In many manufacturing companies, the maintenance department still operates in a constant state of emergency.

When a machine stops, a race against time begins to repair it, causing delays and inefficiencies in production. Implementing IoT predictive maintenance can transform this scenario.

Why is maintenance always in emergency mode?

Even when a preventive plan exists, it is often ineffective for several reasons:

• Rigid interventions – based on fixed intervals rather than real machine data.
• Premature or delayed maintenance – some tasks are performed too early, others only after a breakdown, causing machine downtime.
• Lack of real-time monitoring – managers have to rely on verbal reports or retrospective reports.

In many industrial environments, maintenance remains reactive, costly, and slows down production processes. To overcome this challenge, many companies ask themselves how to move from reactive to proactive IoT predictive maintenance.

How to transform maintenance from reactive to proactive?

To overcome the limitations of traditional maintenance, the company adopted the Zerynth Copilot Platform, an IoT predictive maintenance solution that enables:

• Intelligent machine monitoring
  Thanks to connected sensors, the platform collects real-time data on working hours, alarms, prolonged standbys, and low-quality production cycles, allowing machinery predictive maintenance to be based on concrete evidence rather than fixed intervals.
• Personalized maintenance plans
  Each asset can have a tailored plan: the platform sends automatic notifications when a threshold is reached or an anomaly occurs, while operators log activities in the machine diary, making industrial machine maintenance more efficient and transparent.
• AI support
  The AI agent Zero provides predictive notifications and operational suggestions, for example:

“Machine 4 is exceeding the optimal range: intervention recommended within 8 hours.”

All documentation and intervention history are centralized in a single digital interface, eliminating the need for Excel or paper forms.

In short, a production monitoring platform like Zerynth Copilot makes IoT predictive maintenance a collaborative, data-driven, and continuously optimized process.

How does the Maintenance module work?

The Maintenance module of the Zerynth platform makes IoT predictive maintenance simple and collaborative. It allows you to:

• Create personalized IoT predictive maintenance plans
• Set operational goals
• Involve line operators
• Ensure immediate updates

Tangible results

By adopting the Zerynth Copilot Platform, the company achieved measurable benefits:

From “repair after breakdown” to “intervene before”: a true cultural shift in IoT predictive maintenance.

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