Warehouse racking: find the damage before the collapse
Racking is hit constantly and inspected occasionally. Measure in the gaps between inspections, where nobody is looking.
Slow, silent and found too late
A forklift catches an upright at walking pace. Nobody reports it, because nothing visibly happened, and the next knock lands on a leg that is already weakened. The damage builds up between manual inspections.
- The damage is slow and silent. Repeated low-speed knocks weaken a rack without leaving a mark anyone would notice on a walk-round.
- It is found too late. By the time damage is visible, you are looking at repairs and downtime, and in the worst case a collapse.
- The data is locked away. Where monitoring exists, it often lives in a dashboard of its own rather than in the WMS or ERP the team actually uses.
Square Impact on the rack leg
Square Impact is the rugged Square Xtreme hardware running the Impact VSM app. It mounts on the rack leg and reports impact, vibration, tilt and temperature. Because it is the same hardware as Square Tracker Xtreme, a site that already tracks assets is not buying a new fleet, and a sensor can be given a new job later with a downloadable VSM app, without replacing anything.
- Detection: 3-axis accelerometer for shocks, hits and abnormal vibration
- Battery: 4,000 mAh, event-driven, well over ten years, fitted once with no swap cycle
- Range: LoRaWAN up to 2 km, so one gateway covers a site rather than a hub per aisle
- Environment: IP68 and IK06: waterproof, dustproof, impact-resistant
- Location: Wi-Fi scanning pins each impact to a place, in a building with no GPS
- Set-up: NFC, by tapping with an Android phone
Vibration is the part that predicts
An impact alarm tells you a rack was hit. That is useful, and it is the less interesting half.
The sensor also runs an FFT and reports vibration energy in nine bands from 1 to 256 Hz. Wear and looseness change that signature before anything fails, so a rack can be taken out of service on evidence rather than after an incident. Each band arrives as its own field in Yggio, to chart, threshold and trend like any other reading.
This is where a rack that is quietly deteriorating separates from one that was knocked once. A single hit is an event. A drifting signature is a condition.
Into the systems people already have open
People act inside the systems they already use; rack health in a dashboard of its own gets checked when someone remembers. In Yggio each sensor is an ordinary device on one standardised interface, so the data goes where the work is, with access rights per site or per contractor, dashboards per role and reports on a schedule.
- Operations: WMS, ERP and facility systems over the open API or MQTT
- Reporting: Grafana and Power BI through the same interface
- Action: the Rule Engine decides what an impact above a threshold triggers: a work order, a message to the shift lead, an escalation if nobody acknowledges
What matters at fleet scale
- One gateway per site rather than per aisle, placed where a network outlet already exists.
- Battery and link health tracked for every sensor, so a silent sensor is raised as a fault rather than mistaken for a rack that has not been hit.
- One naming hierarchy across sites, so an impact is reported as an aisle and a bay rather than a device identifier.
- The data stays yours, on open FIWARE data models, in the cloud, at the edge or on premises.
Low risk, and fast to a first result
Confirm during the pilot that one gateway really covers the site, and that an impact reaches the shift lead in the system they already have open. Then extend on the vibration trends after a full quarter: impacts justify the sensors, the drifting signatures make the programme predictive. The full use case in Sensative Docs.
- Scope it in a conversation. An hour is usually enough to find where the damage is, what the repair history says and which systems the data must reach.
- Pilot one site and one set of aisles, the ones with the repair history, delivered into your live WMS rather than a dashboard of its own.
- Scale across the remaining aisles and sites, on the same platform, naming and data model.