Pairing Inspection Findings with Operating Data for Root-Cause Attribution
An asset owner sees an underperforming block in its SCADA data but cannot tell whether the cause is physical defect, soiling, or an inverter fault.
Run on Wayam Eye · Renewable Performance
The challenge
Operating data shows that output is down but not why, so the investigation starts with a site visit.
Inspection imagery shows physical condition but not its effect on generation.
Neither source alone resolves whether the block needs cleaning, repair, or electrical work.
How Wayam Eye solves it
Signal and Image Alignment
Inspection findings are aligned to the SCADA blocks and strings they physically sit in.
Loss Attribution
Measured underperformance is attributed across defect, soiling, and equipment causes.
Cause Isolation
Where imagery shows no physical defect, the investigation is directed to electrical equipment instead.
Action Routing
Cleaning, module repair, and inverter work are routed to the crews that handle each.
Verification Loop
Post-action generation is compared against the attribution to confirm the diagnosis.
The outcome
Underperformance attributed to a cause before a crew is dispatched.
Cleaning, repair, and electrical work routed correctly the first time.
Diagnosis verified against subsequent generation rather than assumed.
Representative scenario: a modelled industry situation showing how this accelerator applies. Figures are projections, not a named client result.
Capabilities used
Every accelerator is assembled from the same capability layer, so a workflow you adopt here shares its foundation with the rest of the portfolio.
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Bring us the version of this that you actually have.
Every engagement is fixed-scope and outcome-guaranteed. The scoping conversation starts with your systems, not with a template.