Flag underperforming equipment and suggest repairs from live data
Thai power company GPSC, part of the PTT Group, uses Copilot Studio with Azure AI Foundry and Microsoft Fabric to watch real-time plant data, spot failing equipment and recommend repairs.
What they did
The system reads real-time operational data from equipment and flags machines that are underperforming before they fail. It maps the fault patterns it finds to ISO standards and generates repair recommendations for the maintenance team.
What happened
Microsoft says the system supports GPSC's reliability and decarbonization goals. No time or cost figures are given.
Keep in mind
This is a short vendor description with no results data, and it does not say who acts on the recommendations or how often they are right.
Try it with your agent
Here is the latest export of sensor readings for <equipment list> from <data source>, plus our maintenance manual <manual file>. Compare each machine against its normal operating range, list the ones trending toward failure with the evidence, and for each suggest likely causes and repair steps from the manual. Rank them by urgency for the maintenance planner.
Replace the <angle brackets> with your own details.