In the paper a typical injection moulding process on a single-screw extrusion machine aimed to the production of axisymmetric polypropylene dishes for alimentary use has been investigated. First of all the most important process parameters have been individuated; subsequently a wide testing hyperspace has been investigated, at varying the process parameters in a large range. For each combination both some geometrical characteristics of the obtained component have been measured and the occurrence of defects has been verified. The largest part of the available data have been used to train a neural network aimed to explain the process dynamics. Furthermore an offline control system, based on fuzzy logic reasoning, has been developed. If a defect is detected the system is able to suggest the most effective adjustment of the process parameters in order to take the process back in control. The validity of the controller has been assessed through several experiments on the available equipment.

The use of artificial intelligence techniques to optimise and control injection moulding processes

Basile V;
1999

Abstract

In the paper a typical injection moulding process on a single-screw extrusion machine aimed to the production of axisymmetric polypropylene dishes for alimentary use has been investigated. First of all the most important process parameters have been individuated; subsequently a wide testing hyperspace has been investigated, at varying the process parameters in a large range. For each combination both some geometrical characteristics of the obtained component have been measured and the occurrence of defects has been verified. The largest part of the available data have been used to train a neural network aimed to explain the process dynamics. Furthermore an offline control system, based on fuzzy logic reasoning, has been developed. If a defect is detected the system is able to suggest the most effective adjustment of the process parameters in order to take the process back in control. The validity of the controller has been assessed through several experiments on the available equipment.
1999
Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato - STIIMA (ex ITIA)
3-211-83148-7
injection moulding
process optimisation
neural network
fuzzy logic
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/227591
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