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Condition Monitoring

Condition monitoring involves the continuous tracking of equipment’s operational status. This strategy allows companies to monitor equipment health, detect anomalies, and predict failures, all of which contribute to improved efficiency and productivity.

Tecnico utilizza un pannello di controllo per la manutenzione predittiva in un ambiente produttivo.

By utilizing advanced technologies and in-depth analysis processes, condition monitoring provides real-time insights into machine performance. Techniques such as vibration analysis, cycle time analysis, temperature monitoring, and noise monitoring enable detailed and timely diagnostics.

This approach helps reduce the costs of unscheduled maintenance, enhances maintenance planning, and allows for more effective resource management. Integrating IoT and AI technologies facilitates a deeper understanding of failure causes, leading to reduced environmental impact and more sustainable operations when monitoring equipment health.

Tips for Implementing Condition Monitoring

Integrate Specific Sensors for Comprehensive Monitoring

Deploy a network of advanced sensors to monitor equipment conditions, particularly for auxiliary machines such as pumps, bearings, motors, fans, or reducers, as well as production machinery like CNC machines. Vibration sensors, acoustic sensors, and thermocouples provide real-time data on operational conditions, allowing early detection of potential issues. Ensure sensors are strategically placed to capture detailed information on each phase of the production process, aiding in the detection of anomalies.

Leverage AI for Predictive Analysis

Adopt AI-based solutions for real-time data analysis. Artificial intelligence can process large volumes of data collected by sensors to identify patterns and detect anomalies that may not be visible to the human eye. This helps predict failures, allowing for more efficient maintenance planning, minimizing downtime, and reducing associated costs.

Optimize Maintenance Scheduling with Historical Data

Analyze historical data to enhance maintenance planning. Historical analysis helps identify recurring patterns or cyclical failures, allowing for preventive action before issues occur. This reduces the need for emergency maintenance, improves equipment availability, and optimizes resource usage, making maintenance more predictable and less reactive.

See How Zerynth Helps Companies Streamline Production

Zerynth enables businesses to optimize production processes and increase the value of connected industrial products. The Zerynth Platform tracks the status of each piece of equipment, monitors energy consumption, emissions, and real-time conditions, promoting proactive maintenance.

Discover our resources on machine monitoring!

Case Study: Predictive Maintenance for automotive Industry

Vitesco Technologies Italy has reduced machine downtime and is now able to predict pneumatic valve malfunctions 24 hours in advance.

White Paper: Preventive and Predictive Maintenance in Industry 4.0

Leveraging IoT solutions for preventive and predictive maintenance techniques enables the scheduling of necessary interventions to minimize failures, resulting in significant cost reductions and improved production efficiency.

interview with emanuele figliolia

Q&A with Zerynth: How to Make Your Factory Sustainable

Interview with Emanuele Figliolia, Product Manager at Zerynth