Predictive maintenance in the industrial machinery sector is a crucial strategy for ensuring plant reliability and efficiency. Its primary goals include reducing operational disruptions and costs associated with unexpected failures. By constantly monitoring the condition of machines through sensors and advanced technologies, any signs of malfunction or wear and tear can be identified early, enabling targeted and planned interventions to prevent serious and costly failures. This helps extend the useful life of machines and optimize the use of human and material resources.

Intelligent Monitoring

The WARNN system, developed by Alma Automotive, allows key values of machine operation to be monitored.

• Vibration
• Temperature
• Lubricant quality
• Operating points
• Machine data

Anticipate the Problem

Using Artificial Intelligence, WARNN builds a digital twin of the observed machine and compares all acquired data with the corresponding reference values in case of optimal operation.

Thanks to this process, it is possible to anticipate faults and understand when the machine is deviating from its standard operation, triggering a whole series of alarms that enable its maintenance.

• Cost reduction
• Damage containment
• Lowering risk
• Organized downtime

Predictive maintenance greatly improves workplace safety, as it reduces the risk of sudden failures and accidents. This approach promotes continuous, high-quality production, ensuring maximum operational efficiency. The implementation of advanced technologies such as IoT and data analytics enables the collection of detailed information on machine performance, identifying significant trends and providing valuable information for future decisions.

The advantages for companies are significant, as predictive maintenance promotes sustainable production with lower environmental impacts and optimized maintenance costs. This approach improves company reputation, attracts new customers, and stimulates industry growth through a constant search for technological innovation to optimize industrial plant management.