A knowledge-based system for bus maintenance has the potential for improving the efficiency and effectiveness of bus maintenance by making the knowledge of the most highly skilled maintenance personnel available throughout the transit industry. A knowledge-based system is a practical application of the research that has been performed on artificial intelligence. These systems have been developed for a wide range of applications, including the diagnosis of dieselelectric locomotive problems. The four basic elements of a knowledge-based system are described, and an example is provided of the application of such a system to bus maintenance. From a review of the impact on performance of two other techniques for bus diagnosis, spectrochemical oil analysis and the New York City Transit Authority's Automated Bus Diagnostic System, it is concluded that both a reduction in the time required for diagnosis and an increase in the quality of maintenance, measured in terms of a reduction in road calls, would be achieved. It is recommended that a prototype system be developed so that both the costs of implementation and the savings that would result can be determined.

Media Info

  • Media Type: Print
  • Features: Figures; References; Tables;
  • Pagination: pp 85-91
  • Monograph Title: Winter and transit bus maintenance and highway maintenance management
  • Serial:

Subject/Index Terms

Filing Info

  • Accession Number: 00453132
  • Record Type: Publication
  • ISBN: 0309039088
  • Files: TRIS, TRB
  • Created Date: May 31 1986 12:00AM