“Skywise”airline ‘early adopter’ highlights
Paris Air Show (Le Bourget)
Tuesday 20th June 2017
Operator case studies, in alphabetical order:
AirAsia uses Skywise open data platform for large-scale fleet analyses
Airbus and AirAsia teams have been working closely in direct collaboration with users in Reliability, Safety, and Operations. Together they have deployed the Skywise data platform, integrated data from across disparate sources, and developed new capabilities against AirAsia's specific and immediate needs, including time series analysis of large-scale DataBird sensor data, component reliability, and repetitive fault analysis.Key results include: The deployment of the data platform and integrated several years’ worth of AMOS data across all AOCs as well as PFRs; The deployment of component reliability, ‘rogue component’, and repetitive-fault applications which will allow reliability and maintenance teams to perform analyses at scale to improve the reliability of the fleet; Continuous training on ‘Quiver’ – a Skywise application which allows users to visualise and analyse large-scale sensor data to perform flight-ops analysis, predictive maintenance, and troubleshooting.
easyJet deploys Airbus Skywise platform for fleet Predictive Maintenance
Airbus and easyJet have deployed the new Skywise data platform to enable a fleet-wide predictive maintenance capability. This capability has successfully prevented technical delays normally caused removals of aircraft components including integrated drive generators (IDGs), high pressure valves (HPVs) and radio altimeters. By working closely together with easyJet, the Airbus design office and the airline were able to address easyJet’s ‘top-100 operational issues’. This work has resulted in the building and deployment of a fully customized application which allows actionable items to be performed preventing unnecessary delays for customers. In addition, easyJet is accessing the underlying platform directly to measure the effectiveness of maintenance actions and conduct fleet-wide analysis on aircraft technical and maintenance data.
Emirates uses Skywise for Real-Time Health Monitoring and predictive maintenance
Emirates is collaborating with Airbus to reduce operational disruptions by sharing data on the new Skywise open data platform. The airline is benefitting from the Airbus Real-Time Health Monitoring, providing predictive maintenance and enhanced diagnostic to improve its fleet performance, optimize its operations, and make quicker and more informed decisions. Moreover, in case of unexpected technical issues arising, this Airbus predictive and monitoring capacity allows prompt mitigation solutions while final fixes are being implemented. So far, the Airbus Real-Time Health Monitoring and predictive maintenance has demonstrated a significant gain in operational reliability of around one percent for Emirates’ fleet.
Peach uses Skywise data platform to automate quality monitoring, and interactively visualise flight paths
Airbus and Peach have deployed Airbus’ Skywise open data platform. This allows data to be integrated from across the airline’s disparate sources and enables various capabilities required by the airline including quality reliability reporting, component reliability and safety analysis. In particular, the platform enables Peach to automate the quality monitoring process and produce key metrics grouped by ATA chapter and aircraft in seconds. Reports which used to take days are now produced in only a few clicks. For component reliability, another application uses data from the platform to track unscheduled removals over time, run “Weibull” distributions over the data, and determine the optimal replacement schedule. Another benefit to Peach from the platform is the capability to interactively visualise flight paths using a special application called “Flight Path 360” This can drill-down on select parts of a flight based on key sensor data measurement.
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Contact for the Media:
Martin FENDT
Mobile:+33 617 720 581
email:
Airbus Press Office1, Rond-point Maurice Bellonte
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