1,720,964 research outputs found
New multi-function building plate for improving metal laser powder bed fusion by enhancing the alignment accuracy of in-process monitoring data, computed tomography measurements, and building volume geometry
Full text linkLaser-based powder bed fusion of metals (PBF-LB/M) is an additive manufacturing process enabling the fabrication of parts with highly complex and customizable geometries, enhanced strength-to-weight properties, and minimized material waste. Despite its unique capabilities, PBF-LB/M needs research and innovation efforts to enhance process dynamics and product quality, as well as to broaden its adoption in high-value industrial sectors, such as aerospace and biomedical. In this context, in-process monitoring solutions and post-process part quality evaluations are fundamental to improving the process towards sustainable, first-time-right, and zero-defect production. This paper describes a novel building plate concept for metal laser powder fusion, whose characteristics were specifically designed to enable and improve the performances of in-process monitoring and high-resolution X-ray computed tomography (CT) measurements. In particular, the plate features markers for perspective correction in off-axis optical monitoring and dismountable inserts with machined geometrical elements to be used for the precise alignment between high-resolution CT reconstructions, in-process gathered data, and building volume geometry. The plate capabilities were demonstrated through examples related to in-process monitoring and post-process X-ray CT measurements
INVESTIGATION ON THE USE OF MACHINE LEARNING AND X-RAY COMPUTED TOMOGRAPHY FOR LACK-OF-FUSION POROSITY PREDICTION
No full textWhile laser powder bed fusion technology has gained widespread adoption across various industries, its susceptibility to low repeatability and manufacturing challenges often results in defect formation. Consequently, there is a growing interest in the development of in-process monitoring systems to detect defects as fabrication progresses. This necessitates robust correlations between process events and actual defects, based on an accurate comparison between datasets acquired during in-process monitoring and post-process measurements. This work explores the correlation between off-axis long-exposure process monitoring and aligned reference data on internal defects, obtained through X-ray computed tomography. Particularly, a machine learning workflow including feature extraction and logistic regression was designed and implemented, with a specific focus on predicting lack-of-fusion porosity formation directly from in-process monitoring data
New experimental approach for local measurements of effective layer thickness, powder bed density and volumetric energy density to enhance metal laser powder bed fusion
No full textThis work presents an experimental approach for simultaneous measurements of effective layer thickness, powder bed density, and volumetric energy density, useful to improve the analysis of process dynamics and enhance precision in metal laser powder bed fusion. The approach is based on a special building platform, including removable inserts with reference geometries, and high-resolution X-ray computed tomography. The local variability in layer thickness and energy density are evaluated and used as indicators of process stability and energy transmission efficiency. The contextual measurement of powder bed density offers additional insights into potential process-related influences such as spatter formation and denudation
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Evaluation of defects in laser powder bed fusion metal parts via in-process optical measurements and post-process X-ray computed tomography
No full textLaser powder bed fusion (LPBF) enables the fabrication of metal parts characterized by high geometrical complexity, unique possibilities of customization and increasingly good mechanical properties. However, parts produced by LPBF are often characterized by poor geometrical and dimensional accuracy as well as by a number of internal defects, which undermine a wider application of LPBF in industry. Several in-process measurement methods have been proposed to identify out-of-control process conditions and take immediate action, as well as to improve the understanding of the LPBF process. However, the correlation between in-process measurement results and actual defects in the fabricated parts is not always clear yet. This work presents an experimental study aimed at defining a reproducible methodology for comparing optical in-process evaluations to X-ray computed tomography post-process measurements of actual defects
Prediction of spatter-related defects in metal laser powder bed fusion by analytical and machine learning modelling applied to off-axis long-exposure monitoring
Full text linkLaser powder bed fusion of metals is increasingly used for fabricating complex parts requiring good mechanical properties. Simultaneously, researchers in the field are intensifying the efforts to reduce defects, such as internal porosities, which hinder a wider industrial adoption of this technology, urging process monitoring to a pivotal role in defect identification and mitigation. Therefore, understanding the correlation between in-process monitoring signals and post-process actual defects is fundamental to taking informed decisions and potential corrective actions during the process. This work focuses on developing models to predict spatter-related defects from specific process signatures detected through off-axis long-exposure imaging. Layer-wise images were properly aligned with corresponding cross-sections from tomographic reconstructions to investigate the relationship between spatter-related signatures and actual defects measured by X-ray computed tomography. This relationship was used as a knowledge basis to develop an analytical image-processing approach and a machine learning-based methodology, which were then compared in terms of their correlation performances. The advantages and limitations of both methods are discussed in the paper. Both approaches led to promising results in the prediction of lack-of-fusion defects caused by spatters, with the machine learning approach showing a prediction accuracy in the order of 90 % for defects with equivalent diameter above 90 μm, while the analytical model needed equivalent diameters larger than 130 μm to reach a prediction accuracy in the order of 80 %. Furthermore, the machine learning method led to strong results regarding early defect detection, with most of the investigated defects properly predicted by analysing two consecutive layers after the signature detection
Deformations modelling of metal additively manufactured parts and improved comparison of in-process monitoring and post-process X-ray computed tomography
Full text linkThe comparison of potential defects detected through in-process real-time monitoring systems and actual defects measured in the fabricated parts by X-ray computed tomography offers relevant opportunities for improving the understanding, sustainability and precision of metal laser powder bed fusion processes. However, the comparison outcome strongly depends on data alignment accuracy, which is hindered by typical process-induced part deformations arising during and after production. This work presents a methodology that includes the modelling of part deformations for improving the alignment and comparison of in-process and post-process datasets. The methodology was successfully implemented, starting from deformations predicted by process simulations, and verified experimentally by producing samples including fiducials specifically designed to provide insights on local deformations. Results show an improved data alignment accuracy, which is fundamental for enabling the establishment of robust correlations aiding the reduction of false positives and false negatives in the in-process gathered signals. The approach is also found to be effective in accurately categorizing non-significant process signatures occurring during the fabrication, hence preventing the implementation of wrong corrective actions
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
- …
