1,720,995 research outputs found
Knowledge Generation of Wire Laser-Beam-Directed Energy Deposition Process Combining Process Data and Metrology Responses
No full textIndustries are leveraging the wire laser-beam-directed energy deposition (DED-LB) additive manufacturing (AM) process to manufacture and repair high-quality, defect-free, and cost-effective parts. However, expensive, non-easily accessible, and complex metrology equipment is needed to quantify part-related performance metrics such as cross-sectional dimensional accuracy and intrinsic defects. This information is necessary for establishing the operating process window and for the quality characterization of the part. Therefore, this work presents a methodology that combines information captured from a vision-based monitoring system with the output of Computed Tomography (CT) towards the knowledge generation and process optimization of wire DED-LB. The design of experiments as well as the interpretation of the results are achieved by employing Nested ANOVA where the dependency of cross-sectional stability on the laser power parameter is demonstrated, enabling, at the same time, the understanding of unstructured datasets where multiple parameters vary at different levels. Finally, this work can be the pillar for adopting new production and part requirements while also giving directions about the effect of control strategies on the part quality
Stack and Structure: Ultrafast Lasers for Additive Manufacturing of Thin Polymer Films for Medical Applications
Full text linkOvercoming the limitations of powder-based additive manufacturing processes is a crucial aspect for the manufacturing of patient-specific sophisticated implants with tailored properties. Within this work, a novel manufacturing process for the fabrication of polymer-based implants is proposed. This manufacturing process is inspired by the laminated object manufacturing technology and is based on using thin films as raw material, which are processed using an ultrafast laser source. Utilizing thin films as a starting material helps to avoid powder contamination during additive manufacturing, thus supporting the generation of internal cavities that can be filled with secondary phases. Additionally, the use of medical materials mitigates the burden of a later certification of potential implants. Furthermore, the ultrafast laser supports the generation of highly resolved structures smaller than the average layer thickness (from 50 to 100 µm) through material ablation. These structures can be helpful to obtain progressive part properties or a targeted stress flow, as well as a specified release of secondary phases (e.g., hydrogels) upon load. Within this work, first investigations on the joining, cutting, and structuring of thin polymer films with layer thickness of between 50 and 100 µm using a ps-pulsed laser are reported. It is shown that thin film sizes of around 50 µm could be structured, joined, and cut successfully using ultrafast lasers emitting in the NIR spectral range
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
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
Decision Support System (DSS) for Manufacturing Engineering of Cans Rolling
No full textPublisher Copyright: © The Author(s) 2025.Decision Support Systems (DSS) can help factory workers in the decision-making step of multiple tasks. In digital factories, these systems make use of data towards a human-centered manufacturing. Rolling of large and thick plates into cans is a common practice in the metal forming industry to fabricate pipes or tanks. The process is adjusted by trial and error with a high level of operator intervention. Furthermore, only a small number of cans are identical. The objective of this work is to prescribe, by means of a DSS, the process parameters to be applied by the operator in the machine to optimize the can fabrication. The development of the DSS involved several steps, including firstly signal preprocessing and classification and then data extraction, aggregation, and regression in a multi-stage prediction framework. A significant use of domain knowledge for a data-centric solution contributes to the quality of the recommendations and the ability to organize and transfer know-how among operators.Peer reviewe
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Advances in Artificial Intelligence in Manufacturing II
No full textThis open access book reports on recent developments of artificial intelligence applications in the manufacturing industry. Gathering contributions to the second European Symposium on Artificial Intelligence in Manufacturing, held on October 16, 2024, in Athens, Greece, it reports on machine learning, deep learning and generative AI models for process monitoring, optimization, and control, flexible and precise industrial robots, human-robot collaboration, data management and information technologies, digital twins, data augmentation and synthetic data. Giving a special emphasis to the integration of artificial intelligence in manufacturing systems, automation and processes, this book offers a timely and practice-oriented guide to a multidisciplinary audience of engineering researchers, system developers, AI scientists and industrial managers
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