Maintenance Management

Predictive Maintenance and Digital Twin Technologies

Condition monitoring programmes usually collect more data than anybody acts on, and the gap is rarely the sensors: it is that nobody defined what reading would trigger which decision. This course closes that gap. Delegates work through failure modes and which ones actually give warning, selecting monitoring techniques to match, and vibration, thermography, oil analysis and ultrasound on what each detects. Alarm limits and setting them from equipment history follow. Data collection, storage and the analysis that turns readings into a remaining life estimate are covered. Digital twins are addressed honestly: what a model can predict, what it needs to be fed, and where the value is real. Integrating findings into the maintenance plan and the work order system is covered. The course closes on proving the programme paid for itself and on sustaining it once the initial enthusiasm passes.