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Contenido archivado el 2024-04-30

Digital imaging techniques for surface quality assessment in manufacturing industry

Objetivo


Project's actual outcome (actual status at mid term):
Prototype systems for the fixed camera system and the robot guided strain analysis system together with a prototype marking facility have been build and are in the stage of industrial testing. A database for aesthetic defects is has been set up and filled with data. A prototype of an aesthetic defects device has been build and integrated into the system. The DIGIMAN common user interface developed in this project allows easy monitoring and interpretation of the quality of the measured sheet metal parts.
Objectives and content
Sheet metal forming is one of the most efficient and most
economic production processes for mass production of
several components. However, sheet metal stamping of
complex components is also characterised by several
failure modes like wrinkling and puckering, cracking and
necking as well as surface defects. Avoiding rejects
requires quality control in the production line and the
evaluation of the collected data to control previous
process steps. The surface geometry measurement and
aesthetic defect detection of stamped parts in the
manufacturing process shall be performed with digital
image processing techniques combined with automated
strain analyses.
The main problems using these techniques are the large
dimensions of the formed parts combined with very small
features respectively errors. In addition the time
available for the quality control of each part is very
short within the scope of the mass production.
Therefore, the objective of the project is the
development of an automatic optical measuring system for
the assessment of sheet metal components in terms of
shape accuracy, strain and surface quality. To achieve
this goal, the system has to analyse the surface of the
component. Based on the optically measured geometric
parameters of the part the system will detect deviations
from the desired geometry, for instance due to puckers
and springback. The long-term objective of the project
is to develop a basis for a closed loop control of the
production process. Based on detected deviations from
the desired quality of sheet metal components the process
parameters can be optimised. This would lead to further
cost reduction and technological improvement.
The aim of the project is the development of a 3D surface
measurement and evaluation system for in-line control of
the sheet forming process. The research carried out will
combine optical 3D measurement techniques and sheet metal
forming technologies. Experiments will be carried out on
laboratory level and in an industrial production
environment. In order to obtain the expected benefits
for the end users the digital image processing know-how
and the sheet metal forming know-how have to be combined.
This offers an improvement in the economic efficiency by
increasing quality through in-line production monitoring.
The utilisation of acquired knowledge for further design
activities is another benefit for the end user.
Therefore, the power of system makers, end users and
university institutes coming from image processing,
production engineering and sheet metal forming will be
joined in this project to achieve a high degree of
synergy effects.
To achieve this goal, the consortium comprises of two
image processing companies (AICON, Metronor), a truck and
bus manufacturer (IVECO) and an automotive supplier for
steel parts (Eurostamp) as end-users, a research centre
of an automotive company (Fiat Research Centre) and two
university institutes (Universities of Rome and Hanover).

Ámbito científico (EuroSciVoc)

CORDIS clasifica los proyectos con EuroSciVoc, una taxonomía plurilingüe de ámbitos científicos, mediante un proceso semiautomático basado en técnicas de procesamiento del lenguaje natural. Véas: El vocabulario científico europeo..

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Coordinador

AICON 3D Systems GmbH
Aportación de la UE
Sin datos
Dirección
32,Cellerstrasse
38114 Braunschweig
Alemania

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Coste total

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Participantes (6)

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