1,721,275 research outputs found
Application of synchrosqueezing transform and autoencoders for monitoring of production systems. A case study on plastic chain conveyor systems
No full textThis paper presents a data-driven methodology for monitoring and quantifying the degradation of plastic chain conveyors, a relevant asset in industrial automation. The proposed approach leverages system vibrations and employs the synchrosqueezing Short-Time Fourier Transform and convolutional autoencoders to generate a compact representation space for the data. This space enables the construction of control charts to monitor the extracted metrics. The method is intended to provide a comprehensive assessment of system degradation. Applied to a plastic conveyor chain on a dataset collected over a four-month period, the methodology seeks to identify and quantify the two most significant degradation mechanisms: the chain’s elongation due to joint wear and the wear and tear of the slide rail. This research intends to address a significant gap in the literature, offering a practical and automatic solution for condition monitoring based on vibration for industrial equipment. Two aspects will be considered for the evaluation of the method: the capability to “reduce” the storage usage (dimensionality reduction) and the anomaly detection capabilities of the system
On the use of vibrations and temperatures for the monitoring of plastic chain conveyor systems
No full textIn industrial automation, the transportation of unit loads plays a crucial role. This paper addresses the under-explored area of plastic chain conveyors, a versatile and efficient means of transport within production processes. Despite their widespread use, these conveyors suffer from wear and tear due to continuous contact between the chain and guide rails, often leading to unscheduled shutdowns and increased costs. The literature on monitoring solutions for such systems is sparse, particularly for plastic chains. This paper aims to bridge this gap by surveying the most common wear mechanisms for these systems and presenting a physical model that describes the interaction between the chain links and guide rails, based on chain of masses, springs and dampers and the Archard wear model. This model allows to relate the variations due to wear with other physical quantities, such as passage frequencies of the links and heat generated due to friction. The comprehensive model provides analytical formulas to understand the vibrations induced by the chain on the platform and the guide-rail temperatures. To validate the model and evaluate how the measurements are affected by the degradation of the system, an extensive experimental campaign was conducted on a conveyor test rig, acquiring vibration and temperature data. The end goal is to identify and discuss methodologies suitable for estimating the wear mechanisms of conveyor systems, with a focus on the constraints of industrial environments. Hence, this study aims to lay the groundwork for defining monitoring solutions that enhance the maintenance efficiency of plastic chain conveyor systems. The results suggest that the power Spectral Densities (PSD) of the platform's accelerations are sufficient to estimate the average links pitch, which in turn could be used to assess the chain elongation. Besides, the local temperatures confirmed the model observations, making them suitable for estimating the slide-rail thinning
A novel approach for quality control of automated production lines working under highly inconsistent conditions
No full textWhen addressing product quality standards in manufacturing lines, a critical issue is the identification of the parameters that define the quality of the final product and their tracking. The problem of process control under inconsistent working condition of an automatic machinery, i.e. when some parameters are highly variable, is still quite unexplored in literature. This objective becomes even more challenging when the most important process variables are not directly measurable. This paper demonstrates that it is possible to achieve quality control by coupling a soft sensor, whose predictive model is a neural network, with an anomaly detector. The methodology has been applied to automatic machinery placed in a manufacturing line, where high variability in production rate has an important effect on the measured physical variables. This makes automated and accurate quality control difficult, due to the fact that in this test case the data collected are accelerometers signals, extremely sensible to variation in machine productivity by definition. It is shown that this approach outperforms many other classification methods (Support Vector Machines, Ensemble Bagged Tree, Discriminant Analysis, K-nearest neighbours and the direct application of a Neural Network) proposed in the past, achieving satisfactory results evaluated on the basis of four metrics (Accuracy, precision, recall and F1-score), even if anomalous data have been collected in a limited number of machine's working points. In particular, an accuracy over 92% has been reached also for production rates where only nominal conditions are collected. This procedure exceeds the direct training of a neural network (accuracy of 57.6% at new production rates), as well as the application of shallow methods based on the extraction of dimensionless features (around 35% in accuracy at new production rates)
Implementation of an innovative technique to improve Sauvignon Blanc wine quality
No full textThe purpose of the study was to compare two different pressing systems of Sauvignon Blanc grapes using an innovative wine press manufactured by Puleo Srl Company (Marsala, Italy). Grape pressing is a very important step in the winemaking process as it may promote the presence and/or absence of enzyme processes on the must, leading to the creation of different products in terms of chemical composition from the same grapes. Chemical composition of must firstly and wine after, obtained from the two pressing mode, was analysed in first instance with PCA method
Statistical advances in epidemiology and public health
Full text linkThe key role of statistical modeling in epidemiology and public health is unquestionable [...]
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
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
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