Deep Learning for Engineering Inspection
Lead Participant:
BLOC DIGITAL LTD
Abstract
This project will create the **Deep Learning for Engineering Inspection** (**DL4EI)** application, simplifying inspections and creation of HGV 3D digital twins at vehicle and fleet levels to transform the ability to extract critical insight from the data.
**DL4EI** will:
* enable mobile device users to easily gather accurate Inspection data and apply deep learning to create accurate digital twins of each vehicle.
* convert data into insights, enabling optimised vehicle maintenance programs to be developed, saving up to 20% on the unscheduled repair program for a haulier.
* enable organisations to anticipate and avoid the impact of degradation thus reducing operational disruption through improved inspection planning and scheduling repair within existing service schedules.
**DL4EI** will:
* enable mobile device users to easily gather accurate Inspection data and apply deep learning to create accurate digital twins of each vehicle.
* convert data into insights, enabling optimised vehicle maintenance programs to be developed, saving up to 20% on the unscheduled repair program for a haulier.
* enable organisations to anticipate and avoid the impact of degradation thus reducing operational disruption through improved inspection planning and scheduling repair within existing service schedules.
Lead Participant | Project Cost | Grant Offer |
---|---|---|
BLOC DIGITAL LTD | £33,974 | £ 33,974 |
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Participant |
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INNOVATE UK | ||
UNIVERSITY OF DERBY | £15,965 | £ 15,965 |
People |
ORCID iD |
Frank McQuade (Project Manager) |