A Method for Determining the Flow Front Position and Velocity of a Polymer Melt in an Injection Moulding Process

Mensler, Holger (2021) A Method for Determining the Flow Front Position and Velocity of a Polymer Melt in an Injection Moulding Process. PhD thesis, University of Gloucestershire. doi:10.46289/PO17BF22

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During the filling phase of an injection moulding process, the flow front velocity of the plastic melt decisively influences the form part quality. It has been believed that a constant flow front velocity of the melt leads to form parts that are free of distortion and residual stress. A process control strategy based on a constant flow front velocity of the melt, however, requires the full understanding of the flow front position as a function of the screw position of the injection moulding machine. With current methods, this can only be achieved by direct measurements using a number of sensors inside the mould, which leads to a complicated structure, great effort, and a high cost for tooling equipment. This study proposes, designs, and develops an innovative method for determining the flow front velocity of a plastic melt in an injection moulding machine using only one pressure sensor at the front of the screw, which is based on the idea of mapping a simulated filling process to a real injection moulding process. The mapping ensures that the characteristic event points are identified and matched for both the simulated and real filling processes. The results of the simulation analysis and experimental evaluation demonstrate that the proposed method is effective for determining the flow front position and resulting flow front velocity of the melt on the entire flow path. No specific measuring devices (sensors) were used within the mould cavity to locate the melt front position during the filling phase in any of the experimental studies. Only one single pressure sensor, located outside the mould, was required to determine the flow front velocity of the melt. The two case studies have provided the necessary evidence that the new method offers great potential for rule-based setting of the injection moulding machine and advanced process control strategies based on machine-independent parameters, such as constant melt front velocity or constant melt viscosity during the filling phase. With the new method, it is conceivable that transferring a single form part-specific event pattern (determined at the time of part development), in combination with its filling pattern, to the proposed process parameter determination unit assigned to the mould is possible. With its methods and functions for determining the real and form part-specific event patterns and for matching these patterns, the flow front position of the melt can be reliably determined from shot to shot. The results from the analysis and evaluation for pattern matching show that a comparatively simple matching algorithm with linear transformation would be sufficient for this purpose. Depending on the amount of available data and the complexity of the control unit, machine-independent parameters can be determined in real time on the entire flow path and used to closed-loop control the machine setup. Because the method dispenses with any sensor technology within the mould, it can be used for any existing application without complex and expensive retrofits of existing moulds. With the obtained parameters, the new method could be an essential component in the search for advanced process control strategies and thus for autonomous injection moulding.

Item Type: Thesis (PhD)
Thesis Advisors:
Thesis AdvisorEmailURL
Zhang, Shujunszhang@glos.ac.ukhttps://www.glos.ac.uk/staff/profile/shujun-zhang/
Uncontrolled Keywords: Injection moulding process; Flow front velocity; Quality improvement; Quality control; Rule-based algorithm; Injection moulding machine settings
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD2321 Industry
Divisions: Schools and Research Institutes > School of Business, Computing and Social Sciences
Research Priority Areas: Applied Business & Technology
Depositing User: Susan Turner
Date Deposited: 11 Jul 2022 08:50
Last Modified: 01 Sep 2023 12:36
URI: https://eprints.glos.ac.uk/id/eprint/11303

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