Correlating nano-scale surface replication accuracy and cavity temperature in micro-injection moulding using in-line process control and high-speed thermal imaging

Federico Baruffi, Mert Gulcur, Matteo Calaon, Jean-Michel Romano, Pavel Penchev, Stefan Dimov, Ben Whiteside, Guido Tosello*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)
139 Downloads (Pure)

Abstract

Micro-injection moulding (μIM) stands out as preferable technology to enable the mass production of polymeric components with micro- and nano-structured surfaces. One of the major challenges of these processes is related to the quality assurance of the manufactured surfaces: the time needed to perform accurate 3D surface acquisitions is typically much longer than a single moulding cycle, thus making impossible to integrate in-line measurements in the process chain. In this work, the authors proposed a novel solution to this problem by defining a process monitoring strategy aiming at linking sensitive in-line monitored process variables with the replication quality. A nano-structured surface for antibacterial applications was manufactured on a metal insert by laser structuring and replicated using two different polymers, polyoxymethylene (POM) and polycarbonate (PC). The replication accuracy was determined using a laser scanning confocal microscope and its dependence on the variation of the main μIM parameters was studied using a Design of Experiments (DoE) experimental approach. During each process cycle, the temperature distribution of the polymer inside the cavity was measured using a high-speed infrared camera by means of a sapphire window mounted in the movable plate of the mould. The temperature measurements showed a high level of correlation with the replication performance of the μIM process, thus providing a fast and effective way to control the quality of the moulded surfaces in-line.
Original languageEnglish
Pages (from-to)367-381
Number of pages15
JournalJournal of Manufacturing Processes
Volume47
Early online date22 Oct 2019
DOIs
Publication statusPublished - Nov 2019

Bibliographical note

Funding Information:
This research work was undertaken in the context of MICROMAN project (“Process Fingerprint for Zero-defect Net-shape MICROMANufacturing”, http://www.microman.mek.dtu.dk/). MICROMAN is a European Training Network supported by Horizon 2020, the EU Framework Programme for Research and Innovation (Project ID: 674801). This research has also received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 766871 (HIMALAIA). The project H2020 ITN Laser4Fun (agreement No. 675063) is also acknowledged.

Funding Information:
This research work was undertaken in the context of MICROMAN project (“Process Fingerprint for Zero-defect Net-shape MICROMANufacturing”, http://www.microman.mek.dtu.dk/ ). MICROMAN is a European Training Network supported by Horizon 2020, the EU Framework Programme for Research and Innovation (Project ID: 674801). This research has also received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 766871 (HIMALAIA). The project H2020 ITN Laser4Fun (agreement No. 675063 ) is also acknowledged.

Publisher Copyright:
© 2019 The Society of Manufacturing Engineers

Keywords

  • micro-injection moulding
  • flow visualization
  • surface replication
  • in-line quality assurance

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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