Automated quality control as a right-hand tool
In the early 1900s, Frederick W. Taylor, often referred to as the father of scientific management, emphasised the importance of quality through inspection. Since then, what began as a simple focus on inspection evolved into Total Quality Management and methodologies like Lean Six Sigma. As quality principles became more deeply embedded in the organisation, the tools and techniques used to uphold them advanced in parallel, shaping the way businesses strive for excellence today.
For decades, quality control in the feed industry relied heavily on manual inspections – trained workers assessing raw materials and finished products by sight, touch, smell, spectral and chemical analysis. Yet, no matter how skilled the workers, the process remained labour-intensive and prone to human error. That’s where Automated Quality Control (AQC) comes in.
AQC leverages advanced tools to enhance and accelerate the quality control process, reducing reliance on manual checks while maintaining – if not improving – standards. While industries like automotive and pharmaceuticals have been at the forefront of automation, the feed industry is now catching up. Through innovations such as, but not limited to, real-time monitoring, IoT-enabled systems, electronic noses and hyperspectral imaging, AQC is revolutionising the way feed quality is assessed.
Prevention over detection
At the heart of AQC lies a fundamental principle: prevention over detection. Rather than simply identifying defects after they occur, AQC aims to prevent them in the first place. AI and machine learning play a crucial role in this shift, detecting patterns and even enabling mapping out potential pitfalls to help teams take proactive action.
This philosophy aligns with one of the 4 Absolutes of Quality defined by Philip B. Crosby, who stated that “the system of quality is prevention”. What was once a manual, reactive process is evolving into an intelligent, automated system – one that ensures feed quality is not just controlled but continuously optimised.
Why automated quality control is a right-hand tool
Conventional feed quality control methods have their limitations – they are labour-intensive, costly, time-consuming, and often require destructive testing. Beyond these inefficiencies, traditional methods also still leave room for human error and subjectivity.
Industry 4.0 technologies are changing the game by integrating the aforementioned techniques, eliminating the need for manual inspections. AQC systems also work at scale and operate 24/7, offering expansion and continuous product monitoring without the need for onboarding and training of new inspectors. But speed and efficiency aren’t the only benefits – automation allows for early defect detection, identifying issues at the source before they escalate. By addressing concerns immediately, manufacturers can minimise rework and prevent defective products from reaching the market. In short, AQC doesn’t just replace traditional quality control – it transforms it, making inspections faster, more reliable, and more cost-effective.
One powerful application is predictive maintenance. By leveraging sensor data and AI-driven models, equipment failures can be forecasted before they occur, allowing for optimised maintenance schedules. This not only reduces equipment stoppages but also extends equipment lifespan.
Another key advancement is inline quality measurement in the extrusion process. By integrating real-time sensor data with quality parameters of the input mixture, AI can predict optimal extrusion settings to enhance final product quality while minimising rework. This level of automation ensures consistency, reduces material waste, and optimises energy efficiency, which are key factors in maintaining high-quality production while controlling costs.
These innovations exemplify how AQC is transforming feed manufacturing, enabling smarter decision-making, greater efficiency, and improved profitability across the industry.
Overcoming challenges in automation
Adopting AQC presents several challenges. The significant upfront investment in equipment, software, and integration can be a hurdle for many companies, as well as the required skills in statistics, programming, and machine learning needed to implement it, which many companies lack in-house.
Additionally, these systems rely on vast amounts of high-quality data to function effectively – data that must be carefully collected, cleaned, and maintained. Careful human oversight remains essential as data interpretation must be handled with care. Automated systems may mistakenly flag real but extreme values as outliers, risking the loss of valuable insights.
Despite these challenges, the benefits of AQC – faster inspections, early problem detection, and objective decision-making – make it a worthwhile investment. With strategic planning and the right resources, companies can successfully integrate AQC and unlock its full potential.
Conclusion: embracing automation for a smarter future
AQC is revolutionising industries alike, offering unparalleled efficiency, accuracy, and scalability. From predictive maintenance to inline continuous quality measurements, its real-world applications are already driving tangible benefits. While challenges exist – from upfront investment to integration complexities – the long-term gains can far outweigh the hurdles. Companies that embrace AQC are not just improving quality control; they are positioning themselves for sustainable growth and industry leadership in an increasingly data-driven world.
The question is no longer if but how to implement AQC effectively. Every business has its own challenges, but the right tools can make all the difference. Explore insights and solutions to see how automation can work for you.
