Predictive Maintenance: How to Reduce Industrial Machine Downtime

For manufacturers, one hour of a stopped machine can mean losses of tens to hundreds of millions of rupiah — from delayed production and missed contracts to emergency repair costs. This is where IoT-based predictive maintenance makes the difference.

Three maintenance approaches

• Reactive — fix after failure. Cheapest upfront, most expensive when it happens.
• Preventive — scheduled maintenance. Better, but often replaces healthy parts.
• Predictive — fix just before failure, based on the machine’s real condition.

How predictive maintenance works

Sensors monitor parameters such as vibration, temperature, current, and noise in real time. Analytics detect abnormal patterns — for example, slowly rising bearing vibration — long before a human would notice. The system then sends an alert so the team acts on schedule, instead of panicking when the line goes down.

Real impact

Done well, this significantly reduces unplanned downtime, extends asset life, and cuts maintenance costs. This principle underpinned INCLUDE’s earlier product InCrane (now InAsset), which prevented potential losses of up to Rp245 million per day on port container cranes.

Start from what you have

You don’t need to replace machines. Through IncludeBox and IncludeGateways, legacy machine data is read via Modbus, MQTT, or HTTP and shown on one dashboard. For specific needs, the INCLUDE services team can build an IoT solution tailored to your process.