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Content archived on 2024-04-19

Development of a on-line quality system using neural networks for recycled plastics production

Objective



Processes are difficult to control, when applying recycled material where the material properties are not as constant as for new materials. Producing parts out of recycled material economically a closed loop quality control is necessary with a cheap 100 % quality evaluation.
The objectives of this project are the increase of productivity, a reduction of costs for quality assurance and rejections, and the improvement of the application possibilities of recycled plastics by developing a system based on neural networks for on-line quality estimation. Cooperation is needed to solve the following problems :
a) Development of an adequate neural network topology.
b) Determination of recycled material characteristics to describe the quality- relevant material properties.
c) Determination of quality relevant process variables.
d) Exemplary demonstration with recycled plastic material.
e) Indication of the transferability of results to other processes. Finding a way to produce high quality ensured products out of recycled material is an urgent problem to keep the effort on recycling plastic alive. Up to now there is no system yet to predict product qualities in plastic production which works by self learning on-line during the running production and which executes the estimate based on raw material characteristics and simply measurable process variables.

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Call for proposal

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Coordinator

Ibos Qualitätssicherungssysteme GmbH
EU contribution
No data
Address
Jülicherstraße 336
52070 Aachen
Germany

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Total cost
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