Preventive & predictive maintenance
Logio sets preventive plans where fixed intervals are enough, and predictive monitoring where they are not.
The team starts from asset criticality and failure modes, then defines inspection intervals, condition limits, and the work‑order flow that keeps them alive in your EAM or CMMS.
Use it when unplanned downtime keeps overwriting the schedule and you need to know which assets justify sensors and models. That answer comes out of process design and data you already have, not out of more hardware.
Your challenges
What’s holding you back right now?
Unplanned downtime keeps overwriting the maintenance plan
Every asset gets the same inspection interval, whatever its risk
Condition and sensor data exist, but nobody acts on them
Work orders get closed without usable failure codes
Critical spares are missing exactly when a prediction comes true
Nobody can say whether preventive work is paying for itself
When it matters
You’ll benefit when you are…
Re‑setting inspection intervals for critical assets
Deciding which assets are worth sensors and predictive models
Moving from reactive repairs to a planned maintenance calendar
Cleaning up failure codes and work‑order discipline in EAM/CMMS
Aligning maintenance windows with production peaks
Sizing critical spares against real failure patterns
Proving the payback of preventive and predictive work
Rolling one plant’s maintenance regime out to the rest
Outcomes
What we deliver
Asset criticality map
Which assets get run‑to‑failure, fixed intervals, or condition‑based monitoring, and why.
Preventive plan per asset class
Inspection intervals, tasks, and service levels derived from failure modes, not from habit.
Predictive where data allows
Condition rules and models on the assets whose data and cost of failure justify them.
EAM and CMMS work‑order flow
Failure codes, roles, and closing discipline, so the next plan has data to learn from.
Critical spares coverage
Segmentation and targets for the parts a planned intervention actually needs.
Downtime and cost reporting
Role‑based dashboards that show whether the regime is paying for itself.
What makes us different
Logio experts at your service
Hybrid team of consultants, maintenance practitioners, and system architects.
Vendor‑independent view on sensors, EAM, and CMMS, with hands‑on delivery.
We start from failure modes and the cost of failure, not from a technology catalogue.
Proven experience in manufacturing and rail, including EAM and spare‑parts work.
Data‑driven methods and advanced analytics to target root causes.
Data and AI‑first company
Logio applies AI where it adds value, combining it with mathematics, data, and industry know‑how. On maintenance that means models built on your own failure history and condition data, and an honest answer when the data is too thin to predict anything. That philosophy underpins consulting delivery and software development at Logio.
For maintenance teams, automated BI removes manual consolidation and speeds up decision‑making. Logio routinely builds Power BI environments that standardize KPIs and put downtime, backlog, and spares coverage in one place.
Case studies
We tackled many supply chain challenges
Maintenance assessment for a Czech food manufacturer
Independent audit identified improvement potential in maintenance and produced seven prioritized projects, with emphasis on prevention, training, and efficient shutdowns.
Maintenance optimization for Z‑Group Steel
Logio helped Železárny Hrádek redesign its maintenance strategy, organisation and processes, which improved the balance of preventive and corrective maintenance, shortened repairs and reduced production downtime.
Keep assets reliable, safe, and cost‑effective
If your maintenance is reactive, fragmented, or held back by data silos, Logio can design a strategy and plan that delivers uptime and control. Let’s discuss your targets and the fastest way to get there.