The SVETLANA project aimed to provide an advanced smart update of flight safety by:

• Deploying an automated and standardised flight data management cycle capable of routinely processing large amounts of data to allow operators to thorougly examine all flight data using advanced sophisticated algorithms;
• Proposing a common standard methodology for flight data analysis using singular points automation based on data from various systems and operators to be combined and processed by advanced algorithms. Analysis on a larger statistical footprint with data from various aircraft types or operators would become comparable and could be combined;
• Identifying, detecting and correcting potentially unsafe trends before they can manifest themselves in an incident, using self-learning adapted methodologies;
• Performing a study of potential parameters or assessment techniques that can help in predicting the condition or failure of hardware on the basis of current FDR data, and can reduce the amount of corrective maintenance and provide better insight for predictive maintenance cycles;
• Limiting the need for specialist involvement in the FDM cycle to the decision making process only;
• Providing insight into abnormal events in order to adjust training, maintenance and procedures to prevent recurrence;
• Establishing isolation criteria templates for well-known conditions and situations from large simulated datasets, allowing a broader and earlier identification of abnormal conditions;
• Validating and assessing the advanced FDM Methodology in a simulated/synthetic environment;
• Providing a common standardised solution that has acceptance in both the EU and the Russian Federation.