1,720,961 research outputs found
Analytics and Intelligence for Smart Manufacturing
No full textDigital transformation is one of the main aspects emerged by the current 4.0 revolution. It embraces the integration between the digital and physical environment,including the application of modelling and simulation techniques, visualization, and data analytics in order to manage the overall product life cycle
Random forests model selection
No full textRandom Forests (RF) of tree classifiers are a popular ensemble method for classification. RF have shown to be effective in many different real world classification problems and nowadays are considered as one of the best learning algorithms in this context. In this paper we discuss the effect of the hyperparameters of the RF over the accuracy of the final model, with particular reference to different theoretically grounded weighing strategies of the tree in the forest. In this way we go against the common misconception which considers RF as an hyperparameter-free learning algorithm. Results on a series of benchmark datasets show that performing an accurate Model Selection procedure can greatly improve the accuracy of the final RF classifier
Random Forests model selection
No full textRandom Forests (RF) of tree classifiers are a popular ensemble method for classification. RF have shown to be effective in many different real world classification problems and nowadays are considered as one of the best learning algorithms in this context. In this paper we discuss the effect of the hyperparameters of the RF over the accuracy of the final model, with particular reference to different theoretically grounded weighing strategies of the tree in the forest. In this way we go against the common misconception which considers RF as an hyperparameter-free learning algorithm. Results on a series of benchmark datasets show that performing an accurate Model Selection procedure can greatly improve the accuracy of the final RF classifier
Performance assessment and uncertainty quantification of predictive models for smart manufacturing systems
No full textWe review in this paper several methods from Statistical Learning Theory (SLT) for the performance assessment and uncertainty quantification of predictive models. Computational issues are addressed so to allow the scaling to large datasets and the application of SLT to Big Data analytics. The effectiveness of the application of SLT to manufacturing systems is exemplified by targeting the derivation of a predictive model for quality forecasting of products on an assembly line
Investigating sustainability as a performance dimension of a novel Manufacturing Value Modeling Methodology (MVMM): From sustainability business drivers to relevant metrics and performance indicators
No full textThe world and society are now constantly evolving through scenarios of global change and development having direct and indirect impact on manufacturing companies. The related manufacturing value chains require different assessment and evaluation of strategic dimensions such as Quality, Innovation, Flexibility and Sustainability. In order to capture and evaluate these dimensions, value modeling methodologies are currently used. Since sustainability is gaining attention as a close future business driver, in this paper an existing and specific Manufacturing Value Modeling Methodology (MVMM) is firstly shortly described to focus then on the analysis and development of sustainability dimension. Implementing manufacturing sustainability into the MVMM requires the setting of a structured information set (named catalogue) that presents an overview of sustainable challenges and opportunities in order to identify a correct structure of metrics (and relevant key performance indicators) for assessment and evaluation, which translate business goals into consistent manufacturing strategy, and allows to improve operational performance by suggesting, and then adopting, a set of best practices. To this end, a qualitative literature review on industrial sustainability performance management has been performed with the aim of analyzing the existing body of literature, re-organizing these data accordingly to a hierarchy of structured KPIs, identifying poor analyzed areas, and finally providing a first comprehensive database of metrics to build up and structure the aforementioned catalogue
A Manufacturing Value Modeling Methodology (MVMM): A Value Mapping and Assessment Framework for Sustainable Manufacturing
No full textSustainable manufacturing is becoming increasingly important. This requires sustainable industrial system different to todayâs global industry with different business models, creating different products and services requiring new strategies, frameworks, and tools. The evolution towards a âsustainableâ industrial production systems requires a holistic approach, with a fundamental reassessment of the value creation. In order to achieve this target a system design approach is required. In this paper an existing and specific Manufacturing Value Modeling Methodology (MVMM) is used as a value mapping framework to help firms in creating value propositions better suited for sustainability considering economic, environmental and social perspectives. Concerning sustainability, implementing it into the MVMM requires the setting of a catalogue that presents an overview of sustainable external and internal impact factors and a mapping between them in order to translate business goals into manufacturing strategy, and allows to improve operational performance by adopting a set of sustainable industrial practices
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
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