Predictive maintenance helps heavy equipment teams move from reactive repairs to planned service decisions based on operational data.

The problem with reactive maintenance

Breakdowns create schedule delays, emergency parts costs and lost equipment availability. Manual inspections are important, but they often miss trends that appear across runtime, location, fault and utilization data.

How AIoT supports maintenance planning

AIoT combines equipment monitoring, alerts and automated work orders. Managers can prioritize service based on risk, utilization and project impact instead of waiting for failures to occur.

Metrics to track

Track mean time between failures, service response time, downtime hours, open work orders and utilization after repair. These measures connect predictive maintenance for heavy equipment to real business outcomes.