Your machines are already telling you they are going to fail.
Most plants collect condition data and still get surprised. The gap is rarely the sensor – it is that nobody mapped which failure modes matter, how much warning each one gives, or who acts on the alert.
- Failure mode and criticality analysis before any technology is selected
- P-F interval established per failure mode, so warning time is known not assumed
- Technology matched to failure mode – vibration, thermography, oil, ultrasound, motor current
- Alarm thresholds set from your own baselines, not OEM defaults
- Decision workflow defined, so an alert becomes a work order
Request a programme review
A practising reliability engineer will assess your current position and respond within one business day.
The technology is rarely the problem. The decision chain is.
Predictive maintenance fails for structural reasons, not technical ones. These six account for most of the programmes we are asked to rescue.
Technology chosen before failure modes
A vibration contract is signed, then someone asks which failure modes it actually detects. Half the critical modes on the asset list are invisible to the chosen technique.
No P-F interval, so no lead time
An alert arrives. Nobody knows whether it means six hours or six weeks. Without the P-F interval established per mode, the alert cannot be planned against and gets treated as noise.
OEM alarm thresholds on non-OEM duty
Default limits set for a reference installation, applied to plant running different loads, speeds and process conditions. The result is alarms nobody trusts.
Alerts with no owner
The data reaches a dashboard and stops. No defined route from alert to inspection to work order, and no accountability for the decision.
Baselines never established
Trending requires a known-good reference. Where none was captured at commissioning or after overhaul, every reading is interpreted in isolation.
Detection without prescription
The system flags an anomaly but recommends nothing. Detection alone shifts the burden back to an engineer who now has more data and no more time.
Strategise · Deploy · Monitor · Optimise
The same four-phase Asset Performance Management cycle we apply across every engagement, scoped here to predictive maintenance.
Strategise
Define the objectives of the APM strategy. For predictive: agree the critical assets, the failure modes that matter and the decisions the evidence must support.
Deploy
Transform strategy into systems that collect data and manage change. Technology selection, installation, baseline capture and threshold configuration.
Monitor
Use analytics to monitor performance. Trending against established baselines, with alerts routed to a named owner and a defined response.
Optimise
Analyse data to optimise performance. Review what the evidence supported, refine intervals and thresholds, and extend to the next asset tier.
How ready is your plant for predictive?
Six questions covering the areas that decide whether a predictive programme delivers or stalls. Answer honestly.
Your indicative band will appear here as you answer.
Indicative only. A programme review assesses your full critical asset list, failure mode coverage and alarm configuration against ISO 17359 and your own operating context.
Questions we get every time.
Do we need to buy new hardware?
Often not. A large share of the programmes we review already have adequate instrumentation and are failing on thresholds, coverage or ownership. We assess what you have before recommending anything.
Which technology is best?
The question is which failure modes you need to detect. Vibration, thermography, oil analysis, ultrasound and motor current each detect different things. Choosing technology before failure modes is how programmes end up blind to the failures that actually occur.
Does this replace our maintenance strategy?
No. It sits inside it. Predictive changes when and why you intervene on the assets where it is justified; it does not remove the need for a maintenance strategy grounded in RCM or FMECA.
Can you guarantee we will catch failures?
No, and be wary of anyone who does. The evidence supports investigation and planning; it does not replace engineering judgement or guarantee detection of every mode.
How long before we see value?
Threshold and ownership fixes can show within weeks. A full programme across a critical asset tier is typically a three to six month deployment before trending is meaningful.
Do you operate the programme or hand it over?
Either. Under ARaaS® we run it as a managed service. Where you prefer to own it, we build the capability and transfer it deliberately.
Stop being surprised by failures you could see coming.
Start with a review of what you already monitor and what you are missing. We will tell you honestly where predictive is justified and where it is not.