Riyadh, energy

Energy programmes in Riyadh are run from headquarters, delivered in the field

Head office wants a portfolio view. The plant wants a work order that makes sense. The two only meet when asset data, sensor history and maintenance records describe the same equipment.

An asset register that matches reality is the whole project.
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Key takeaways

What you need to know, in a minute

  1. 01

    One asset hierarchy

    Tags, equipment records and maintenance history aligned so a failure can be counted once.

  2. 02

    The operational network stays separated

    Sensor data crosses into the analytics layer through a controlled path, and the boundary is documented.

  3. 03

    Alerts arrive as work

    A prediction that does not become a scheduled work order with parts attached changes nothing.

Maintenance

Failure prediction on critical equipment

Models trained on the plant's own sensor and failure history, with the false alarm rate reported honestly.
Utilities

Consumption and loss analysis

Metering, billing and network data reconciled so the loss figure survives a challenge.
Supply

Procurement and spare parts

Spend and stock read together, so a critical part is not ordered late and a slow part is not ordered twice.
Use cases

Where this applies in practice

What usually stalls these programmes

Tag names that differ per system

Mapping is unglamorous and it is where the value is. We do it before modelling.

Sensor history too short

We say so early and start with condition rules while the history builds.

No route from alert to technician

The integration into the maintenance system is part of the first release, not a later phase.

Energy and utilities in Riyadh, questions we get

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