1,722,016 research outputs found

    In situ monitoring of powder bed fusion homogeneity in electron beam melting

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    Increasing attention has been devoted in recent years to in situ sensing and monitoring of the electron beam melting process, ranging from seminal methods based on infrared imaging to novel methods based on backscattered electron detection. However, the range of available in situ monitoring capabilities and solutions is still quite limited compared to the wide number of studies and industrial toolkits in laser-based additive manufacturing processes. Some methods that are already industrially available in laser powder bed fusion systems, such as in situ detection of recoating errors, have not yet been investigated and tested in electron beam melting. Motivated by the attempt to fill this gap, we present a novel in situ monitoring methodology that can be easily implemented in industrial electron beam melting machines. The method is aimed at identifying local inhomogeneity and irregularities in the powder bed by means of layerwise image acquisition and processing, with no external illumination source apart from the light emitted by the hot material underneath the currently recoated layer. The results show that the proposed approach is suitable to detect powder bed anomalies, while also highlighting the link between the severity of in situ detected errors and the severity of resulting defects in the additively manufactured part

    A statistical learning method for image-based monitoring of the plume signature in laser powder bed fusion

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    The industrial breakthrough of metal additive manufacturing processes mainly involves highly regulated sectors, e.g., aerospace and healthcare, where both part and process qualification are of paramount importance. Because of this, there is an increasing interest for in-situ monitoring tools able to detect process defects and unstable states since their onset stage during the process itself. In-situ measured quantities can be regarded as “signatures” of the process behaviour and proxies of the final part quality. This study relies on the idea that the by-products of laser powder bed fusion (LPBF) can be used as process signatures to design and implement statistical monitoring methods. In particular, this paper proposes a methodology to monitor the LPBF process via in-situ infrared (IR) video imaging of the plume formed by material evaporation and heating of the surrounding gas. The aspect of the plume naturally changes from one frame to another following the natural dynamics of the process: this yields a multimodal pattern of the plume descriptors that limits the effectiveness of traditional statistical monitoring techniques. To cope with this, a nonparametric control charting scheme is proposed, called K-chart, which allows adapting the alarm threshold to the dynamically varying patterns of the monitored data. A real case study in LPBF of zinc powder is presented to demonstrate the capability of detecting the onset of unstable conditions in the presence of a material that, despite being particularly interesting for biomedical applications, imposes quality challenges in LPBF because of its low melting and boiling points. A comparison analysis is presented to highlight the benefits provided by the proposed approach against competitor methods

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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