Predictive maintenance uses IoT data to facilitate actionable insights and advanced analytics to help organisations predict equipment failure. In doing so, it enables organisations to drive an increase in operational efficiency and reduce maintenance costs.
Traditionally, organisations have followed preventative maintenance techniques, which mitigated equipment risk through regular scheduled maintenance. This relies on a predetermined maintenance schedule; the schedule being determined by the forecast overall use and normal wear and tear of the asset.
In contrast, predictive maintenance utilising sensors to help determine the condition of any part or piece of equipment, predict breakdowns and pinpoint the most cost effective time for maintenance without losing throughput. In simple terms, it tries to predict failure before it occurs using continuous observations and health-checks.