The sum of the human failures with specific severity degree, i={I, R, C, F}
( )
nW
nw
i
ii
∗
∗∑

10. 10
Future Incident Rate
Incident Rate =
Incident : The number of incidents per month
Departure: The number of flight departure per month
000,1×
∑
Departure
Incident
Airline Departure
Times
Accident Incident Accident
Rate
Incident
Rate
A 81,448 1 73 0.012 0.90
B 134,814 2 192 0.015 1.42

11. 11
Steps to establish the HF model
• 2. Develop the mathematical model
– Use Neural Network method
– Verify the prediction performance of the model
• 3. Start using the model to evaluate safety
status
– Output: Future Incident Rate
– Different company might have different prediction
performance or time range (month or quarter)

12. 12
Steps to establish the HF model
• 4. Detect the uprising trend of future incident
rate
– Self- or Expert-decided warning threshold
• 5. Find out the root causes and the original
data sources
– Based on real and reliable data collected by different
safety systems or programs
– To support the corresponding safety management
activities

13. 13
• Current Achievement:
– Succeed in the prediction of future incident rate using
human factors analysis
– Based on real safety audit data from aviation authority
(data-driven & practical)
– Prove the causality of human error and safety
– General Accuracy
• Correlation Coefficient: 0.6 ~ 0.75
• R2
: 0.35 ~ 0.58
HF-Based Safety Management Model

14. 14
Prediction Result
0
2
4
6
8
10
Months
IncidentRates
Actual Simulate
Airline A
Airline B
60
0
1
2
3
4
5
Month
IncidentRates
Actual Simulate

15. 15
• Advantages
– Can integrate various data sources from different safety
programs using the same standard
• Human Factors concept
• As an integrated part of SMS
– Can become a safety management tool to detect risk
associated with uprising incident rate from a systematic
perspective
• Find out the root causes related to incident rate
• Conduct corresponding management activities to
control the risk
HF-Based Safety Management Model

16. 16
HF-Based Safety Management Model
• Improvement to safety management system
– Help manager’s decision making regarding the safety
management priority
– Integrate and utilize various safety data to improve
safety management in a quantitative way
– Focus on both active and latent human factors such as
safety climate which could affect the safety performance
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