Document Details

Document Type : Thesis 
Document Title :
DEVELOPING FLIGHT DATA ANALYSIS AND RISK ASSESSMENT MODEL INTO ENHANCED FLIGHT SAFETY
تطوير نموذج تحليل بيانات الرحلات وتقييم الـمخاطر لتحسين سلامة الطيران
 
Subject : Faculty of Engineering 
Document Language : Arabic 
Abstract : FDM is a proactive method to capture system performance as it happens in real-time, during normal operations to identify potential flight hazards through the utilization of QARs which record data that will be utilized later for analysis purposes only. Data is the fuel of a SMS. Yet, collecting, storing and analyzing this data remains a challenge for shifting from the re-active mode after the accident/incident occur into pro-active prevention; and then predictive in the near future in order to reduce physical damage to equipment and human losses. Using such data helps in identifying operational risks in order to be eliminated, reduced and provided to training department. It aids in complying to regulations, and finally identifying technical issues for maintenance. Data are collected through QARs installed in the aircraft, then validated by FDM specialists to be further analyzed using KNIME Analytics software. The potential hazards will be analyzed by a risk assessment technique: FMEA which is a widely-used engineering technique for identifying and eliminating/reducing potential hazards. Outcomes are discussed in five phases: Events (identification of operational risks; occurrences and percentages for stations, aircrafts and months). Flights (complying to regulations by computing the percentage of flights captured compared to the actual flights). Replays (number of aircrafts transmitting wirelessly or manually). Risk Analysis (FMEA technique) and Risk Assessment (risk matrix that uses the severity and probability to end up with the risk classification). Operational risks were identified for (aircrafts, stations and months). Percentage of flights captured compared to the actual along with the number of aircrafts transmitting wirelessly is increasing in which it’s expected to meet the regulations successfully in the first quarter of 2016. Using FMEA technique, several events were resolved or properly identified to get a better or improved solution. 
Supervisor : Dr. Mohamed Zytoon 
Thesis Type : Master Thesis 
Publishing Year : 1439 AH
2018 AD 
Co-Supervisor : Dr. Hisham Alidrisi 
Added Date : Thursday, February 1, 2018 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
يزيد حسن ناجيNaji, Yazeed HassanResearcherMaster 

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 43044.pdf pdf 

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