Capacity-based daily maintenance optimization of urban bus with multi-objective failure priority ranking

There is a specific correlation between bus operational failures and work intensity. The hysteresis effect identified the correlation between the number of repairs and the bus capacity of urban bus fleets. Therefore, administrators can determine whether to perform maintenance on a specific bus based on the severity of detected potential failures. At this stage, administrators should make a maintenance decision after considering maintenance costs, operational losses, and bus capacity. As a result, we propose a model for optimizing maintenance decisions with multi-objective failure priority ranking in this article. We employ the TOPSIS to prioritize the maintenance of failed buses based on indicators such as transport capacity loss, downtime, and maintenance cost. Finally, the study verifies the model's validity by utilizing real data from urban bus operation and maintenance data in China. The outcomes of the case study indicate that implementing the model can reduce operating expenses by 18.8143% when considering a corrective maintenance cost of 300. The model adoption provides a significant reduction in operating costs.