A Topsis-Based Methodology for Prioritizing Maintenance Activities Suitable for A Municipal Water Works

Abstract

Maintenance is performed on industrial plants to ensure that they continue to function up to the designed capacity. In most instances, scheduled maintenances are hardly fully implemented owing to budget fluctuations/constraints. The budget shortage has a negative impact on maintenance strategies and results in the undesirable deterioration of the production plant’s components and increased risk of accidents and downtimes. In most traditional maintenance practices, the choice of “which maintenance location should be addressed urgently and which to delay” is left to the subjective discretion of the maintenance manager. One of the dangers of such discretional judgment in maintenance is that the risk of delayed maintenance is different for different components even for the same plant. The Thesis developed and implemented a methodology to minimize the impact of budget fluctuation by quantifying the risks associated with the failure of components of municipal water works plants as a basis for prioritizing the maintenance activities. TOPSIS algorithm uses a value system to estimate the risks related to failure and repair of the various components of the plant under various criteria and to integrate the scores to arrive at a prioritization metric as an alternative to the risk priority number of the traditional failure mode and effect analysis (FMEA). The framework is implemented on a real case study of municipal water works and the conclusions proved well for wider applications in varied and allied industrial settings. From the results obtained, the pipeline component (herein coded as alternative A2) has a relative closeness coefficient of 0.79592 which shows its highest maintenance priority. This is attributed to the age of the pipes, high pressure in the system during the period of low water consumption, and environmental and soil conditions. Therefore, this component requires urgent attention for maintenance. The alternative A1 (the pumping machine) has a relative closeness coefficient of 0.56815 which shows it is less critical when compared with the components like valve, reservoir, pipe and power source. Therefore, maintenance can be delayed on this component.