ORACLE open world 2015 Laurent PELTIERS Jean-Marc WATTECANT. Big Data in Airbus Flight Test and Integration Center

Transcription

1 ORACLE open world 2015 Laurent PELTIERS Jean-Marc WATTECANT Big Data in Airbus Flight Test and Integration Center

2 Some figures about AIRBUS employees over mainly 4 countries (more than 1000 in the US) Revenues (2013) 42,000 million / EBIT 1,710 million 8121 aircrafts in service operated by more than 400 companies Largest civil aircraft: the double deck A aircrafts delivered in 2014

3 Flight & Integration test center : our place in A/C development A/C certified! MG3 MG4.1 MG4.2 MG5 MG6 MG7 MG9 MG11 MG13 Concept ~24 months Definition Integration Tests Data for Manufacturing Flight Tests Test Phase ~24 months Production Assembly line Ramp Up 6 Year Development lead time

4 Flight & Integration test center: our mission Design office & program domains Tests definition Aircraft certification Flight &Integration test center Tests preparation Tests reports Ground or flight tests Tests analysis

5 Evolution of data collected Parameters # x parameters 450 TB archived parameters 150 TB archived parameters 12,8 TB archived Data archived x parameters 8,5 TB archived AMPEX 28 tracks 8 GB SONY AIT 2/3 50/100 GB SCSI hard disk 300 GB SSD hard disk 700 GB

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7 Big data project: One year project

8 Big data project: the scope of the first step Acquire Organize Analyse Raw data Current tools compatibility Data triggering Machine learning No functional impact for the user Enhancements : Less overhead to get the data Full campaign on-line Decide Discovery tools

9 Main challenges? Big data appliance nosql database HADOOP cluster Up to 4 flights 2 times a day

10 Current status 4 aircrafts parameters / aircrafts 700h of flights 5 billions of events 15% of the disk capacity Big Data Appliance X4-2 6 nodes nosql 6 nodes HADOOP 50% of the NEO processing use the appliance Time saving for multiflights analysis

11 Next steps: processing Descriptive analysis: Complex event detection Wide correlation between parameters Predictive analysis: Sensor failure Anomalies database

12 Next steps: Vizualisation

13 AIRBUS Flight and Integration Test Centre : our data processing view Processing HMI Data mining tool Full campaign on-line Complex event detection Time correlation for diag Machine learning algo Results storage Flight Tests data lake

14 Big Data application : Improve «Data retrieval» Save flight hours Easy search will be generalized «search autopilot on & altitude > ft & Mn>0.8 & bank > 5 then and plot the vertical load factor» Opportunities to bridge with other database (configuration, logs, ) Compare versions in the frame of incremental development A320 :1988 Sharklet 2012 NEO 2015

15 Big Data application : Perform «Data re-use» Increase system design maturity use the data for design verification prior implementation in avionic software (robustness) Continuous detection of anomalies on the whole campaign Tuning and re-launch surveillance algorithms Patterns recognition out of the «usual» enveloppe

16 Big Data application : Accelerate «Test Analysis» Enhance the analysis through statistical tools Correlation analysis: eg : longitudinal oscillation A380 specific flight needed to understand the root cause No stimulation No stimulation stimulation Mn=0.85 Mn=0.85->0.8 Mn=0.85 «Self» learning and clustering capability

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