Maple Leaf Foods
Maple Leaf Foods increases its production yield with AVEVA MES
Maple Leaf Foods, Canada's largest producer of prepared meats and poultry, wanted to identify the ideal operating conditions for its bologna product in order to ensure consistency, improve yield and reduce waste. The company sought to leverage IoT and AI technologies to drive operational excellence at a legacy site, as part of its sustainability commitment. Deploying AVEVA Manufacturing Execution System, coupled with advanced artificial intelligence models from Braincube, enabled detailed, near-real-time data analysis directly on the production floor. Maple Leaf Foods took advantage of its existing AVEVA MES and SCADA systems by adding this new analytics layer on top. The benefits are significant: a 10 to 12% increase in gross profit thanks to reduced waste and improved bologna production yield, and a return on investment achieved in just three months. The company thus strengthens its position as a committed leader in food industry sustainability in Canada.
FAQ
How does AVEVA MES improve yield in a long-established food production operation?
Maple Leaf Foods, Canada's leading producer of prepared meats, deployed AVEVA Manufacturing Execution System to identify the ideal operating conditions for its bologna product. Combined with Braincube AI models layered on its existing MES and SCADA systems, the manufacturer now runs near real-time analysis directly on the shop floor. This approach generated a 10 to 12% increase in gross profit through waste reduction and improved yield, with ROI achieved in just three months.
How can AI be integrated with existing AVEVA MES and SCADA systems?
Rather than replacing its infrastructure, Maple Leaf Foods built on its existing AVEVA MES and SCADA by adding a Braincube AI analytics layer. This incremental approach considerably reduces the cost and risk of an industrial AI project. Contextualized data from AVEVA MES feeds the models, which deliver recommendations directly to operators. It is a particularly relevant digital transformation model for legacy food sites looking to modernize without disrupting operations.
Why make data analysis available to operators on the shop floor?
At Maple Leaf Foods, AVEVA MES allows operators on the bologna line to see optimal production conditions in near real time directly at their workstations. This autonomy speeds up response to quality drifts, reduces scrap and makes yields more reliable. Analysis is no longer reserved for data experts: it becomes an everyday operational tool. This democratization of data is a major lever for operational excellence in high-throughput food industries.
What ROI can be expected from an MES project in the food industry?
The AVEVA MES project deployed at Maple Leaf Foods paid for itself in just three months, with a 10–12% increase in gross profit on bologna production. The savings come from reduced waste, improved material yield and stabilized process parameters. For an industry where margins are often tight, such a fast return demonstrates the value of combining MES and AI for high-volume products and complex processes.
How does AVEVA contribute to sustainability in the food industry?
The waste reduction and yield improvements made possible by AVEVA MES directly support the sustainability strategy of Maple Leaf Foods, a committed leader on this issue in Canada. Less product thrown away, less energy wasted per unit produced and optimal use of raw materials all help lower the site's environmental footprint. Industrial performance and sustainability are not in conflict: they reinforce each other through data-driven digital transformation.