| Abstract
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<p>Predicting future maintenance nee … <p>Predicting future maintenance needs of equipment can be addressed in a variety of ways. Methods based on machine learning approaches provide an interesting platform for mining large data sets to find patterns that might correlate with a given fault. In this paper, we approach predictive maintenance as a classification problem and use Random Forest to separate data readouts within a particular time window into those corresponding to faulty and non-faulty component categories. We utilize diagnostic trouble codes (DTCs) as an example of event-based data, and propose four categories of features that can be derived from DTCs as a predictive maintenance framework. We test the approach using large-scale data from a fleet of heavy duty trucks, and show that DTCs can be used within our framework as indicators of imminent failures in different components.</p>ailures in different components.</p>
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| Author
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Parivash Pirasteh +
, Sławomir Nowaczyk +
, Sepideh Pashami +
, Magnus Löwenadler +
, Klas Thunberg +
, Henrik Ydreskog +
, Peter Berck +
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| Conference
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WSDM 2019: The 12th ACM International Conference on Web Search and Data Mining, Melbourne, VIC, Australia, 11-15 February, 2019
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| DOI
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http://dx.doi.org/10.1145/3304079.3310288 +
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| Diva
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http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:1335754
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| HostPublication
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Proceedings of the Workshop on Interactive Data Mining +
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| PublicationType
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Conference Paper +
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| Publisher
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Association for Computing Machinery (ACM) +
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| Title
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Interactive feature extraction for diagnostic trouble codes in predictive maintenance : A case study from automotive domain +
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| Year
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2019 +
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| Has queryThis property is a special property in this wiki.
|
Publications:Interactive feature extraction for diagnostic trouble codes in predictive maintenance : A case study from automotive domain +
, Publications:Interactive feature extraction for diagnostic trouble codes in predictive maintenance : A case study from automotive domain +
, Publications:Interactive feature extraction for diagnostic trouble codes in predictive maintenance : A case study from automotive domain +
, Publications:Interactive feature extraction for diagnostic trouble codes in predictive maintenance : A case study from automotive domain +
, Publications:Interactive feature extraction for diagnostic trouble codes in predictive maintenance : A case study from automotive domain +
, Publications:Interactive feature extraction for diagnostic trouble codes in predictive maintenance : A case study from automotive domain +
, Publications:Interactive feature extraction for diagnostic trouble codes in predictive maintenance : A case study from automotive domain +
, Publications:Interactive feature extraction for diagnostic trouble codes in predictive maintenance : A case study from automotive domain +
, Publications:Interactive feature extraction for diagnostic trouble codes in predictive maintenance : A case study from automotive domain +
, Publications:Interactive feature extraction for diagnostic trouble codes in predictive maintenance : A case study from automotive domain +
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| Categories |
Publication +
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| Modification dateThis property is a special property in this wiki.
|
2 August 2019 20:23:18 +
|
