The progressive improvement of additive manufacturing (AM) techniques enables the production of geometrically complex and lightweight parts, which explains the incredibly fast growth of AM for space and aerospace applications. The first standards require the production of witness specimens manufactured together with the components for assessment and qualification for the material control. However, one of the most critical issues is determining the ‘fitness-for-purpose’ of fatigue loaded parts, which is strictly related to the microstructure and defects generated during the manufacturing process. One of the most suitable techniques for detecting defects even near the surface or in thin, complex geometries is micro-computed tomography (μ-CT). This paper deals with the application of statistics of extremes for analysing X-ray CT scan measurements in view of component assessment by discussing its advantages and requirements.

Qualification of AM parts: Extreme value statistics applied to tomographic measurements

ROMANO, SIMONE;BERETTA, STEFANO
2017-01-01

Abstract

The progressive improvement of additive manufacturing (AM) techniques enables the production of geometrically complex and lightweight parts, which explains the incredibly fast growth of AM for space and aerospace applications. The first standards require the production of witness specimens manufactured together with the components for assessment and qualification for the material control. However, one of the most critical issues is determining the ‘fitness-for-purpose’ of fatigue loaded parts, which is strictly related to the microstructure and defects generated during the manufacturing process. One of the most suitable techniques for detecting defects even near the surface or in thin, complex geometries is micro-computed tomography (μ-CT). This paper deals with the application of statistics of extremes for analysing X-ray CT scan measurements in view of component assessment by discussing its advantages and requirements.
2017
Additive manufacturing; AlSi10Mg; Computed tomography; Defect analysis; Fatigue; Qualification; Materials Science (all); Mechanics of Materials; Mechanical Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1031517
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