Development of a Predictive Model for Industrial Circuit Breaker Degradation in Stochastic Environments

The need to improve asset management frameworks has been a major concern among industrial consumers in Uganda. Poor asset management increases frequency of faults among industrial consumers thus resulting into poor quality of power supplied. This research was developed based on the fact that cases of cascaded failures in connected systems have rampantly increased among industrial consumers in Kawempe Industrial Area. This has been due to factors such as proliferation of substandard circuit breakers, malfunctioning of circuit breaker components, external conditions that affect circuit breaker performance such as temperature, dust, etc., and negligence in conduction of compliance tests among others. These factors have not been put into consideration for the sake of effective asset management. Prior to implementation of an effective asset management framework, there is need for diagnosis of the present factors that hamper effective asset management and develop replacement strategies. This paper focused on Circuit Breakers (CBs) since they consume a large proportion of budgets of maintenance of utilities and are critical to system reliability. The parameters influencing CB performance were determined by Weibull modeling in MATLAB 2018: findings revealed that the industrial CBs had a maximum hazard rate of 5.6% with an average mean time-to-failure of 13.47 years, which represents a high propensity to death and critical condition of all CBs