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Data Analytics - Predictive Analytics

  • 08/26/2022
  • 8:30 AM - 10:00 AM
  • 1435 Cincinnati Street, Suite 300, Dayton, OH 45417

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Predictive Analytics

GE’s Fleet Support team provides 24/7 technical product support to assist airlines around the world with their GE aircraft engines. In addition to assisting with any engine issues, Fleet Support also uses data analysis to help prevent operational issues from happening in the first place. GE Aviation employees in Cincinnati and Shanghai perform around-the-clock engine performance data analysis, seeking to identify trends and abnormalities that could disrupt engines in the field. Once a potentially troublesome trend is spotted, they work with airline customers so that they can perform maintenance checks before any issues lead to unscheduled delays. In this presentation, Asko Soimakallio, senior product staff manager, will explain how GE Aviation approaches asset data management to support these critical efforts.

Facilitators: Asko Soimakallio, Master Data Management Lead for the Fleet Support Team AND Patrick Ketelaar, Principal Engineer, Remote Diagnostics, GE Aviation

Asko Soimakallio works in the GE Aviation Fleet Support team as a Senior Product Staff Manager responsible for customer & asset data and associated digital capabilities. He has worked in the aviation industry for 12 years, supporting airline and shop customers and GE process improvements across US and Europe. Data, analytics, and digital development have been key to how he has been able to drive support and business insights for customers and GE alike.


Patrick Ketelaar works in the GE Aviation Fleet Support team as a principal engineer responsible for remote monitoring and diagnostics. He has worked in the aviation industry for 22 years, starting as an airline propulsion engineer at Delta Airlines and customer support engineer at Boeing. At GE for the last eight years, Patrick’s focus has been in remote engine monitoring and diagnostics, driving fleet stability through early detection of engine conditions and using analytics to recommend maintenance actions to customers.


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