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Prediction and control of injection molded part weight using machine learning – A literature review

Year: 2023

Type: article

Abstract: Injection molding is an important and widely used process for the production of thermoplastic parts. Internal and external perturbations, such as fluctuating material properties due to the increasing use of recyclates, make it necessary to rapidly and continuously adapt the process to changing conditions. To ensure consistently high product quality and to support machine operators, machine learning methods are increasingly used for process monitoring and control. This study provides an overview of current approaches in this field, focusing on part weight as a decisive quality criterion.

Source: Procedia CIRP

DOI: 10.1016/j.procir.2023.06.149

Authors: Jonas Krauß, Ilona Borchardt

Institution: Fraunhofer Institute for Manufacturing Engineering and Automation

Language: English

Topic: Injection Molding Process and Properties

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4384788150

FWCI: 1.178

Cites: 49

Cited by: 12

Related to: 10