Optimizing Industrial Reliability: A Comparative Study of Hot and Cold Standby Configurations in Three-Unit Parallel Systems

Abstract

This comparative research study explores the efficacy of two parallel systems, Model A employing a hot standby configuration and Model B utilizing a cold standby setup, each comprising three units operating based on demand. The investigation focuses on evaluating the reliability and cost-effectiveness of these systems, employing metrics such as Mean Time to System Failure, availability at full and reduced capacity, repairer busy periods, downtime, and profit analysis using Semi-Markov and regenerative point techniques. Results reveal that Model B (cold standby) outperforms Model A (hot standby) across multiple parameters, including Mean Time to System Failure, availability, repairer busy periods, downtime, and profitability. Specifically, Model B demonstrates higher values for Mean Time to System Failure, Availability at full and reduced capacity, Busy period for repairmen, and Profit in Rs. Consequently, it is inferred that Model B proves to be more reliable and efficient than Model A. These findings underscore the potential advantages of employing cold standby configurations in similar machinery setups, offering insights to enhance system performance and minimize downtime, thus suggesting avenues for optimizing cold standby parallel systems based on the study's outcomes.