Food · Beverage

Equipment efficiency that holds
quality and cost at once

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Challenges on food sites

Recurring problems from intake to packaging and storage.

Refrigeration losses become cost

Air compressors, chillers, boilers and steam equipment carry most of the load, so any efficiency loss turns straight into cost and quality risk.

A stoppage costs a great deal

Hygiene standards and quality regulation are strict, so a single interruption leaves a large loss.

Energy patterns shift batch to batch

With batch production, a change in output changes the energy profile with it.

Cost, carbon and ageing arrive together

Cost pressure, carbon compliance and ageing equipment are all happening in the same period.

Representative use cases

What Refinery
actually does
on a food manufacturing site.

Chiller and compressor power and operating pattern analysis

Problem
Equipment efficiency slipping without ever surfacing
Approach
Power consumption and operating patterns are stacked to locate where efficiency bends.
Outcome
Better equipment efficiency and lower energy cost

Before and after simulation for equipment replacement

Problem
Replacement benefit that cannot be shown in numbers
Approach
Post-replacement energy use is estimated from current operating data and placed side by side.
Outcome
Investment case verified and replacement benefit quantified

Unified electricity, LNG, steam and water monitoring

Problem
Utilities tallied separately, each on its own
Approach
Electricity, LNG, steam, water and consumption by asset are connected through an ontology into one structure, so the whole plant energy flow sits on one screen.
Outcome
Usage patterns made visible by energy source

Energy intensity tied to output

Problem
Batch-to-batch variance with no baseline to compare
Approach
Production records and energy use are linked to derive intensity by batch and product automatically.
Outcome
Better cost structure and comparable process efficiency

Chiller efficiency analysis and operating optimization

Problem
Chillers running on without a reference point
Approach
Chiller COP is computed continuously so the most efficient units are run first.
Outcome
Lower cooling energy and steadier quality

Vibration-based equipment monitoring

Problem
Rotating-equipment faults that surface only after a stop
Approach
An AI agent reads anomalies in vibration trends to catch early signs, and proposes both the likely cause and the next action with the history behind it.
Outcome
Failures prevented and downtime reduced

How it fits together

How site data gains meaning and turns into a decision.

Site
  • Chillers
  • air compressors
  • boilers
  • temperature sensors
Connect
  • MES
  • SCADA
  • ERP⁠·⁠SAP
  • Modbus TCP⁠/⁠IP
  • LoRaWAN
  • 4-20mA
Refinery
  • Ontology
  • AI agent
  • rules and automation
Use
  • Equipment dashboard
  • excursion alerts
  • batch reports

Where PLC or MES already exists, Refinery sits on top of it and integrates both ways rather than replacing it. Where none exists, collection is built from the ground up.

Systems we connect to

The systems and protocols commonly used on food manufacturing sites.

MESSCADAERP · SAPModbus TCP⁠/⁠IPLoRaWAN4-20mASerialBMS

Systems not listed here can still be connected over standard protocols and APIs. Get in touch and we will walk through it.

What you gain

Benefits across operations, engineering and management.

Verified case for replacement

Before and after are set out in numbers to justify the spend.

Chiller and compressor tuning

Operating patterns are refined to save cooling energy.

Efficiency compared against output

Batches are weighed against each other to improve the cost structure.

Retracing equipment on a quality issue

Equipment state at the moment of the issue is retraced on one timeline.

Less downtime

Vibration catches faults early, preventing failures.

Let’s find the answer that fits
your food operation, together.

Request a demo