AI operations for industrial, logistics, and manufacturing teams
Case study: Custom MES for a CPG manufacturer
A manufacturing execution system built end to end for a consumer packaged goods plant: inventory, work in process, batch and lot, and work orders in one system.
01The situation
What the plant was running on
A consumer packaged goods manufacturer was running production and inventory on spreadsheets and ad-hoc trackers. As batch volume and SKU count grew, the team lost confidence in three things.
- What was on hand versus committed.
- Which batch or lot was in process.
- Whether work orders matched what the floor was actually doing.
They needed a manufacturing execution layer fit for an early plant, sized to that plant rather than to a multi-year enterprise rollout.
02What was built
A manufacturing execution system scoped to that plant
A purpose-built system for that process, rather than a generic product with unused modules.
- 01Inventory and production trackingA live view of materials, work in process, and finished goods, without spreadsheet reconciliation.
- 02Batch and lot trackingTraceability for food and CPG quality and recall readiness.
- 03Work ordersPlanned against actual production in one place.
- 04Shop-floor workflowsOperators and supervisors update status where the work happens.
- 05IntegrationsScoped connections to the tools already in the plant, so the system was not a dead end.
03Results
What the work made possible
- 01One plant systemInventory, work in process, batch and lot, and work orders in one place.
- 02Out of spreadsheetsStatus no longer assembled from spreadsheets and email.
- 03Batch and lot structureTraceability in place for quality and recall as volume grew.
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Anvil Labs LLC
AI operations for industrial, logistics, and manufacturing teams.
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