Air conditioning systems are a major contributor to energy consumption in commercial buildings, making effective maintenance essential for keeping energy use and costs under control. Predictive maintenance is a powerful tool that uses machine learning algorithms to analyze data points collected by air conditioning systems and identify potential problems that could affect future performance. This type of maintenance, including multi-zone variable air volume (VAV) systems, proactively detects operational issues that lead to energy waste and notifies stakeholders of maintenance needs as soon as possible. An intelligent building management platform (IBMP) can be used to implement predictive maintenance for air conditioning. Predictive air conditioning maintenance provides an extra layer of protection between scheduled maintenance visits, allowing you to optimize your maintenance visits.
OnPoint's data-driven predictive maintenance for HVAC enables you to create effective efficiency strategies, achieve significant savings, improve operations, and enhance the occupant experience. With this predictive maintenance solution, you can set up rules to monitor anomalies in your customers' HVAC system and maintain peak performance. Predictive maintenance of air conditioning systems using an IBMP completely transforms a building's maintenance program and drastically reduces maintenance costs. This data-based predictive maintenance approach for air conditioning systems offers many advantages over conventional preventive maintenance, resulting in greater cost savings. Buildings IOT provides the next-generation services and products necessary for predictive air conditioning maintenance.
