Chiller Sustainability: With Predictive Maintenance Strategies for Long Term Energy & Cost Savings

Abstract

Chiller systems play an important part in maintaining optimal temperatures in different industrial and commercial environments. However, they present notable difficulties because of their substantial energy use and operating expenses. This study focuses on the significance of predictive maintenance solutions in improving the sustainability of chillers by diminishing energy consumption and decreasing long-term costs. The introduction emphasizes the significance of chillers in contemporary infrastructure and the urgent need for energy-efficient solutions. The aim of the research is to evaluate the influence of predictive maintenance on the energy efficiency and cost reduction of chiller systems. The systematic literature review evaluates the current body of research on predictive maintenance, emphasizing its capacity to enhance energy efficiency and cost-effectiveness in chiller operations. The process is doing a quantitative study using SPSS software, with data obtained from organizations that have adopted predictive maintenance on their chiller systems. The research posits hypotheses to investigate the impact of predictive maintenance on energy consumption, cost savings, and the life of system. Data analysis centres on the use of statistical tests, such as ANOVA and Chi- square test, to assess the efficacy of these tactics. The conclusion shows that the use of predictive maintenance greatly improves the long-term viability of chillers by optimizing energy usage and decreasing operating expenses. These results emphasize the significance of implementing predictive maintenance in the chiller sector, offering useful information for firms aiming for long-term sustainability and efficiency. This study adds to the expanding pool of information on sustainable practices, providing practical suggestions for enhancing the efficiency of chiller systems while reducing their environmental footprint and operating costs.