Design and implementation of an Air Traffic Control safety console for information analysis and integration of operational and safety performance data.
The objective of this project was to develop a safety method that considers systemic and dynamic aspects of safety as part of an integrated safety management system. Risks emerge gradually from the interaction of stakeholders, but unfortunately nobody has the full picture to understand them. A technology is required to capture the ‘risk patterns’ that emerge from this interaction between stakeholders. To achieve a total optimisation of the system, the safety concept must address the trade-offs between safety and productivity. Because a lot of existing safety knowledge is captured in bow ties and barrier analysis, the safety concept must properly interface with bow ties together with risk patterns and data mining techniques.
The following implementation is based on the following Corballis solutions
Safety management systems
Our solutions are based on extensive experience and research within the aviation sector, the aircraft maintenance sector in particular including extensive and on-going participation in regulatory and industry-wide forums and workgroups.
Risk and change management
Our innovative aviation risk and change management solutions support industry requirements and recommendations in a flexible manner designed to meet your specific organisational needs and approaches.
Open development platform
Out-of-the-box software modules that can ensure your money is spent on features making real business impact. Achieve significant savings by utilising our free and comprehensive Corballis Development Platform.
This project demonstrated how data science principles and use of risk intelligence can be applied to the design of an integrated safety information system. Our innovative approach to data collection techniques allowed the ATC operators to seamlessly integrate safety data (incidents/hazards/barriers) with operational information (weather, flight data, controller rosters) to calculate the complexity metric that defines thresholds of controller performance on day to day operations.