The Stochastic Reliability Modeling of a Centrifugal Pump of a Rectifier Cooling System of DC-Rectiformer with a Standby Unit and Preventive Maintenance

Objectives: To perform a stochastic reliability analysis of a standby Rectifier Cooling System in the aluminum industry, with the aim of evaluating system performance metrics such as Mean Time to System Failure (MTSF), availability, and busy period in the context of an energy-intensive industrial setting. Methods: The study employs Weibull distribution to model failure and repair rates of system components, considering two types of repair personnel (regular and expert). The semi-markov process and regenerative point techniques are applied to derive key performance measures. The system, including DC-rectiformers, pumps, and cooling mechanisms, is analyzed under assumed operational data through numerical and graphical illustrations. Findings: The analysis yields quantitative insights into system reliability, showing how repair personnel skill level affects system availability and MTSF. The study highlights the role of standby pump operation in maintaining cooling system efficiency, with performance metrics indicating potential improvements in system uptime under optimized conditions. Novelty: This work provides a unique application of stochastic modeling techniques, specifically Semi-Markov and Weibull-based reliability analysis, to the Rectifier Cooling System in an aluminum production setting. It also introduces a comparative evaluation of system availability based on repair personnel expertise, which is not commonly addressed in prior reliability studies within this industry. 2020 AMS Classification: 90B25, 60K10 Keywords: DC-Rectiformer, Rectifier Cooling System, Preventive Maintenence, MTSF, Weibull distribution