Predictive Maintenance is a plan for monitoring equipment performance and condition that decreases the chance of failure under normal operating conditions. The goal is to predict a failure and then strive to avoid it through corrective maintenance. Whether or whether they are required to foresee the need for maintenance, traditional methods depend on historical data regarding equipment performance and previous breakdowns or simply generate periodic maintenance schedules. Modern predictive maintenance solutions, on the other hand, continuously monitor equipment behavior to collect data in real time and utilize advanced neural network and artificial algorithms to decide and raise an alert when a potential equipment breakdown is likely to occur.Rayven, a predictive maintenance IoT solutions provider, for example, provides AI and IoT-based pipeline monitoring and leak detection to assist oil and gas companies save money.
A well-designed process model, which comprises linked equipment, feature engineering, machine learning, implementation, and prediction, is the foundation of a basic Predictive Maintenance system. A smart maintenance predictive solution collects data and then generates an automated feature set and an optimized predictive model with real-time estimates and outcomes. Furthermore, the growing number of connected assets in industrial applications is driving the growth of the smart predictive maintenance solutions.
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