The interest toward metal Additive Manufacturing (AM) technologies is growing in several industries, especially in biomedical, aerospace and rapid tooling sectors. To meet the stringent requirements imposed by these industries, the capability, repeatability and stability of AM processes are of key importance and their improvement represents a fundamental step toward widespread adoption. Considering the efforts in terms of time and cost for additively producing a part, together with the complexity of components fabricated via AM, quality controls performed at the end of the process represent a relevant portion of the overall part cost. For this reason, in-situ monitoring of AM processes is a potential key enabler for quick detection of defects and to reduce the need of post-process inspections. By focusing on the class of AM technologies named Selective Laser Melting (SLM), this study aims at providing a general methodology for characterisation and monitoring of the process via analysis of high-speed videos. The proposed approach focuses on the computation and assessment of statistical descriptors that, through properly designed control charts and spatial maps, has a twofold application: analysing the response of the descriptors to different process and design choices, and assessing their behaviour with respect to process stability. The proposed methodology is made available and could be exploited in future works.
Le tecnologie di stampa 3D stanno suscitando crescente interesse in diversi settori, in particolare in campo biomedico, aerospaziale e di attrezzaggio rapido. Con l’obbiettivo di soddisfare gli stringenti requisiti imposti da questi settori, la capacità, la ripetibilità e la stabilità dei processi di stampa 3D diventano di cruciale importanza, e l’ottimizzazione di quest’ultimi rappresenta un passaggio fondamentale verso l’adozione definitiva di questa tecnologia. Considerando il tempo e il costo necessari per produrre parti stampate in 3D, oltre alla complessità geometrica di queste, affidarsi a sistemi di controllo qualità post-processo non è una soluzione economicamente sostenibile. Per questo motivo, il monitoraggio online dei processi rappresenta un fattore chiave per l’identificazione online dei difetti e ridurre il ricorso a controlli qualità ex-post. Focalizzandosi sulla classe di tecnologie di stampa 3D nota come SLM (Selective Laser Melting), questa tesi ha l’obbiettivo di fornire una metodologia generale per la caratterizzazione ed il monitoraggio del processo di stampa, attraverso l’analisi di video ad alta velocità. Il metodo proposto si basa sul calcolo e l’analisi di descrittori statistici che, attraverso la progettazione di carte di controllo dedicate e la creazione di mappe spaziali, possono avere un duplice utilizzo: analisi delle reazioni dei descrittori statistici rispetto a differenti parametri di processo e progettazione, e valutazione del loro andamento come indicatore di stabilità di processo. Il metodo discusso in questa tesi è reso disponile per utilizzi ed implementazioni future.
In-situ image-based analysis of metal additive manufacturing
CUBICCIOTTI, SIMONE;FERRARI, PAOLO
2016/2017
Abstract
The interest toward metal Additive Manufacturing (AM) technologies is growing in several industries, especially in biomedical, aerospace and rapid tooling sectors. To meet the stringent requirements imposed by these industries, the capability, repeatability and stability of AM processes are of key importance and their improvement represents a fundamental step toward widespread adoption. Considering the efforts in terms of time and cost for additively producing a part, together with the complexity of components fabricated via AM, quality controls performed at the end of the process represent a relevant portion of the overall part cost. For this reason, in-situ monitoring of AM processes is a potential key enabler for quick detection of defects and to reduce the need of post-process inspections. By focusing on the class of AM technologies named Selective Laser Melting (SLM), this study aims at providing a general methodology for characterisation and monitoring of the process via analysis of high-speed videos. The proposed approach focuses on the computation and assessment of statistical descriptors that, through properly designed control charts and spatial maps, has a twofold application: analysing the response of the descriptors to different process and design choices, and assessing their behaviour with respect to process stability. The proposed methodology is made available and could be exploited in future works.| File | Dimensione | Formato | |
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2017_Dicembre_Ferrari_Cubicciotti.pdf
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https://hdl.handle.net/10589/136906