Functionality characterization of injection moulded micro-structured surfaces

Francesco Regi, Mads Doest, Dario Loaldi, Dongya Li, Jeppe Revall Frisvad, Guido Tosello, Yang Zhang*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Micro-structured surfaces are increasingly being used on parts and products to embed functional properties that could be optical, electrical, thermal, or likewise. In this work, directional optical properties were achieved on plastic with a microstructure composed of a close array of ridges, defined by a constant width and by the angle with respect to the normal of the generative surface. Under constrained lighting, the reflectance was maximized from a certain viewing angle and direction, and minimized from its horizontally orthogonal position. The purpose was the generation of quick response codes that could be easily scanned by means of commercially available software, e.g. smartphone applications, or professional equipment for identification or embedding specific information within the sample parts. To evaluate the functionality, defined as the generated light contrast from contingent micro ridges, the replicates were characterized by means of a robot assisted vision system, provided with a light source and a camera, used as a gonioreflectometer. The contrast was then correlated to the replication quality, i.e. the deviation of three defining parameters of the structures from the mould insert, thus determining the best processing conditions. The results showed that high injection speed, 60 °C mould temperature and 100 MPa packing pressure were required to achieve optimal replication and generated contrast: large variations in the surface functional behaviour were present even for small differences between the parts. However, an empirical approach highlighted that even for processing parameters that were less likely to promote replication, sufficient information decoding was achieved.
Original languageEnglish
JournalPrecision Engineering
Volume60
Pages (from-to)594-601
ISSN0141-6359
DOIs
Publication statusPublished - 2019

Keywords

  • Functional surfaces
  • Micro-structured surfaces
  • Injection moulding
  • Process optimization
  • Vision systems
  • Contrast quantification
  • Reflectance

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