GTM-T7B9ZLF
Skip to main content
  1. Home >
  2. About Fujitsu >
  3. Resources >
  4. News >
  5. Press releases >
  6. 2019 >
  7. Fujitsu Wins First Prize for Predictive Maintenance in Airbus AI Challenge

Fujitsu Wins First Prize for Predictive Maintenance in Airbus AI Challenge

Fujitsu Europe

News facts:
  • ‘Airbus AI Gym’ challenge to find most accurate unsupervised predictive AI capability for helicopters awards first prize to Fujitsu
  • Winning solution achieved 93% precision; identifies when sensors are functioning unusually and shows early warnings for vehicle faults
Munich, December 11, 2019 – Fujitsu has been awarded first prize by leading global aerospace manufacturer Airbus SE in a worldwide competition to find the most accurate use of an unsupervised artificial intelligence (AI) system.

Top ranking in the Airbus AI Gym1 challenge for accurate sensor monitoring went to Fujitsu for developing a way of using unsupervised AI to detect anomalies in accelerometer data from Airbus pre-certification helicopters, ahead of 140 other teams participating in this helicopter challenge.

Flight engineers attach large numbers of sensors onto test helicopters to capture every nuance of behavior. To enhance detection of early-warning signals in this vast amount of data Airbus established its AI Gym challenge, fostering research into a new way of accurately locating potential issues, especially data outliers. A multi-disciplinary team of specialist engineers supports each flight to study this mass of observations – a major investment in every flight made. Because almost all sensor data is considered ‘normal’ this mechanism should be able work without prior guidance from engineers.

Fujitsu’s winning solution achieved 93% precision, leveraging its “DeepTAN” Unsupervised AI Model created by the company’s sub-division, Fujitsu Systems Europe2 (FSE). The solution took data sequences from multiple sensors and analyzed them across a fixed time period, detecting abnormal sensor behavior using a deep learning algorithm based on Multivariate Anomaly Detection with Generative Adversarial Networks3 [MAD-GAN]. FSE trained and validated the algorithm in its own data center using 1,677 one-minute-sequences of accelerometer data from test helicopters flying at various locations, angles and flights.

Fujitsu plans to industrialize its solution for unsupervised time-series analysis solution, complementing DeepTAN with end-to-end functionality, integrated data pipelines and further evolved algorithms.

New functions include a semi-supervised mechanism to classify the type of sensor anomaly, addressing the imperative for engineers and maintenance services to find the root cause of anomalies, and to interpret multi-variate data and correlations between all test flights in a program. The company will then be able to bring value to customers across the aircraft lifecycle, from test flight and pre-delivery, to airlines and Aviation MRO4 organisations.

Ian Godfrey, Director Solutions Business at FSE, says: “Winning first prize in this data challenge not only underlines Fujitsu’s world-leading AI expertise and technologies - it also provides concrete evidence of our ability to apply them to real-world business scenarios. The concepts we applied to this specific problem have shown us how these new deep learning techniques not only help manufacturers but the firms working to sustain aircraft in service as well.”

Notes to editors
1 Airbus is at the forefront in the development of AI technologies and solutions in the aerospace industry. Through its collaborative platform AI Gym, Airbus is providing large, clean data sets so that any start-up, company or institution can test and train their algorithms on real-life data. AI Gym represents a new way of co-innovating by demonstrating the benefits of open partnerships and collaborative relationships beyond the aerospace industry. For more information: https://aigym.airbus.com/
2Fujitsu Systems Europe (FSE) focuses on innovative solutions in the technical computing arena. FSE uses its legacy skills, based on many years of experience working as an HPC (high performance computing) solution provider, and applies them to new evolving areas such as deep learning, AI, HPDA (high performance data analytics) and Cloud computing.
3A Generative Adversarial Network (GAN) is a class of machine learning systems where two neural networks contest with each other using a training data set.
4Maintenance, Repair and Overhaul – Organizations providing services to the aviation industry for continuing aircraft operations.

Online resources

About Fujitsu

Fujitsu is the leading Japanese information and communication technology (ICT) company, offering a full range of technology products, solutions, and services. Approximately 132,000 Fujitsu people support customers in more than 100 countries. We use our experience and the power of ICT to shape the future of society with our customers. Fujitsu Limited (TSE: 6702) reported consolidated revenues of 4.0 trillion yen (US $36 billion) for the fiscal year ended March 31, 2019. For more information, please see www.fujitsu.com.

Public Relations

International Corporate Communications

E-mail: E-mail: public.relations@fujitsu.com


All other company or product names mentioned herein are trademarks or registered trademarks of their respective owners. Information provided in this press release is accurate at time of publication and is subject to change without advance notice.

Date: 11 December, 2019
City: Munich