Predictive maintenance is the process of predicting when maintenance is required before equipment failure occurs. This is achieved by using data collected from IoT sensors, which monitor the performance of machines and equipment in real-time. By analyzing this data, businesses can detect patterns and anomalies that indicate a potential failure and take corrective actions before the equipment breaks down.
IoT sensors are installed on machines and equipment to collect data on various parameters such as temperature, vibration, pressure, and humidity. This data is transmitted to a central system, which uses machine learning algorithms to analyze the data and detect patterns that indicate potential issues.
The system generates alerts when it detects an anomaly, and maintenance personnel can use this information to perform preventive maintenance, reducing the risk of equipment failure. By continuously monitoring equipment performance, predictive maintenance systems can also identify areas of improvement in the maintenance process, enabling businesses to optimize their maintenance programs further.
