AI-powered Data Management System for Sustainable Food Production unlocking better yield, lower waste, and reliable decision-making

This hands-on partnership ensured the system addressed real-world needs: from reducing food waste and unnecessary costs to improving product quality — all in the context of high-volume, variable-output manufacturing environments.

The system goes beyond performance optimization. It captures the valuable expertise of seasoned operators, preserving it digitally to support less experienced staff and protect process consistency as workforce dynamics evolve.

This innovation is both practical and scalable, helping food companies future-proof their operations amid increasing challenges such as:

• Labor shortages
• Rising production costs
• Growing pressure for sustainability and zero-waste practices

With the support of the HighFive program, the company have taken a major leap forward with the FOBIS® software platform. It is now a smarter, more intuitive AI-powered data management system that integrates seamlessly with factory equipment. Through a real-time feedback loop, the system empowers operators and managers to act instantly on live data — enabling faster decisions, lower waste, and a calmer, more controlled production environment.

Modernizing Food Production: Challenges and the Case for Smarter Systems

Food producers across Europe are under increasing pressure. They must operate more efficiently using fewer resources, minimize waste, and navigate a labor market where experienced staff are becoming scarce.

Yet, many companies still depend on traditional analysis methods — primarily backward-looking reporting that fails to support real-time decision-making. This reactive approach often results in overfilling, unnecessary waste, energy inefficiencies, and inconsistencies in product quality.

A particularly illustrative example is found in the meat processing and sausage production industry. In these environments, precision and timing are critical. For instance, the exact ratio of fat to lean meat in sausages must be carefully monitored to ensure compliance with product specifications, customer expectations, and food safety regulations. Traditional manual sampling and delayed lab analyses make it difficult to catch deviations in real time. This can lead to entire batches being scrapped or reworked — both costly outcomes.

Furthermore, production lines are highly automated but still require nuanced human oversight — especially when adapting recipes, switching batches, or addressing equipment anomalies. As older, skilled staff retire, and new workers enter the field with less hands-on experience, a lack of smart management information systems creates serious challenges. Without embedded operational intelligence, tacit knowledge is lost. Operators struggle to make fast, confident decisions, increasing the risk of human error, equipment downtime, and ultimately, reduced profitability.

To remain competitive, meat producers must adopt predictive, real-time analytics that support line operators and managers with actionable insights — from detecting material losses and process deviations, to ensuring quality consistency and optimizing yield.

Smart, Practical AI for the Realities of Food Production

RBK Group has integrated real-time artificial intelligence and predictive analytics into its FOBIS® platform — a trusted ERP and MES solution widely used in the food industry. Our latest innovation goes beyond the dashboard buzzwords: it offers direct, actionable insights where they matter most — on the factory floor.

Imagine dynamic dashboards and traffic light-style signals that clearly show operators when to adjust processes, intervene, or stay the course. But what sets this system apart is not just the technology — it's the fact that it was specifically developed and tested on a real production line, including one of the most challenging stages: the drying process in meat and sausage production.

This stage is critical for product quality, yield, and shelf life, yet it often suffers from variability due to manual decision-making and fluctuating environmental conditions. Traditional systems simply can't respond quickly enough. Our smart platform does — detecting patterns and trends in real time and guiding staff to act at the right moment.

The system has already proven its value, enabling:

• 2% reduction in overfilling
• 5% shorter drying times
• Maximized yield from raw materials

More importantly, it embeds the tacit knowledge of experienced operators into the digital core of the plant. This helps less experienced staff perform with greater confidence and consistency, reducing the learning curve and minimizing costly mistakes.

Impact

The outcome of this innovation project will meet – and in many ways even exceed – our original expectations. It will not only solve key operational challenges, but also set a new standard for efficiency and agility in food production.By easing reliance on scarce, highly skilled workers, the solution enhances workforce flexibility and resilience. At the same time, it significantly reduces waste and product throwaway, supporting both economic and environmental goals.

The solution redefines production by introducing smarter, more responsive systems that improve agility, insight, and efficiency. The measurable benefits include:

• 2% reduction in weight overfill
• 5% decrease in drying time
• 2% reduction in raw material waste
• 2% reduction in product giveaways
• 2% decrease in rework and reprocessing
• Additional project-specific improvements based on implementation scope

This project demonstrates the transformative potential of innovation when grounded in deep industry understanding and a commitment to practical, scalable impact. This project has already shown that success depends heavily on people. In today’s tight labor market, attracting the right talent is a growing challenge. To address this, we have made structural improvements in how we recruit and plan to scale development capacity. Along the way, we have deepened our understanding of the complexities in food production.

The solution we are developing aims to reduce reliance on scarce, highly skilled labor by embedding expertise into systems. For Zwanenberg, this is expected to bring several benefits: decoupling skill from manual labor, reducing product give away, and cutting down waste through better process control.

We also anticipate shortening drying time, which would boost throughput and scheduling flexibility. These improvements are designed not only to enhance efficiency but also to support sustainability by minimizing energy use and material loss.

Ultimately, the project is positioned to deliver both operational gains and a strong foundation for long-term resilience in a rapidly evolving industry landscape.

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