**Appendix D**

**Table A4.** Surveys—Subject Matter Experts.

### **Regulatory Authority Subject Matter Expert Questionnaire**

Dear Participant,

This study is about identifying and understanding the contributory factors to aircraft maintenance related accidents and incidents in Nigeria. All relevant information regarding the methods used would be made available to you. This survey has been prepared for Aviation Safety Inspectors (ASI) at the Safety Deficiency Incidents Analysis (SDIA) unit of the Nigerian Civil Aviation Authority (NCAA). A total of five open ended questions would be presented to you and your responses/ideas would be highly beneficial to this study.

Q1 What taxonomy do you use in analysing occurrence data? Does this taxonomy support coding of maintenance error or maintenance related occurrences? What other taxonomy/taxonomies would you prefer to use? Please describe your experience and process of analysing the mandatory occurrence reports

Q2 With respect to the data output of this research, please evaluate and discuss your opinion of the methodology used and the output. What could have been done better?

Q3 Please discuss other methods that can be used to identify and prioritise aircraft maintenance related high risk areas. Do you think developing customised taxonomies for maintenance related events would help identify high risk areas in Nigeria?

Q4 In order to further predict incidents, make adequate plans (such as new rule making, safety promotion, training, workshops, increase/targeted oversight etc.) using the results of this data analysis, what methods can you recommend for aviation regulatory authorities and all relevant stakeholders?

Q5 Please discuss the main challenges in terms of data integrity or quality. Is there su fficient detail and information available within the MORs submitted/dataset to determine human factors related causal and contributory factors?

Q2 As an air Accident Investigator with the Accident Investigation Bureau, are you satisfied with the depth of human factors included in your training? Do you have a separate department which focuses on Human Factors related issues such as human factors in aircraft maintenance?

Q3 With respect to the data outputs of this research, please evaluate and discuss your opinion of the methodology used and the output. What could have been done better?

### **Accident Investigation Bureau Subject Matter Expert Questionnaire**

Dear Participant,

The aim of this study is to explore the contributory factors to aircraft maintenance-related accidents and incidents in Nigeria in order to achieve a deeper understanding to this safety critical aspect of the aviation industry.

To achieve this aim, one of the objectives was to qualitatively analyse the accident investigation reports published by the Accident Investigation Bureau in the last 10 years. This was achieved by using Insley's (2018) Maintenance Factors Analysis and Classification System (MxFACS) taxonomy to code the data.

The results of the analysis showed that the aircraft maintenance-related accidents were attributed to the following contributory factors.


This questionnaire is designed for Air Safety Investigators of the Accident Investigation Bureau (Nigeria). A total of three open ended questions would be presented to you and your responses/ideas would be highly beneficial to this study.

Q1 Does the Accident Investigation Bureau carry out long-term (e.g., last 10 years) reviews of previous accident trends? Do you think that such reviews (e.g., the one carried out in this study focusing on airworthiness and maintenance) may help to identify and prioritise high risk areas and plan mitigation actions such as targeted oversight, rulemaking or safety promotion?

Q2 As an air Accident Investigator with the Accident Investigation Bureau, are you satisfied with the depth of human factors included in your training?

Do you have a separate department which focuses on Human Factors related issues such as human factors in aircraft maintenance?

Q3 With respect to the data outputs of this research, please evaluate and discuss your opinion of the methodology used and the output. What could have been done better?
