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Naji, M. |
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Motta, Antonella |
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Aletan, Dirar |
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Mohamed, Tarek |
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Ertürk, Emre |
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Taccardi, Nicola |
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Kononenko, Denys |
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Petrov, R. H. | Madrid |
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Alshaaer, Mazen | Brussels |
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Bih, L. |
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Casati, R. |
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Muller, Hermance |
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Kočí, Jan | Prague |
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Šuljagić, Marija |
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Kalteremidou, Kalliopi-Artemi | Brussels |
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Azam, Siraj |
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Ospanova, Alyiya |
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Blanpain, Bart |
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Ali, M. A. |
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Popa, V. |
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Rančić, M. |
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Ollier, Nadège |
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Azevedo, Nuno Monteiro |
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Landes, Michael |
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Rignanese, Gian-Marco |
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Ion, William
University of Strathclyde
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (14/14 displayed)
- 2021Optimisation of cutting parameters and surface deformation during thin steel sheets plasma processing using Taguchi approachcitations
- 2017A novel methodology for in-process monitoring of flow formingcitations
- 2017Automated microstructural analysis of titanium alloys using digital image processingcitations
- 2017In-process monitoring and quality control of hot forging processes towards Industry 4.0
- 2017Protective coatings for ceramic superplastic forming diescitations
- 2016Protective coatings for superplastic forming ceramic dies
- 2016Investigating relationships between laser metal deposition deployment conditions and material microstructural evolution
- 2016Remanufacturing H13 steel moulds and dies using laser metal deposition
- 2014Thermal sprayed protective coatings for superplastic forming ceramic dies : a monitoring system of die condition
- 2014Protective coatings for superplastic forming dies
- 2014Protective coatings for superplastic forming ceramic dies
- 2014Protective coatings for superplastic forming ceramic dies : opportunities for thermal spray technology
- 2014Thermal sprayed protective coatings for superplastic forming ceramic dies
- 2013Identifying the dominant failure mode in the hot extrusion tooling used to forge nickel based superalloycitations
Places of action
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article
Automated microstructural analysis of titanium alloys using digital image processing
Abstract
<p>Titanium is a material that exhibits many desirable properties including a very high strength to weight ratio and corrosive resistance. However, the specific properties of any components depend upon the microstructure of the material, which varies by the manufacturing process. This means it is often necessary to analyse the microstructure when designing new processes or performing quality assurance on manufactured parts. For Ti6Al4V, grain size analysis is typically performed manually by expert material scientists as the complicated microstructure of the material means that, to the authors knowledge, no existing software reliably identifies the grain boundaries. This manual process is time consuming and offers low repeatability due to human error and subjectivity. In this paper, we propose a new, automated method to segment microstructural images of a Ti6Al4V alloy into its constituent grains and produce measurements. The results of applying this technique are evaluated by comparing the measurements obtained by different analysis methods. By using measurements from a complete manual segmentation as a benchmark we explore the reliability of the current manual estimations of grain size and contrast this with improvements offered by our approach.</p>