On-machine focus variation measurement for micro-scale hybrid surface texture machining

Teguh Santoso*, Wahyudin P. Syam, Subbareddy Darukumalli, Yukui Cai, Franz Helmli, Xichun Luo, Richard Leach

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)
20 Downloads (Pure)

Abstract

Fast and accurate in-line areal surface topography measuring instruments are required to control the quality of microscale manufactured components, without significantly slowing down the production process. Full-field areal optical surface topography measurement instruments are promising for in-line or on-machine measurement applications due to their ability to measure quickly, to access small features and to avoid surface damage. This paper presents the development and integration of a compact optical focus variation sensor for on-machine surface topography measurement mounted on to a hybrid ultraprecision machine tool. The sensor development is described and a case study involving the on-machine dimensional measurement of the depth of hydrophobic microscale features, including microchannels and micro-dimples, is presented. Comparisons of results between the on-machine measurements obtained by the developed sensor and a desktop focus variation microscope are presented and discussed. The comparison results show that the developed focus variation sensor is able to perform on-machine dimensional measurement of microscale features within sub-micrometre accuracy.

Original languageEnglish
Pages (from-to)2353-2364
Number of pages12
Journal The International Journal of Advanced Manufacturing Technology
Volume109
Issue number9-12
Early online date30 Jul 2020
DOIs
Publication statusPublished - 1 Aug 2020

Funding

This research work was undertaken in the context of MICROMAN project (“Process Fingerprint for Zero-defect Net-shape MICROMANufacturing”, 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), and by the H2020-MSCA-ITN-2016 project PAM2 (Precision Additive Metal Manufacturing), EU Framework Programme for Research and Innovation H2020 – Grant Agreement No 721383. This work was also supported by the Engineering and Physical Sciences Research Council [grant number EP/M008983/1].

Keywords

  • focus variation
  • motion stage
  • on-machine measurement
  • precision engineering
  • surface texture

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