A TOPSIS-BASED METHODOLOGY FOR PRIORITIZING MAINTAINANCE ACTIVITIES: A CASE STUDY OF CHANCHAGA MUNICIPAL WATER WORKS

Abstract

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. Budget shortage has negative impact on maintenance strategies and results in the undesirable deterioration of production plant’s components and increased risk of accidents and downtimes. In most traditional maintenance practices, the choice of “which maintenance location that 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 failure of components of a 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 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 relative closeness coefficient of 0.79592 which shows its highest maintenance priority. This is attributed to age of the pipes, high pressure in the system during the period of low water consumption, environmental and soil condition. Therefore, this component requires urgent attention for maintenance. The alternative A1 (the pumping machine) has relative closeness coefficient of 0.56815 which shows it is less criticality when compare with the components like valve, reservoir, pipe and power source. Therefore, the maintenance can be delayed on this component.