| Article ID: | iaor201523933 |
| Volume: | 31 |
| Issue: | 2 |
| Start Page Number: | 251 |
| End Page Number: | 263 |
| Publication Date: | Mar 2015 |
| Journal: | Quality and Reliability Engineering International |
| Authors: | Kou Gang, Ergu Daji, Zhou Yu |
| Keywords: | statistics: empirical, decision, decision theory: multiple criteria, maintenance, repair & replacement |
Effective maintenance decision‐making depends on information obtained by analysing system operating data. In this paper, we present a method to measure the daily, weekly, monthly and long‐term performance of the corrective repair and preventive maintenance by analysing the operating data. Operating data from a bus fleet, served successively in two routes, were observed for over 6 years. The proportional intensity model is used to evaluate the environment effects, which include temperature, humidity and rainfall. Two composite models are proposed to analyse the interplay of events, which include repair/maintenance arrival/finished time, cost, repair/maintenance number and time between failures. A maintenance performance scorecard is developed to present a snapshot of the bus fleet maintenance performance, which can assist maintenance planning and management.