Manufacturing · An energy-intensive manufacturer, continuous process plant

Energy Intelligence & Predictive Optimization

Energy measured where it is spent

“Energy is our second largest cost and we see it once a month, on a bill.”

Context

Where it started

Consumption was metered for the whole site, never per machine, shift or product. Reduction targets were set by judgement, and a drifting asset hid inside the site total.

Action

What our team built

Equipment-level metering feeds the operational layer, with load profiled per asset and per SKU. The agent moves non-critical load off peak tariff inside limits production sets, and drift against an asset's own baseline is flagged the day it starts.

Results

What changed

TYPICAL RANGEUp to 30%

energy cost reduction

Under 3 months

typical payback

Per asset

attribution by shift and SKU

Figure drawn from published benchmarks for this pattern.

Tariff windows move and the agent moves with them, every day, with no analyst standing in the loop.

Where does your AI programme actually stand?

Ten minutes, scored across the dimensions that decide whether pilots ship. You get the score and the gap map immediately.

Related work

More from the pipeline