Food processing organisations hoping to make the most of the recent automation trend must start by recognising ideal use cases. One of robotics’ greatest strengths is its precision. Accuracy and repeatability, in turn, are most impactful in some of the industry’s more challenging workflows. As such, the best food processing robot applications use this technology to address the sector’s most significant pain points. By Emily Newton, Editor in Chief, revolutionized.com
Meat processing
Ingredient preparation is an ideal use case for automation, given its repetitive nature and demand for precision. Within this area, meat processing is uniquely suited for robots, as manual approaches are potentially dangerous and introduce cross-contamination risks.
Roughly 600 million people worldwide fall ill after consuming contaminated food each year. Reducing it at the source is key to addressing these illnesses, and food processing robots make a considerable difference here. Because robotic equipment never leaves the facility, it never introduces outside contaminants, and coated metal surfaces can be both microbe-resistant and easy to sanitise.
Deboning and cutting workflows may also require knife work. Consequently, they are a major hazard to human employees, but automation removes safety concerns by distancing them from cutting edges. Robots also do not get tired or distracted, so they can cut and prepare meat with the same precision with each pass, even after hours of non-stop work.
Quality control
Quality inspections are another optimal automation candidate. Manual inspections create bottlenecks, as humans cannot thoroughly judge an ingredient or product’s quality as fast as machines can process it. Artificial intelligence (AI), however, can.
AI-guided robots can look for defects or signs of food safety concerns as quickly as products come down the conveyor belt. Because the robot will compare each item to the same reference data, it will also provide the same level of accuracy with each one. This combination of reliability and speed is an unmissable advantage.
Manual quality control can be fast or detailed, but not both. Machine vision does not sacrifice one for the other, allowing food manufacturers to increase output without raising customer safety risks.
Packaging and palletisation
In addition to being repetitive, packaging is often wasteful, and robots address both concerns. Purpose-built robots can fold boxes, wrap meats, place ingredients in containers and fill bottles faster than humanly possible. Machine vision functionality enhances such benefits by helping these machines adapt to slight variations, avoiding missteps that may affect product quality or safety. The same advantages extend to palletisation, where robots can load boxes on pallets quickly and accurately.
Automation’s precision can improve packaging sustainability, too. A worrying 83% of plastic waste in the U.K. comes from food and beverage packaging, signifying a need for change. Because robots can act more precisely, they can wrap products while using less material, preserving quality while reducing plastic consumption and ultimately minimising waste.
Warehouse operations
Similarly, robots can optimise food and beverage companies’ warehouse operations. While production may be the most obvious candidate for efficiency and safety improvements, logistics is responsible for considerable waste and time losses. Picking, sorting and loading workflows are also ideal automation use cases.
Manual picking is remarkably inefficient, and any inefficiencies in the food industry can lead to safety concerns if working with limited shelf lives. Consequently, using automated material handlers and picking robots instead leads to far-reaching positive ripple effects. Doing so can also minimise repetitive strain injuries among the workforce.
Some facilities have implemented robotic arms to load lorries more efficiently. AI algorithms can analyse a shipment to determine the best way to stack boxes for safety and space efficiency, while the automated motion reduces manual labour.
Facility maintenance
Food processing automation can improve a factory’s indirect workflows. Like food and beverage manufacturing itself, maintenance is highly repetitive, prone to error and time-consuming. A difference of just a few seconds can create bottlenecks, too, raising the need for optimal maintenance. Automation is the ideal solution.
AI models can analyse equipment performance data in real time to spot early signs of wear. They can then alert maintenance personnel to the issue so they can schedule repairs before larger, more disruptive breakdowns occur. As a result, downtime decreases while machines stay in top condition for longer periods, as automation detects issues before they’re noticeable to humans.
While software automation like this may not be what comes to mind first for many food and beverage brands, the benefits are impossible to ignore. Such optimisation becomes increasingly advantageous the more automated equipment a facility deploys, too.
Food processing automation best practices
Recognising these optimal use cases is just the first step in effective food processing automation adoption. Businesses must also plan to address several common obstacles to this technology.
Financial concerns like high upfront costs and a lack of funding access remain a leading barrier to technology adoption in the U.K. While robotics typically reduces long-term expenses, the upfront investment is often significant. One solution is to start by automating the one process with the greatest need for optimisation. That way, facilities will see a positive return in less time, enabling further expansion.
Training and development are also critical. Any amount of automation will result in a new workflow employees must learn. Large-scale robotics adoption may make some roles obsolete while opening demand for new ones, necessitating upskilling. Consequently, manufacturers must determine how these factors will change at their facility and retrain workers as necessary.
Fifty-eight percent of global entities cite cybersecurity concerns over robotics. Connected equipment poses a particular risk, as it increases potential entry points for attackers. As such, food and beverage companies must improve their security posture before implementing any new machines.
Best security practices include network segmentation, encrypting data transmissions between equipment, using multi-factor authentication on all endpoints and deploying automated network monitoring software. Employee cybersecurity training and regular penetration testing will also help.
Finally, food and beverage producers must embrace ongoing improvements. Robots and their workflows will likely need adjustment over time to reach their full potential. Regular review and monitoring of key performance indicators is crucial to long-term success.
Food processing robots are more versatile than ever
Food processing automation has reached new heights. Robotic equipment can serve more roles than ever and do so with greater results. However, manufacturers must understand where these benefits stem from to capitalise on them.
Education is the first step toward automation optimisation. The more food and beverage organisations know about robots and how to use them, the better they can deploy this technology.
