1. Analyse
Compressor electricity, ice-water temperatures and flow data were analysed to evaluate overall refrigeration system performance.
When meeting cooling requirements masks inefficiency
A dairy manufacturing site depended on nine ammonia compressors and an ice-water distribution network to deliver the cooling required by production. Although the system continued to meet production needs, this did not indicate whether it was delivering the required cooling efficiently or how much energy was being used to do so. By looking beyond the production outcome, the site could identify hidden inefficiencies that were increasing electricity consumption and operating costs.
Cotopaxi's energy experts identified an opportunity to improve ice-water loop control, addressing how cooling was distributed rather than changing how it was generated.
Ice-water supply temperatures were inconsistent and regularly above the 1C setpoint. This indicated that tighter loop control could reduce the energy required to deliver the same cooling requirement.
Analysis of compressor electricity consumption, ice-water temperatures and flow data showed the system was using more energy than necessary to deliver the required cooling conditions.
Compressor electricity, ice-water temperatures and flow data were analysed to evaluate overall refrigeration system performance.
Engineering analysis associated the unstable loop conditions with lower system efficiency, revealing a hidden improvement opportunity.
Pump control was refined and existing VFDs were used to stabilise pressure and temperature throughout the ice-water loop.
The system now delivers the same cooling requirement while using significantly less energy.
Meeting production targets is often mistaken for operating efficiently. In reality, industrial systems can continue delivering the required outcome while quietly consuming more energy, water and utilities than necessary. Because nothing appears to be wrong, these inefficiencies become part of normal operation. Even in well-functioning systems, opportunities often exist to achieve the same outcome with fewer resources. Combining operational data with engineering expertise helps expose these hidden performance gaps and achive improvement opportunities.