Maintenance and reliability
What is Predictive maintenance?
Predictive maintenance uses live machine data such as vibration, temperature and current to find developing faults and repair them before they cause a breakdown.
Quick answer
Predictive maintenance uses live data from machines, such as vibration, temperature, motor current and oil condition, to detect developing faults and schedule repairs before a breakdown. Instead of fixing machines after they fail or servicing them on a fixed calendar, the team acts when the data shows a problem is coming.
Updated 30 October 2026. Written by the Ajinkya Technologies engineering team, reviewed by Amey Kadle.
Predictive maintenance explained
Most mechanical failures announce themselves well before the machine stops. A worn bearing changes the vibration spectrum, a failing motor draws a different current, an overloaded gearbox runs hotter. Reliability engineers describe this window as the P to F interval: from the point a fault can be detected (P) to functional failure (F). Predictive maintenance aims to detect faults early in that window, so repairs fit into planned stops with the right parts ready.
It sits between two older approaches. Reactive maintenance waits for failure and pays for unplanned downtime and secondary damage. Preventive maintenance services on a schedule, which prevents some failures but replaces healthy parts and still misses faults that develop between services. Predictive maintenance does not replace preventive work entirely; it focuses effort on the assets whose failure is expensive and whose faults are detectable.
A practical programme starts with criticality: which machines stop production when they fail. Sensors or existing PLC signals are added to those first, baselines are learnt for each machine, and alerts are tuned so the maintenance planner trusts them. Alerts become work orders in the maintenance system, and outcomes are fed back so the models improve. The value comes from fewer breakdowns and shorter repairs, not from the dashboard itself.
Key concepts
- Act on condition, not on a calendar
- Vibration, temperature, current, oil, ultrasound
- P to F interval: detect early, repair planned
- Start with critical assets
- Alerts must become work orders
How to start predictive maintenance
- 1
Rank assets by criticality
List the machines whose failure stops production or costs most, and the failure modes that matter for each.
- 2
Instrument the first few
Fit vibration and temperature sensors or read existing PLC signals on three to five critical assets.
- 3
Learn baselines
Collect a few weeks of normal running so alerts compare each machine with its own behaviour.
- 4
Connect alerts to work orders
Route alerts to the planner, create work orders and record what was found so the system learns.
Questions
What is the difference between preventive and predictive maintenance?
Preventive maintenance is scheduled by time or usage. Predictive maintenance is triggered by the measured condition of the machine, so work is done when it is needed.
Which sensors are used for predictive maintenance?
Vibration and temperature sensors on bearings and gearboxes are the most common, plus motor current, pressure, flow and oil analysis depending on the asset.
Do we need machine learning for predictive maintenance?
Not to start. Trends against limits and simple rules catch many faults. Machine learning helps when there are many signals and enough history of failures.
How long before predictive maintenance pays back?
It depends on the cost of the breakdowns avoided. Programmes that start with a few critical assets usually show results within a few months of alerts being acted on.
References
How we help with predictive maintenance
We connect sensors and existing PLC data on critical assets, set limits from each machine’s own baseline, and turn alerts into work orders with QR code asset history and video SOPs for the technician.
Interactive 3D demo with simulated data: vibration rises, the alert fires, you decide.
Go deeper
Related terms
Want this measured on your own line?
Tell us your process, machines and ERP. An engineer, not a salesperson, replies within 24 hours with what we would measure first.