Predictive maintenance
Use equipment history and sensor readings to prioritise inspections. Compare avoided downtime with missed failures and unnecessary visits.
Sector intelligence
The advantage is a more reliable operation, not another dashboard.

Practical opportunities to investigate. Results depend on your data, process and evaluation.
Use equipment history and sensor readings to prioritise inspections. Compare avoided downtime with missed failures and unnecessary visits.
Start with one repeatable defect and a labelled sample. Keep an operator able to challenge the result.
Evaluate consumption per unit of acceptable output, adjusting for product mix and production conditions.
Start where a stoppage or rejected product has a clear cost. A factory with reliable machine readings may be ready for earlier fault warnings; a workshop with scattered paper records may first need a simple maintenance log. The right starting point depends on the information already available.
Choose one machine. Compare the warnings with the maintenance team’s judgement. Count both missed faults and unnecessary inspections, alongside the time saved. Do not let a demonstration directly control equipment.

2024–2025
Catch equipment problems earlier and help a cement plant use less energy.
What happened and what to learn ↗
20 July 2016
Help cooling equipment use less energy while keeping a data centre within operating limits.
What happened and what to learn ↗Measure
Unplanned downtime, defect escape rate, energy per acceptable unit and review effort.
Watch
Rare failure examples, changing equipment and a model drifting away from real operating conditions.
Make the first move concrete
Choose a repeatable task. Record its current performance and the failures that matter. Test on a controlled sample, compare with the existing process, and decide what evidence would justify extending the trial.
Compare your opportunities Read the documented case: TITAN ↗