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Much equipment in the eThekwini Electricity network has been in use for several decades. Failure of this equipment could critically impact electricity supply to customers, and result in high costs associated with loss of load and/or component replacement. The fundamental motive for any power utility is to plan, operate, and maintain power infrastructure such that customers receive reliable electric services at the minimum expense possible.   For this dissertation, the Reliability Centered Maintenance (RCM) model was implemented in the eThekwini Electricity network. This model emphasises the importance of long-term planning and allocation of resources over the life time of a transformer, or any other component. RCM is an ongoing process that entails gathering data from operating systems performance, and using this data to improve design, operation, and maintenance of the system. The eThekwini Power network failure statistics for the previous five years were collected and thoroughly analysed to identify critical components associated with higher failure rates, and associated consequences. Upon examination, it was determined that the power transformer is a critical component of the system. The transformer plays a significant role in the power system due to its remarkable effect on overall reliability, in addition to the fact that it is a major cost factor in the power grid. Transformer management comprises of identifying the appropriate type and frequency of maintenance, and the appropriate time to replace the transformer in a cost-effective manner.   The Markov model for ascertaining the transformer’s remaining service life was applied on the identified critical transformer. The transformer deterioration process is modelled by representing the oil insulation by discrete stages. Using the Institute of Electrical and Electronics Engineers (IEEE) standard for interpreting the transformer insulation, the transformer under review was found to be at stage two. Further analysis was performed on system unavailability rates versus mean time to first failure (MTTFF). The analyses indicated that the higher the MTTFF, the longer the system availability whereas the lower the MTTFF, the more reduced the system availability. Improving the MTTFF rates of a system will enhance reliability. The effective application of RCM will optimise the maintenance processes with reasonable expenditures.

Reliability centered maintenance implementation on the eThekwini electricity network for system maintenance process optimisation