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Insights › Solution stories

Solution stories

Dairy Processing: Fat Balance, Cold Chain and Quality in One View

Reconciling milk components, not litres — from collection centres to packed products.

Trikaan Research & Engineering·10 Nov 2026·4 min read
Dairy Processing: Fat Balance, Cold Chain and Quality in One View

KEY TAKEAWAYS

  • Milk value is in fat and SNF, so reconciliation must track components, not litres.
  • Collection-centre data needed to be digital at source.
  • Chilling and cold-room temperatures needed continuous monitoring.
  • Quality results linked to routes and centres revealed sources of problems.
About this story: This is an illustrative solution story. It is a composite built from situations we commonly see in this industry, not an account of a single named customer. Figures shown as [X] are placeholders to be replaced with verified results.

A dairy processor collecting milk from village centres and producing milk, curd and ghee saw losses it could not explain.

Here is how the solution came together.

The situation

Collection centres recorded quantity, fat and SNF on paper or standalone devices. The plant reconciled litres, not components. Temperature logs were manual.

What they had already tried

  • More frequent audits of centres.
  • Manual temperature checks.
  • Monthly reconciliation in Excel.

How we diagnosed the real problem

We traced milk components from centre to products for a month.

  • Litres reconciled, but fat did not.
  • Some routes had longer chilling delays.
  • Quality failures clustered on specific centres.

The solution, product by product

No single product solved this. The value came from the products working on the same data.

ProductRole in this solution
Field app (Seed Track platform)Collection centre entries for quantity, fat, SNF and photos, offline
AnvayaProcurement, payments, stock, dispatch to distributors
ASTR ProductionComponent (fat/SNF) balance by stage and product, yields for curd and ghee
Machine Digital TwinChiller and cold-room temperature monitoring with alerts
ASTR ReportingComponent losses by route, centre and stage

How it rolled out

  • Digital capture at centres.
  • Component-based balance.
  • Temperature sensors on chillers and cold rooms.
  • Route and centre quality dashboards.

What changed

Losses were located by route and stage rather than spread across the month.

  • Fat reconciliation gap reduced by [X]%.
  • Temperature excursions alerted within minutes.
  • Quality rejections reduced by [X]%.
In practice: Reconciling fat instead of litres revealed losses that litres hid.

What we would tell a similar company

  • Reconcile components, not volume.
  • Capture at the collection point.
  • Monitor cold chain continuously.
  • Link quality to source.

Frequently asked questions

Can collection centres work offline?

Yes, with offline capture and later sync.

Does it handle farmer payments?

Procurement and payment calculations are handled in Anvaya.

Is this a real customer?

It is an illustrative composite.

  • #dairy processing software case study
  • #milk procurement app
  • #fat SNF reconciliation
  • #cold chain monitoring dairy
  • #dairy plant digital

Trikaan Research & Engineering

Trikaan

Written by the researchers and engineers who build Anvaya, ASTR and Seed Track, with input from Trikaan's delivery and engineering teams.

ON THIS PAGE

  • The situation
  • What they had already tried
  • How we diagnosed the real problem
  • The solution, product by product
  • How it rolled out
  • What changed
  • What we would tell a similar company
  • FAQ

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