Auto Learning for Industrial Equipment Monitoring

Advancing the Automation of Predictive Maintenance Asystom, a specialist in condition monitoring for industrial equipment using artificial intelligence, is introducing an evolution of its system at Global Industrie 2025: the "Auto Learning" mode. This feature is designed to simplify and accelerate the deployment of machine monitoring by automatically adjusting the learning period before activating predictive diagnostics. Automated and Adaptive Learning Determining the appropriate learning duration for an industrial machine typically requires expert assessment, considering its operating cycles and usage conditions. With "Auto Learning", the algorithm dynamically analyzes the required data volume and adjusts the learning period accordingly, ensuring a smooth transition to continuous monitoring. Functionality and Integration The "Auto Learning" mode is integrated into the AsystomSentinel solution, which relies on autonomous sensors to collect and analyze vibrational and acoustic data. These data are then securely transmitted to either a cloud-based or on-premise platform, enabling multiple levels of analysis: Continuous monitoring of equipment health status. Detection of deviations and anomalies to facilitate proactive maintenance. Access to detailed data for in-depth analysis by technical teams. A Tool for Optimized Predictive Maintenance By reducing the need for manual adjustments at startup and improving the reliability of diagnostics during monitoring, "Auto Learning" enhances the accessibility of predictive maintenance while optimizing industrial equipment operations. 📍 Asystom will be at Global Industrie 2025 to present this development and engage with industry professionals on condition monitoring solutions.