Keywords defect classification systems, neural networks, steel industry
Start Date: To be announced / Duration: 36 months
[ contact / participants ]
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.
Mr Quoc Tran Dinh
16, rue Barbès
F - 92426 Montrouge
tel: + 33 / 1-4092-4092
fax: + 33 / 1-4092-0954
SEMA GROUP - F - C
ILVA - I - P
ANSALDO RESEARCH INSTITUTE - I - P
CSM - I - A
UNIVERSITY OF GENOVA - I - A
ONNI-ADC - 9266, December 1993
please address enquiries to the ESPRIT Information Desk
html version of synopsis by Nick Cook