Predictive Maintenance
What Data Is Actually Needed for Predictive Maintenance?
Condition signals become useful only when connected to operating state, failure modes, maintenance actions, and verified outcomes.
A large time-series database is not automatically predictive-maintenance data. Measurements need a stable asset identity and enough context to distinguish deterioration from load, speed, product, environment, maintenance mode, or sensor change.
The most valuable label is often not “failure.” It is an inspected condition, diagnosed component, action taken, and what the equipment did afterward.
Engineering consideration
Asset and operating context
Record asset hierarchy, component, operating mode, load, speed, starts, runtime, product or duty cycle, environmental condition, and configuration version. Without context, a model may learn normal differences among modes as if they were faults.
Engineering consideration
Condition and event history
Choose vibration, current, temperature, pressure, flow, acoustic, oil, or other signals because they relate to a defined failure mechanism. Preserve raw or appropriately processed evidence at a sampling rate suitable for that signal.
Engineering consideration
Maintenance and outcome evidence
Connect inspections, findings, work performed, parts replaced, timestamps, technician notes, and post-work behavior. This closes the loop between an alert and the real equipment.
- What was observed
- What was inspected
- What was found
- What changed
- Whether the condition recovered
Questions worth answering
Before selecting the technology
- Is the failure mode observable with available signals?
- Can normal operating modes be identified?
- Are maintenance findings recorded consistently?
- Is there enough warning time to take a useful action?
The engineering decision
Predictive maintenance needs a defensible chain from asset and operating state to condition evidence, intervention, and verified result.
The correct decision depends on the operating requirement, failure consequence, available evidence, and ability to act on the result. Technology should be selected after those constraints are understood.