A Predictive Maintenance System for Bus Fleets: Innovation and Research from the Case Study of Ravenna

The paper introduces an innovative Predictive Maintenance (PdM) system to assess the quality of engine oil for buses, tested in Ravenna (Italy) within the “European Bus System of the Future – EBSF_2” project, funded by the European Union. The system relies on PdM software linked to oil sensors and filters, installed on a test fleet and using a specifically designed Information Technology (IT) architecture. The system enables continuous assessment of the oil quality, which is highly predictive of engine performance. It thus detects potential or prospective breakdowns and plans replacement with spare parts when needed or ahead of regular schedules. The system also detects which substances, namely metals, and problems in general cause poor oil quality. The paper describes the system and its IT architecture, the testing scenarios, the assessment methodology, based on a comparison of performance with and without the PdM system, and the preliminary outcomes. Thus far, results (associated with various areas of impact – maintenance, operations, fuel consumption, costs, staff training, and the efficiency of the IT system in processing data) are encouraging, although operating costs seem to have risen, and they enable an assessment of additional, potential environmental benefits (especially in terms of mitigation of emissions toxicity and improvement of the waste management process). Such results are analyzed and commented on, with the objective of advancing knowledge to inform further research studies beyond EBSF_2, in the field of PdM.

  • Supplemental Notes:
    • This paper was sponsored by TRB committee AP010 Standing Committee on Transit Management and Performance.
  • Authors:
    • Corazza, Maria Vittoria
    • Guida, Umberto
    • Musso, Antonio
    • Petracci, Enrico
    • Tozzi, Michele
    • Vasari, Daniela
    • de Verdalle, Emmanuel
  • Conference:
  • Date: 2018

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; Photos; References; Tables;
  • Pagination: 16p

Subject/Index Terms

Filing Info

  • Accession Number: 01658000
  • Record Type: Publication
  • Report/Paper Numbers: 18-00906
  • Files: TRIS, TRB, ATRI
  • Created Date: Jan 25 2018 9:35AM