Predictive Maintenance

Example Customer

Aerospace and Technology Corporation

Data Owner

Parts Manufacturers

Data Users

Airlines’ Predictive Maintenance Teams

Type of Data

Parts Specifications and Engineering Specs

Summary of Pain Point

The issues involved with predictive maintenance can be demonstrated using the airline example.

Airlines are complex partnerships of various manufacturers, each of which wants to protect IP.

Aircraft manufacturers need to predict the remaining useful life of their engines. 

Supply chains are a trade secret for parts suppliers, making predictive maintenance models less accurate.

Summary of TripleBlind’s Solution

With privacy enhancing computation, airlines can privately run predictive models on aircraft data to determine the remaining useful life of their aircrafts and parts — without ever having access to the raw data sets.

The manufacturer networks are able to share information from airlines they don’t have direct relationships with.

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TripleBlind’s innovations build on well understood principles of data protection. Our innovations radically improve the practical use of privacy preserving technologies, by adding true scalability and faster processing, with support for all data and algorithm types. We support all cloud platforms and unlock the intellectual property value of data, while preserving privacy and enforcing compliance with HIPAA and GDPR.