Intelligent Issue 01 | Page 39



for each aircraft based on historical flight data , OptiClimb allows the analysis of thousands of scenarios taking into account individual aircraft performance and accurate 4D weather forecasts to recommend optimal climb speeds to pilots for each flight .
Further to an OptiClimb trial involving more than 1,000 flights , AeroLogic has demonstrated average fuel savings of 234kg per climb , which could translate into a fleetwide carbon footprint reduction of at least 5,000 tons of CO 2 per year .
In addition to implementing OptiClimb , AeroLogic is working with Safety Line to explore further flight optimisation opportunities in all flight phases .
For instance , AeroLogic was the first cargo operator to successfully trial OptiDirect , a solution that recommends shortcuts to pilots based on historical tracks flown and forecasted weather on the route .
now easily access our smart technology through SITA FOR AIRCRAFT ’ s ‘ Digital Day of Operations ’ portfolio and work towards more sustainable aviation . We look forward to delivering further innovation through this collaboration to save fuel and improve costefficiency at every stage of flight .”
News of the partnership comes shortly after a summer announcement that AeroLogic , a joint venture between DHL Express and Lufthansa Cargo operating 777 freighters , had become the first cargo airline to implement OptiClimb .
According to AeroLogic ’ s Managing Director , Joe Moser : “ Within AeroLogic , sustainable operations is a priority for all . We are excited to innovate with OptiClimb , a unique solution that empowers our pilots to further contribute to more efficient and greener operations .”
Safety Line Founder and CEO , Pierre Jouniaux , added : “ We are proud to have AeroLogic as our first cargo airline customer . We look forward to working together towards even more flight efficiency .” �

Although the COVID-19 crisis has had less impact on cargo operations , it has further enhanced the general drive for more sustainability in aviation .
AeroLogic is more than ever committed to proactively save fuel and reduce CO 2 emissions . Climb-out is one of the most fuel-consuming phases of the flight , especially for AeroLogic ’ s fully loaded 777Fs . Thereby , it offers the most potential for savings , but it is also the most complex phase , with many parameters changing simultaneously as the aircraft ascends .
Machine Learning helps to address this complexity . By building performance models
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