# Predictive maintenance

> To optimise asset maintenance, start with the list of critical assets, where a failure stops the service or costs a lot. For those, collect the data you already have (BMS, meters, maintenance software history), set thresholds, then use models that read trends over time. Every alert becomes a work order. Low-criticality assets stay on calendar or run-to-failure maintenance.

Most buildings are maintained in one of two ways: on a calendar, even when nothing is needed, or after a failure, when it costs most. With the data the building already produces you can see a problem as it starts and decide when to act. We help you choose the right assets, connect the data and turn alerts into work orders.

## The four strategies

Corrective: after the failure. Preventive: at fixed intervals. Condition-based: when a measurement crosses a threshold. Predictive: when data trends point to an approaching failure (EN 13306).

## Assets where it pays

Yes: air handling units, pumps and motors, chillers and heat pumps. It depends: switchboards, lifts. Usually not: lighting, windows, finishes.

## The five steps

1. Critical assets. 2. Data check. 3. One code per asset. 4. Thresholds, then models. 5. From alert to work order.

## FAQ

**How can I optimise the maintenance of my assets?**

Start with critical assets, where a failure stops the service or costs a lot. For those, use the data you already have, BMS, meters and maintenance history, first with simple thresholds and then with trend models. Every alert becomes a work order. Everything else stays on calendar maintenance.

**What is the difference between preventive and predictive maintenance?**

Preventive maintenance acts at fixed intervals, whether the asset needs it or not. Predictive maintenance acts when the data shows a failure is approaching. The first is easy to plan; the second avoids unnecessary work and catches failures that happen between two intervals.

**What data does predictive maintenance need?**

BMS trends, consumption from meters, the history of failures and work orders from the maintenance software and, where needed, vibration or temperature sensors. All of it must use the same code for each asset, otherwise the data does not connect.

**Do you need a digital twin for predictive maintenance?**

No, you can start from BMS and maintenance data. A digital twin helps when there are many assets: it shows where each asset is, what it serves and which documents relate to it, so the crew arrives with the right information.

**How much does predictive maintenance save?**

It depends on the assets and on what failures and calendar work cost you today. That is why we start from your data: the calculator on the site gives a first estimate, then we check it together on a group of assets before extending the work.

URL: https://bimon.it/en/predictive-maintenance