Enhancing reliability and performance of sequential chiller system using copula

Chiller systems play a pivotal role across various industries, providing essential cooling solutions. Ensuring their efficiency and reliability necessitates precise performance evaluation. The Gumbel-Hougaard family copula, an efficient approach for modelling multivariate dependencies, is used in this paper to carry out an in-depth examination of chiller machine systems. Through this method, we can capture intricate correlations between chiller system characteristics and performance metrics such as reliability, availability, mean time to failure (MTTF), cost and MTTF sensitivity. We further conducted sensitivity analysis using our copula-based model to identify key factors influencing chiller system performance. The efficacy of the copula-based approach in capturing intricate relationships between several chiller system features and critical performance measures is exemplified by numerical findings that are displayed in tables and graphs. We can make conclusions about the results since they have been validated using quantitative data and can be seen in tables and graphs. This deeper understanding will assist us in optimising system operations for improved cost-effectiveness and energy efficiency. Additionally, our copula-based approach enhances performance evaluation compared to traditional methods by allowing us to assess the system's resilience under varying operational conditions.