The feed industry has spent decades automating its mills, but the dream of a plant that can largely run itself remains elusive. Technology is no longer necessarily the obstacle: robots can handle physical tasks, digital twins can model production, and predictive maintenance can flag equipment failures before they happen. The harder question is whether the investment delivers enough value to justify replacing people.
The barriers to deeper automation are often complex, extending beyond the availability of individual technologies to the challenge of integrating them into a single, reliable system.
"Brownfield mills often combine machinery from different suppliers and generations, with incompatible protocols and isolated data systems," commented Gero Zimmermann, Senior Technologist, Animal Nutrition, Bühler Group. "Integrating these assets into one reliable automation and optimization platform is technically complex."
Unlike dairy or beverage processing lines, which are often supplied by a single OEM, food and feed processing lines typically comprise equipment from multiple manufacturers, added Tran Long, Industry Consultant - Food and Beverage, Southeast Asia, Rockwell Automation.
"This creates significant integration challenges, as customers may struggle to identify a system integrator with the capability to unify the entire operation while maintaining production reliability, efficiency and cybersecurity."
In addition to difficulties in working with old infrastructure, Zimmermann noted, many key quality parameters still depend on manual sampling or delayed laboratory results. Existing sensors may also be poorly calibrated, unreliable, or lack sufficient process context — which limits effective closed-loop control.
The barrier to deeper feed mills automation is less about technology itself and more about strategy and proof of value, commented Cristian Soto, Global Industry Developer Ingredients at Siemens.
"Most feed mills already run pilot projects, think of sensors or a predictive- maintenance trial, but few have a company-wide digitalization roadmap," Soto said. "On the economic side, operators struggle to quantify ROI before committing capital, especially with rising cost pressure.
On the technical side, legacy infrastructure is an important constraint, Soto agreed, adding that other factors include difficulties integrating data across old and new systems and a skills gap in operational software expertise.
On top of that, automation is hampered by reluctance to adopt cloud-based data platforms.
"Many customers continue to prefer on-premises platforms because of concerns about data security and potential leakage," Long said. "We address these concerns by explaining the security principles and safeguards underpinning cloud services and by working with leading providers such as Microsoft Azure.
In general, Long said, customers with a stronger understanding of cloud technologies and AI are generally more receptive to cloud-based platforms and better positioned to use the full capabilities of industrial AI applications.
Where automation pays off
For feed mills, the question is not simply what can be automated, but what is worth automating. Some technologies can quickly deliver savings through lower labor requirements, improved efficiency, or reduced downtime, while others remain difficult to justify because of high upfront costs and long payback periods.
According to Bühler, the clearest return on investment is achieved where automation optimizes throughput, yield, and energy consumption in real time while maintaining consistent product quality despite variability in raw materials.
"Since raw materials represent 70% to 85% of production costs, even marginal improvements in yield or formulation accuracy can have a significant financial impact and deliver a rapid return on investment," Zimmermann said. "By contrast, automation can be harder to justify in applications where process variability is low, and the potential savings are limited."
Siemens team believes that predictive maintenance and energy management remain the clearest, fastest-to-prove returns.
"In feed and grain processing specifically, digitalized batching and plant-wide data integration tend to show up as fewer dosing errors, tighter energy management, and less unplanned downtime," Soto said.
Moreover, he added, when feed mills are integrated as a direct part of the food industry supply chain, production optimization becomes a critical area for measurable impact.
"Digital technologies enable real-time process adjustments and data-driven decision-making, leading to increased productivity and throughput across feed mill operations," Soto said.
Digital and AI-driven technologies are already creating value across a wide range of plant operations, Long said. This includes production efficiency, process optimization, energy management, production logistics, maintenance management and predictive maintenance.
A successful feed mill automation project requires establishing proof of value by agreeing with the customer on measurable ROI criteria and validating them against the customer's operational data.
"This evidence provides a strong basis for investment approval," Long added.
However, there are still areas where automation remains difficult to justify.
According to Long, this involves tasks requiring specialized skills or judgment. He explained that certain inspection and quality-control activities in food and feed processing still depend heavily on experienced operators. Customers typically require a comprehensive demonstration or prototype, validated over an extended period, before committing to automation or digitalization.
In addition, automation can not be equally important for all markets. Where labor remains cheap, this naturally constrains feed mill owners' interest in equipment automation.
"If automation is evaluated solely as a replacement for manual labor, the payback period may be too long to justify the investment," Long said. "The business case becomes stronger when automation also enables higher capacity, more consistent quality, improved safety, greater production flexibility or line-wide data visibility."
How to make it work
Despite the extensive challenges, technology providers argue that automation is within reach for most feed mills. The key is to approach it as a gradual, carefully planned process rather than an all-or-nothing investment. By identifying the areas where automation can deliver the greatest operational gains, integrating technologies step by step and taking account of the mill's existing infrastructure, operators can overcome many of the technical and economic barriers.
"We don't see full automation as something reserved for new-built plants," Soto said. "Modern IIoT platforms can connect to legacy and mixed-vendor equipment without reconfiguring existing controls, and retrofitted sensors plus a digital twin let operators plan upgrades and validate them virtually before touching the physical line."
Among other things, he said, such an approach minimizes downtime during integration.
Soto added that software-defined automation also helps mills handle the variability of raw materials, since control logic can adapt in real time rather than being hard-wired to fixed parameters.
"That said, new-built plants do have an advantage in speed and cost: designing and validating a facility digitally before it's built avoids retrofitting altogether," he said.
Long also noted that Rockwell's recent project with a leading aquafeed manufacturer in Vietnam illustrates how some of these common barriers can be overcome. He revealed that the project brought existing and newly expanded production lines under a common control and data architecture, giving the manufacturer end-to-end visibility of production and batch-level energy use. By integrating process and utilities control within a single system, the approach also helped limit the additional investment required for the expansion.
Bühler believes the potential for further automation remains vast, given the wide range of technologies now available to feed mills — even if fully automated plants are not yet a realistic target for most operators.
"While newly built plants offer the most direct path to full autonomy, existing feed mills can also make significant progress through phased upgrades, starting with critical sensors, controls, data integration, and high-value process areas," Zimmermann said.
In general, technology providers believe that the near- to medium-term future of feed mill automation, then, may not be a plant without people, but a plant where technology takes over the tasks where it can create the most value.
