Additive Manufacturing (AM) is a new technology which allows to simplify the manufacturing process of complex shape objects that are difficult or even impossible to produce with traditional processes. Current AM technologies, however, carry a series of process-related defects such as internal pores, spatter particles and partially melted metal powders, which lead to to lower surface quality of as-built components with respect to traditional techniques. These defects, especially those on the surface and just below it, have the most detrimental effect on fatigue resistance of these parts to the extent to significantly limit their end use. An effective method to detect and measure these surface features will therefore be key in assessing the fatigue properties of these components particularly when defect-tolerant design methods are used. This document deals with the work which has been done to develop a novel procedure to process X-ray micro-Computed Tomography (μ-CT) scans of additively manufactured parts. The aim is to characterise the as-built surfaces of a component to estimate the dimension of the most critical defects from the fatigue resistance point of view. First, the statistics of extreme values is applied to describe the surface features of specimens starting from 2D μ-CT scans. With the same data, the conventional profile roughness parameters are also computed and the results of the two methods are compared. In a following analysis the defects on the 3D surfaces of the specimens are sampled and the related statistics of defects are compared to the 2D ones. Eventually, the robustness of the new method is assessed by comparing the estimated defect size with the statistics of defects measured on the fracture surface of specimens broken after being fatigue tested.
L'Additive Manufacturing (AM) è una tecnologia produttiva particolarmente vantaggiosa che semplifica in modo significativo il processo di costruzione di oggetti di forma complessa, se non addirittura impossibili da realizzare con i processi di lavorazione meccanica convenzionali. I procedimenti AM odierni, però, comportano una serie di difetti legati al processo costruttivo stesso quali porosità, schizzi di materiale e particelle parzialmente fuse, che danno luogo a una qualità superficiale inferiore rispetto a quella di componenti realizzati con le tecnologie tradizionali. Questi difetti, specialmente quelli sulla superficie o appena sotto, sono particolarmente critici per la resistenza a fatica degli oggetti così realizzati. È quindi essenziale poter disporre di un metodo efficace per individuare e misurare questi difetti soprattutto in un ambito di progettazione defect-tolerant. Questo documento descrive il lavoro di tesi che è stato svolto e che ha portato alla messa a punto di un nuovo procedimento per elaborare le scansioni ottenute con la tomografia computerizzata a raggi X di parti prodotte con la tecnologia AM. L'obbiettivo è quello di caratterizzare le superfici nella condizione as-built così da stimare le dimensioni dei difetti critici dal punto di vista della resistenza a fatica. Nella prima parte si è applicata la statistica dei valori estremi su misure di superficie ottenute da scansioni 2D di provini. La rugosità superficiale di questi provini è stata misurata anche con i criteri di misura tradizionali e i risultati dei due metodi confrontati. Successivamente, i difetti sulle reali superfici 3D dei provini sono stati campionati e le relative statistiche confrontate con quelle delle sezioni 2D. Da ultimo, il nuovo metodo è stato validato confrontando la dimensione stimata dei difetti dei provini as-built rispetto alle misure effettuate sugli stessi provini rotti dopo la prova di fatica.
Surface features rating of as-built 3D printed parts for fatigue assessment
DALDOSSI, ALESSANDRO
2018/2019
Abstract
Additive Manufacturing (AM) is a new technology which allows to simplify the manufacturing process of complex shape objects that are difficult or even impossible to produce with traditional processes. Current AM technologies, however, carry a series of process-related defects such as internal pores, spatter particles and partially melted metal powders, which lead to to lower surface quality of as-built components with respect to traditional techniques. These defects, especially those on the surface and just below it, have the most detrimental effect on fatigue resistance of these parts to the extent to significantly limit their end use. An effective method to detect and measure these surface features will therefore be key in assessing the fatigue properties of these components particularly when defect-tolerant design methods are used. This document deals with the work which has been done to develop a novel procedure to process X-ray micro-Computed Tomography (μ-CT) scans of additively manufactured parts. The aim is to characterise the as-built surfaces of a component to estimate the dimension of the most critical defects from the fatigue resistance point of view. First, the statistics of extreme values is applied to describe the surface features of specimens starting from 2D μ-CT scans. With the same data, the conventional profile roughness parameters are also computed and the results of the two methods are compared. In a following analysis the defects on the 3D surfaces of the specimens are sampled and the related statistics of defects are compared to the 2D ones. Eventually, the robustness of the new method is assessed by comparing the estimated defect size with the statistics of defects measured on the fracture surface of specimens broken after being fatigue tested.File | Dimensione | Formato | |
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Descrizione: Testo della tesi
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https://hdl.handle.net/10589/151641