Predictive Maintenance ROI, Honestly: False Alarms, Analysis Hours and a Worked Textile Example
Why most ROI claims fall apart
Maintenance managers have heard it all: '40% less downtime', 'payback in months'. Those figures can be true on average, but an average says nothing about your plant. The claims that fall apart usually ignore three costs: the alerts that turn out to be nothing, the engineering hours spent deciding whether an alert matters, and the machines that were never going to fail in the first place.
A sound business case starts from your own stoppage history, not a vendor's headline.
Sensors are the cheap part
A wireless vibration and temperature sensor is a small line item. The real value, and the real cost, sits in what happens after the data arrives: who reviews the trend, who decides when to intervene, and how quickly a planned repair can be scheduled.
Sensors without analysis produce a dashboard nobody trusts. That is why we price monitoring as a service that includes the analysis, not as hardware.
Count the false alarms
Every alert costs time. If an engineer spends 30 minutes checking an alert and one in four alerts is real, each confirmed fault has cost two hours of investigation. Ask any supplier for the alert-to-confirmed-fault ratio in comparable plants, and track it yourself from week one.
Good systems get quieter over time: thresholds are tuned to each machine's normal behaviour during the first weeks, so nuisance alerts fall as the baseline matures.
A simple formula you can defend
Annual value = (stoppages avoided per year × cost per stoppage) − (alerts per year × hours per alert × engineer hourly cost) − annual monitoring cost.
Use your own numbers for cost per stoppage: lost output per hour × hours stopped, plus emergency repair, expedited parts, scrap and any delivery penalty. Our downtime cost calculator does the first part for you.
Worked example: a textile spinning hall
These are illustrative assumptions, not client results. A spinning hall loses about €2,000 per hour when a critical ring frame drive stops. It suffers six unplanned motor or bearing stoppages a year, each lasting eight hours: 6 × 8 × €2,000 = €96,000 a year, before repair costs.
If monitoring catches half of those early enough to fix during a planned stop, that avoids about €48,000. Subtract 120 alerts a year at 30 minutes each and €25 per engineer hour (€1,500), and the annual monitoring fee. Whether that is worth it depends on the fee and on your real stoppage history, which is exactly the point: run the numbers on your machines first.
Where predictive maintenance is not worth it
Cheap, redundant or easily swapped equipment rarely justifies monitoring. Neither do machines that almost never fail. Start with the few assets whose stoppage halts the whole line, prove value there, then decide whether to scale.
If you would like a second opinion on which machines qualify, we are happy to review your stoppage log with you before any purchase.
Stop Paying the €85,000 Breakdown
Book your free IIoT consultation with our Kastrup (Denmark) or Lahore team to see how quickly you can connect your legacy machinery.
XRPK Solutions
European Industry 4.0 solutions — IIoT, AI predictive maintenance & VR training. Kastrup, Denmark & Lahore.