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overview

The Auxiliary Power Unit (APU) engine is an essential part of an aircraft. When the main engines stop working, the APU intervenes to supply the aircraft with electricity and pressure. It is therefore essential that it is always in an extremely good condition and that possible defects are detected early. 

Challenge 
How can we transform the data streams coming from the APU engine in a way and use them to detect defects early.

Solution

Predictive maintenance for aircraft engines

Hemisphere has developed a deep learning model for EPCOR that looks 280 flights ahead to detect errors. The model had an accuracy of 80% for certain types of defects. Resolving the defect early gives EPCOR a cost saving of 60%.
I was really impressed with the way Hemisphere handled everything. From the first call to everything in between they were very helpful and knowledgeable
Niels van Hofwegen - Program Manager bij EPCOR (Air France-KLM)
Niels van Hofwegen - Program Manager bij EPCOR (Air France-KLM)
Data

Data

APU sensor flight reports from thousands of flights from 80 unique aircraft
Technology

Technology

Keras DNN LSTM
Scope

Scope

Prototype, Test and Implementation
Planning

Planning

Realized in 5 months

Contact

Interested to know more about our services?

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Thomas Schijf
Founder Hemisphere

info@hemisphere.ai
+31 (0)6 140 31 885

Visiting address: 
Jaarbeursplein 6
3521AL Utrecht
The Netherlands

Level 4

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AI is never a standalone solution. It requires a lot of fine-tuning and creating the right conditions to successfully land a Machine Learning model in an organization. Hemisphere knows what it takes to take these models to the next level. 

There are dozens of reasons why a model does not make it to implementation. Quality of (input) data, availability & costs of sufficient computing power and management are all well-known examples.

Hemisphere works with you to see what is needed to get more out of your AI solution. You can contact us from cleaning data and setting up HPC instances to offering customized Machine Learning SLAs.

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A costly hick-up in your process and do you have the feeling that only an AI solution can answer this? 

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As a result, in most cases up to 80% of the final solution can be achieved in a design sprint of 2 weeks.

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The shift to cloud services offers organizations the opportunity to simplify their data processing. Companies that currently rely on batch processing can now implement continuous processing methods without disrupting their current processes. Rather than expensive rip-and-replace, the implementation can be incremental and evolutionary. 

By following the Extract-Transform-Load (ETL) methodology, data is processed and passed on in a qualitative and safe manner. This reduces the chance of errors in the data and provides the management team with the right data to base their decisions on.

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Hemisphere helps you make analyzes to understand the different trends and opportunities at the micro level. By responding to this, you exceed customer expectations and gain trust.