{"id":35675,"date":"2020-08-21T12:55:41","date_gmt":"2020-08-21T12:55:41","guid":{"rendered":"http:\/\/tugraztestweb.asol.at\/gesamtverzeichnis\/unkategorisiert\/smart-data-for-railway-asset-management\/"},"modified":"2020-08-21T14:56:41","modified_gmt":"2020-08-21T12:56:41","slug":"smart-data-for-sustainable-railway-asset-management-ebook","status":"publish","type":"product","link":"https:\/\/tugraztestweb.asol.at\/en\/gesamtverzeichnis\/bauingenieurwissenschaften\/smart-data-for-sustainable-railway-asset-management-ebook\/","title":{"rendered":"Smart data for sustainable Railway Asset Management"},"content":{"rendered":"

Sorry, this entry is only available in Deutsch<\/a>.<\/p>

Rail infrastructure managers are forced to work sustainably and
\nefficiently due to increasing cost pressure. Track engineers face
\nincreasing difficulties to legitimate necessary measures owing to budget
\n restrictions. This requires an objective tool enabling a proper
\ncondition monitoring as well as component-specific, preventive
\nmaintenance planning.
This book presents a condition evaluation of
\nrailway track using innovative track data analyses. Applying functional
\nknowledge – both IT and railway skills \u2013 allows extracting smart data
\nout of big data for railway asset management. The only required input
\ndata are vertical track geometry and track gauge as already measured and
\n stored by infrastructure managers using state-of-the-art track
\nrecording cars. Based on a bottom-up approach, this methodology enables
\nfor both establishing net-wide renewal demands and an in-depth
\nassessment of specific track sections. In this way, planning of specific
\n renewal and maintenance measures for track sections becomes just as
\npossible as strategic asset management on a large scale.
<\/p>","protected":false},"excerpt":{"rendered":"

Sorry, this entry is only available in Deutsch<\/a>.<\/p>\n

Rail infrastructure managers are forced to work sustainably and
\nefficiently due to increasing cost pressure. Track engineers face
\nincreasing difficulties to legitimate necessary measures owing to budget
\n restrictions. This requires an objective tool enabling a proper
\ncondition monitoring as well as component-specific, preventive
\nmaintenance planning.
This book presents a condition evaluation of
\nrailway track using innovative track data analyses. Applying functional
\nknowledge – both IT and railway skills \u2013 allows extracting smart data
\nout of big data for railway asset management. The only required input
\ndata are vertical track geometry and track gauge as already measured and
\n stored by infrastructure managers using state-of-the-art track
\nrecording cars. Based on a bottom-up approach, this methodology enables
\nfor both establishing net-wide renewal demands and an in-depth
\nassessment of specific track sections. In this way, planning of specific
\n renewal and maintenance measures for track sections becomes just as
\npossible as strategic asset management on a large scale. <\/p>\n","protected":false},"featured_media":40210,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"yoast_head":"\n\n\n\n\n\n\n\n\n\n\t\n\t\n\n\n\t\n