Optimisation of Imaging Confocal Microscopy for Topography Measurements of Metal Additive Surfaces

Author:

Newton Lewis12ORCID,Thanki Aditi3,Bermudez Carlos4ORCID,Artigas Roger4,Thompson Adam1ORCID,Haitjema Han3ORCID,Leach Richard1ORCID

Affiliation:

1. Manufacturing Metrology Team, Faculty of Engineering, University of Nottingham, Nottingham NG8 1BB, UK

2. The Manufacturing Technology Centre Ltd., Pilot Way, Ansty Park, Coventry CV7 9LU, UK

3. Manufacturing Metrology Section, Manufacturing Processes and Systems, Mechanical Engineering Department, KU Leuven, 3001 Leuven, Belgium

4. Sensofar, Parc Audiovisual de Catalunya Ctra, BV-1274, Km 1, 08225 Terrassa, Barcelona, Spain

Abstract

Additive manufactured surfaces, especially metal powder bed fusion surfaces, present unique challenges for measurement because of their complex topographies. To address these measurement challenges, optimisation of the measurement process is required. Using a statistical approach, sensitivity analyses were performed on measurement settings found on a commercial programmable array scanning confocal microscope. The instrument measurement process parameters were compared by their effects on three quality indicators: the areal surface texture parameter Sa, measurement noise, and number of non-measured points. An analysis was performed using a full factorial design of experiments for both the top and side surfaces of test surfaces made from Inconel 718 and Ti-6Al-4V using powder bed fusion. The results indicated that measurements of metal additive surfaces are robust to changes in the measurement control parameters for Sa, with variations within 5% of the mean parameter value for the same objective, surface, and measured area. The number of non-measured points and the measurement noise were more varied and were affected by the choice of measurement control parameters, but such changes could be predicted by the statistical models. The contribution offered by this work is an increased understanding of imaging confocal microscopy measurement of metal additive surfaces, along with the establishment of good practice guidance for measurements.

Funder

“PAM2 (Precision Additive Metal Manufacturing)” of the EU Framework Programme for Research and Innovation within Horizon 2020—Marie Skłodowska-Curie Innovative Training Networks

Engineering and Physical Sciences Research Council

Manufacturing Technology Centre

Publisher

MDPI AG

Subject

General Agricultural and Biological Sciences

Reference37 articles.

1. Geometrical metrology for metal additive manufacturing;Leach;Ann. CIRP,2019

2. Surface texture metrology for metal additive manufacturing: A review;Townsend;Precis. Eng.,2016

3. Leach, R.K. (2013). Characterisation of Areal Surface Texture, Springer.

4. Characterisation methods for powder bed fusion processed surface topography;Lou;Precis. Eng.,2019

5. Feature-based characterisation of Ti6Al4V electron beam powder bed fusion surfaces fabricated at different surface orientations;Newton;Addit. Manuf.,2020

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