Predictive diagnosis services for the automotive industry


Texa is an Italian SME involved in the design, production and sale of diagnostic instruments for cars, bikes, commercial and agricultural vehicles and marine engines. This case study aims to combine the huge quantity of data available from electronic diagnostic systems with an innovative service that could ‘genetically map’ a single vehicle (i.e. car, truck, bike, etc.).

The aim is to develop a service that can predict failures, mechanical problems or damage at the component level and to offer the manufacturer very detailed information on how to redesign better or upgrade spare-parts or the vehicle.

To do this an algorithm will be designed to convert raw data into accessible knowledge using cloud-based HPC. This case study is intended to stress-test the algorithm and develop a new cloud-based service to support Texa’s clients.

 



Project:

Partners:
Texa (IT)

Sector
Transport

Keywords
High-Perfomance Computing

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