1,721,047 research outputs found
A FEA-like Method for Evaluating the Ship Equilibrium Point
No full textThis paper will focus on a method for evaluating the ship equilibrium point via the On Board Stability System (OBSS) module. Starting from the exact 3D geometry of ship hull, described by a discrete model in a standard format, distribution of all weights onboard and data acquired by the system, OBSS calculates the ship floating condition using a FEA-like method (Finite Elements Analysis). Results of this paper represent the joint efforts of the public-private partnership in being between Centro Cultura Innovativa d'Impresa (CCII) of University of Salento, Apphia s.r.l. and Avio S.p.A
Prognostic Health Management of Production Systems. New Proposed Approach and Experimental Evidences
Full text linkPrognostic Health Management (PHM) is a maintenance policy aimed at predicting the occurrence of a failure in components in order to minimize unexpected downtimes of complex systems and maximize their availability. Recent developments in condition monitoring (CM) techniques and Artificial Intelligence (AI) tools enabled the collection of a huge amount of data in real-time and its transformation into meaningful information that will support the maintenance decision-making process. The emerging Cyber-Physical Systems (CPS) technologies connect distributed physical systems with their virtual representations in the cyber computational world. The PHM assumes a key role in the implementation of CPS in manufacturing contexts, since it allows to keep CPS and its machines in proper conditions. On the other hand, CPS-based PHM provide an efficient solution to maximize availability of machines and production systems.
In this paper, evolving and unsupervised approaches for the implementation of PHM at a component level are described, which are able to process streaming data in real-time and with almost-zero prior knowledge about the monitored component. A case study from a real industrial context is presented. Different unsupervised and online anomaly detection methods are combined with evolving clustering models in order to detect anomalous behaviors in streaming vibration data and integrate the so-generated knowledge into supervised and adaptive models; then, the degradation model for each identified fault is built and the resulting RUL prediction model integrated into the online analysis. Supervised methods are applied to the same dataset, in batch mode, to validate the proposed procedure
Integration of CAD tools in damage management system
No full textThis paper focuses on the implementation of an advanced CAD integrated application for shipboard safety control systems. Damage Control Management System (DCMS) is a software module included into the Damage Control System (DCS), developed by the researchers of Apphia s.r.l. and CCII (Centro Cultura Innovativa d’Impresa) of University of Salento
Components monitoring and intelligent diagnosis tools for Prognostic Health Management approach
No full textThe main goal of maintenance of complex systems is to minimize downtimes to make the system as much available as possible. Condition-Based Maintenance (CBM) is one of the most effective policies used by Companies nowadays, based on the monitoring of different parameters of machines that reflect its health status. CBM can be implemented by using the Prognostic Health Management approach, made up of four main steps: data collection, signal processing, diagnostic, and prognostic. It is a proactive process that requires the development of predictive models that can trigger the alarm for corresponding maintenance. The huge amount of data that need to be collected has suggested the use of models coming from statistic theory and data mining, in order to discover regular pattern in large data sets and generate knowledge that will be useful in the maintenance decision-making process. In this paper, different intelligent methods for diagnostic purpose, such as Decision trees, K-NN algorithm, Artificial Neural Networks and support Vector Machine, are used to classify the health condition of a rotating component. Collected signals are processed in the time-domain and in the time-frequency-domain in order to extract relevant features to give as input data for the intelligent methods. Such methods are finally compared by evaluating the related accuracy value for both training and testing. The main result of this work is that the time-frequency analysis improves accuracy in classifying the health condition of machines and that new intelligent models can perform in an effective way even in the time-domai
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
A cross‐sectorial review of industrial best practices and case histories on Industry 4.0 technologies
Full text linkIndustry 4.0 (I4.0) was introduced in 2011, and its advanced enablers strongly affect industrial practices. In the current literature, while several papers offer general reviews on the topic, contributions exploring the evidences coming from the implementation of I4.0 in multi-sector Small and Medium Enterprises (SMEs) and large enterprises are few and expected. To address this gap, a comprehensive review of the main I4.0 enabling technologies is conducted, focusing on implementation experiences in companies belonging to different sectors. Forty (40) real case studies are analyzed and compared. The results show that 63% of the identified applications involve large enterprises in the transport sector, that is, automotive, aeronautics, and railway, adopting a structured set of enabling technologies. SMEs engaged in I4.0 projects primarily belong to the mechanical engineering sector, and 37% of such projects deals with the preliminary feasibility analysis of introducing a single enabling technology. Conclusions and trends guide researchers and practitioners in understanding the implementation level of I4.0 technologies
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
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