CanadaFood and restaurants2025 – ongoing

Maple Leaf Foods

Braincube AI models on AVEVA MES data to cut waste in bologna and hot dog production

Maple Leaf Foods reported a 10-12% gross profit rise on bologna after AI models tuned cooking and slicing

WorkingVendor case studyVendor ↗

Problem

Maple Leaf Foods wanted to lose less product to waste and moisture loss in bologna and hot dog production at a heritage plant that makes over 800 million hot dogs a year.

Approach

Braincube's AI and digital twin models analysed process data from the plant's existing AVEVA MES, such as log dimensions, oven temperatures and cook cycles, with order and SKU context. They identified ideal operating conditions, alerted operators to adjust, suggested slicer changes as small as 0.05 mm and helped set oven temperature profiles and schedules for each SKU. The project targeted eight use cases for cutting waste.

Results

10-12%rise in gross profit from waste reduction and better bologna yield, per AVEVA's customer story as repeated by FP on the NetVendor case study[1]

three monthstime to return on investment after the project was completed, per AVEVA's customer story as repeated by FP on the NetVendor case study[1]

Takeaway

The gains came from many small settings changes guided by data the plant already collected in its MES. The figures come from a vendor story.

Sources

Increasing yield and optimising operations from gate to plate
FP on the Net1 May 2025Vendor publication

Source summaries

[1]FP on the Net1 May 2025

A trade-site copy of AVEVA's customer story on Maple Leaf Foods. It describes the Braincube models on MES data and reports a 10-12% gross profit rise, return on investment within three months and eight waste-reduction use cases.

Full details are in the original sources.

Added 1 Nov 2026 · Updated 1 Nov 2026