Open Neural Networks Hardware Implementation for Defect Classification Systems


ONNI-ADC - 9266

Keywords defect classification systems, neural networks, steel industry


Start Date: To be announced / Duration: 36 months

[ contact / participants ]


Objectives

Real-time classification of visible defects on flat and moving materials is a critical issue in quality control and management in many process-oriented industries.

ONNI-ADC aims to develop an advanced defect classification system prototype which will be based on a neural network system approach and OMI technologies. The prototype will be tested in a real user manufacturing plant to validate the system performances and the results for the targeted markets.

The ONNI-ADC development process will consist of the identification of the needs and the requirements of potential users in Europe in sectors such as steel, aluminium and paper; the development of OMI neural network supercells; and the prototyping and testing of the final OMI-based defect classification system in a steel-making plant.

Further information about ONNI-ADC is available from the ONNI-ADC home page.


CONTACT POINT

Mr Quoc Tran Dinh
Sema Group
16, rue Barbès
F - 92426 Montrouge
tel: + 33 / 1-4092-4092
fax: + 33 / 1-4092-0954

Participants

SEMA GROUP - F - C
ILVA - I - P
ANSALDO RESEARCH INSTITUTE - I - P
CSM - I - A
UNIVERSITY OF GENOVA - I - A


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ONNI-ADC - 9266, December 1993


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html version of synopsis by Nick Cook