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  • Pavlopoulos, Ioannis, 1983-, et al. (author)
  • Automotive fault nowcasting with machine learning and natural language processing
  • 2024
  • In: Machine Learning. - 0885-6125 .- 1573-0565. ; 113:2, s. 843-861
  • Journal article (peer-reviewed)abstract
    • Automated fault diagnosis can facilitate diagnostics assistance, speedier troubleshooting, and better-organised logistics. Currently, most AI-based prognostics and health management in the automotive industry ignore textual descriptions of the experienced problems or symptoms. With this study, however, we propose an ML-assisted workflow for automotive fault nowcasting that improves on current industry standards. We show that a multilingual pre-trained Transformer model can effectively classify the textual symptom claims from a large company with vehicle fleets, despite the task’s challenging nature due to the 38 languages and 1357 classes involved. Overall, we report an accuracy of more than 80% for high-frequency classes and above 60% for classes with reasonable minimum support, bringing novel evidence that automotive troubleshooting management can benefit from multilingual symptom text classification.
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  • Result 1-1 of 1
Type of publication
journal article (1)
Type of content
peer-reviewed (1)
Author/Editor
Borg, Markus (1)
Pavlopoulos, John (1)
Steinert, Olof (1)
Lindgren, Tony, 1974 ... (1)
Pavlopoulos, Ioannis ... (1)
Romell, Alv (1)
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Curman, Jacob (1)
Randl, Korbinian, 19 ... (1)
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University
Stockholm University (1)
Lund University (1)
Language
English (1)
Research subject (UKÄ/SCB)
Natural sciences (1)
Year
2024 (1)

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