]> 2026-04-04T11:02:51+02:00 In4Uptime 0 en Sławomir Nowaczyk The goal of the project is to keep commercial vehicles in good operational condition, both from a financial and safety point of view. Haulers and transporters require OEMs to provide vehicles having close to 100% uptime. That means no stops, unless planned, as well as guarantees on optimal performance of all components ensuring acceptable levels of CO2 emission and fuel consumption. Utilizing data that comes from sources with different origin, such as on-board, off-board, structured, unstructured, private and public, and by combining information and finding common patterns will allow us to better adapt the service contracts and maintenance plans to the needs of individual customers and individual vehicles. Volvo Technology will coordinate the project and is overall responsible. The other partners of the project are: Volvo Information Technology, Högskolan i Halmstad, Svenska Innovationsinstitutet and Recorded Future. 11 false Procedure.png In4UptimeInfo.pdf 2016-01 2457388.5 Sławomir Nowaczyk 2014-02 2456689.5 Vehicle diagnostics and predictive maintenance In4Uptime 2014-05-16T13:27:51Z 2456794.0610069 In4Uptime 0 1 list 2 [[Title::In4Uptime]] In4Uptime# QUERY33b170a53db32bff2734a561cee8e607 0 1 ul 4 [[Category:Person]] [[Project::In4Uptime]] [[Category:Staff]] In4Uptime# QUERYf6396eb8e7703b54a06d7ed778ddafaf 0 1 ul 4 [[Category:Person]] [[Project::In4Uptime]] [[Affiliation::+]] In4Uptime# QUERY5e315383648befa99dded6043ece428c Sławomir Nowaczyk 0 en Sławomir Nowaczyk Yuantao Fan 0 en Yuantao Fan Publications:A Self-Organized Fault Detection Method for Vehicle Fleets 500 en A Self-Organized Fault Detection Method for Vehicle Fleets Publications:Evaluation of Self-Organized Approach for Predicting Compressor Faults in a City Bus Fleet 500 en Evaluation of Self-Organized Approach for Predicting Compressor Faults in a City Bus Fleet Publications:Incorporating Expert Knowledge into a Self-Organized Approach for Predicting Compressor Faults in a City Bus Fleet 500 en Incorporating Expert Knowledge into a Self-Organized Approach for Predicting Compressor Faults in a City Bus Fleet Publications:Predicting Air Compressor Failures with Echo State Networks 500 en Predicting Air Compressor Failures with Echo State Networks Project 102 en Project Projects 102 en Projects