https://www.scipedia.com/wd/index.php?action=history&feed=atom&title=Consilvio_et_al_2018aConsilvio et al 2018a - Revision history2026-04-21T20:44:03ZRevision history for this page on the wikiMediaWiki 1.27.0-wmf.10https://www.scipedia.com/wd/index.php?title=Consilvio_et_al_2018a&diff=204461&oldid=prevScipediacontent: Scipediacontent moved page Draft Content 300542469 to Consilvio et al 2018a2021-02-03T15:11:51Z<p>Scipediacontent moved page <a href="/public/Draft_Content_300542469" class="mw-redirect" title="Draft Content 300542469">Draft Content 300542469</a> to <a href="/public/Consilvio_et_al_2018a" title="Consilvio et al 2018a">Consilvio et al 2018a</a></p>
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</td></tr></table>Scipediacontenthttps://www.scipedia.com/wd/index.php?title=Consilvio_et_al_2018a&diff=204460&oldid=prevScipediacontent: Created page with " == Abstract == This paper presents the objectives and the main expected results from IN2SMART Project, funded by the SHIFT2RAIL Joint Undertaking and the European Commission..."2021-02-03T15:11:48Z<p>Created page with " == Abstract == This paper presents the objectives and the main expected results from IN2SMART Project, funded by the SHIFT2RAIL Joint Undertaking and the European Commission..."</p>
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== Abstract ==<br />
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This paper presents the objectives and the main expected results from IN2SMART Project, funded by the SHIFT2RAIL Joint Undertaking and the European Commission, within the SHIFT2RAIL Research Programme. This project contributes to the development of an intelligent and automated platform for Asset Management decision-making, focused on the planning of predictive, condition and risk-based Asset Management activities. Based on a framework for Asset Management aligned with international standards, the platform receives inputs from tools and models for predictive analytics that are able to extract information on current and future asset condition, using heterogeneous data from the field. In particular, nowcasting and forecasting methodologies, diagnostics and anomaly detection techniques and indicators derived from Risk, RAMS and LCC analysis are used to support decision-making. Finally, real-world business cases are presented to show the expected applicability of the proposed automated platform and the usefulness of the relevant methodology.<br />
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== Original document ==<br />
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The different versions of the original document can be found in:<br />
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* [http://hdl.handle.net/11567/971919 http://hdl.handle.net/11567/971919]<br />
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* [https://zenodo.org/record/1441166 https://zenodo.org/record/1441166] under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode<br />
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* [https://zenodo.org/record/1441166 https://zenodo.org/record/1441166],<br />
: [http://dx.doi.org/10.5281/zenodo.1441165 http://dx.doi.org/10.5281/zenodo.1441165] under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode<br />
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* [https://zenodo.org/record/1441166 https://zenodo.org/record/1441166],<br />
: [http://dx.doi.org/10.5281/zenodo.1441166 http://dx.doi.org/10.5281/zenodo.1441166] under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode<br />
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DOIS: 10.5281/zenodo.1441166 10.5281/zenodo.1441165</div>Scipediacontent