The food industry has been relatively slow to adopt what industry insiders call “Industry 4.0,” the fourth revolution in manufacturing. Central to this “revolution,” according to Forbes magazine, are autonomous systems driven by data and machine learning, or the “digitization of manufacturing.” While some level of automation technology in the food industry is the norm, it’s typically limited to specific processing steps such as washing, sorting, and packing.
In other factories, however, automation takes on another meaning and uses more advanced technologies, such as the Internet of Things (IoT), to connect equipment and devices, smart sensors to collect real-time data, and 3D vision and artificial intelligence (AI) to execute complicated tasks.
One reason for this delay in adoption in the food industry is an element of fragmentation within food processing. “While in other sectors you can connect various devices together and collect data, in the food industry there is a lot of standalone equipment,” says Craig Salvalaggio, COO at Applied Manufacturing Technologies, an automation engineering company based in Anaheim, Calif., and member of the board of directors for the Association for Advancing Automation. “It’s like having little islands connected by conveyors.”
Before buying any [automation] equipment, companies should understand their current process, data, and metrics, and where they want to go from there—whether it’s increasing capacity, demand, or flexibility. You can learn a lot from visiting factories in other industries, such as automotive or aerospace.—Craig Salvalaggio
Another reason for the food industry’s slow adoption of Industry 4.0 comes from the complexity of certain operations: “In the meat sector, for instance, some companies believe they’re able to realize higher yield by having more skilled labor and personnel,” says Lee Coffey, market development manager for the CPG segment at Milwaukee, Wisc.-based Rockwell Automation.
The Impact of COVID-19
Part of this gap was recovered during the COVID-19 pandemic, when the adoption of Industry 4.0 solutions was accelerated by new challenges, such as the rise of online grocery shopping: “E-commerce created new opportunities throughout the industry,” says Coffey. “Anywhere from beverage manufacturers to meat processors, companies can reach new customers and markets, but they’re also producing more SKUs than ever. There are more changeovers and more ingredients being used, and that’s adding complexity and downward pressure on productivity and profits.” Workforce shortages is another factor that has become problematic during the pandemic “With workers not showing up and COVID-19 restrictions, companies have been struggling with scheduling production and meeting demands, especially in those labor-intensive areas where you have to handle the product and get it into a tray and then into a box,” he adds.
Key Automation Technology
With these new challenges, some key technologies are proving to be particularly sound solutions. Manufacturing execution systems (MES) are one such solution; they keep track of all food processing data, from raw materials to finished products, and have existed in the food industry for a long time. Recently, however, the approach to these systems is different, says Gerardo Villafuerte, digitalization manager for North America at Liquid Consulting, a Sanford, Fla.-based firm that provides engineering and automation solutions to food manufacturers. “You used to have reports with all kinds of variables and data; now, companies are looking for data that matters to them. It’s no longer about just the technology but also about how it can be applied to have safer processes around products.”
Having the right data is crucial in the case of a product recall: “If a contamination is detected,” says Villafuerte, “you can use your MES and [enterprise resource planning] ERP systems to find out exactly where that lot was produced, where it was shipped, what instruments and ingredients were used to produce it, and how long the ingredients were stored before being processed.”
At the same time, the Industrial Internet of Things (IIoT) can help food companies improve overall equipment effectiveness (OEE), one of the most important metrics in manufacturing plants. “IIoT is a big enabler right now,” says Coffey. “A lot of our customers are deploying it to connect people, processes, and assets throughout the plant and aggregate real-time data to make better decisions on the fly, versus going through data collected manually at the end of the shift. Data can be anything from the temperature of the product to vibration analysis of how a machine is running. It’s an evolution where companies are going from a reactive approach to predictive models that allow them to see when a failure is coming and check the machine in advance.”
A third area where Industry 4.0 can make a difference is the automation of tasks that require a high level of manual dexterity. “Robot end-of-arm tools for grasping can now pick fragile and irregular objects without damaging or marking them,” says Salvalaggio. “For example, we worked with a manufacturer to automate the process of putting pickles in jars. Using a combination of AI, grasping, and vision technology, we designed an application to identify the size and the structure of the pickles and select an optimal pick sequence. We demonstrated that we could get about 70% of the pickles into the jar reliably, with human intervention helping with the remaining 30%.”
Plan for Success
While automation can provide great benefits, it requires proper planning. Villafuerte says it’s important to have a flexible master plan with clear objectives and a timeline so you can organize your investments step by step. “Automation is a journey: You want to first crawl, then walk, and then run,” says Salvalaggio. “Before buying any equipment, companies should understand their current process, data, and metrics, and where they want to go from there, whether it’s increasing capacity, demand, or flexibility. You can learn a lot from visiting factories in other industries, such as automotive or aerospace.”
The plan should always be for the long term, even if you cannot implement everything at once. “It’s likely that you’re not going to have the funding for everything right away,” says Coffey. “The best thing is to prioritize the most critical projects and then identify low-risk, high-yield targets where you can get a couple of quick wins.”
Not having a plan in place might save some time at first but will likely cause issues down the line. “One of the main problems,” says Villafuerte, “is when companies see automation as a one-off project, where, in fact, it’s a constant evolution that changes as the market evolves.”
“Where we see people getting into trouble,” says Salvalaggio, “is when they buy random machines from different vendors, only to find out they can’t support them in the long term because they use different processors and communication networks, or they behave differently from one another.”
The ability of different pieces of equipment to communicate with each other is another critical aspect of automation projects. For this reason, it may be necessary to replace old devices, even if they are still working perfectly. That is particularly true for programmable logic controllers (PLCs): “There are some PLCs from the ‘90s that many customers are still using today,” says Villafuerte. “They’re very reliable and durable, but when they are too old it becomes risky to work with them because they’re impossible to communicate with, and also because there won’t be any spare parts on the market if they break down.”
Finally, companies should not forget the human and cultural component: “Automation requires a deep dive into organizational culture and change management, so you need to ensure that your employees feel engaged and empowered in the process,” says Coffey. “If you deploy a new technology without the buy-in from the people that are going to actually use it, adoption will be poor, and you’ll miss your ROI [return on investment] targets.”
With automation being such an important change, it is likely that organizations will have to train their workforce or hire new talent. Salvalaggio recommends a model that involves three levels of training: “maintenance training to ensure that people know how to do preventative maintenance and use the equipment; technical training for troubleshooting and debugging; and engineering, where you define what equipment goes into the plant, its specifications, safety requirements, etc.”
“The most important skill for an automation engineer or technician is creative thinking,” says Villafuerte. “Anyone can write a program, but if you want to think about the whole system, you need to be open minded and creative about how that is going to work.”
Future Trends in Automation Technology
With a new wave of automation that’s just started, what lies ahead for the food industry is the further adoption of automation technologies that are already being used in other industries. “There will likely be an increase in robotics,” says Coffey. “Not only robots but ‘cobots,’ collaborative robots that can work alongside the workforce.”
Salvalaggio echoes this view: “There will be more robotics, in particular Delta robots, which can handle objects with high speed and throughput rates. Also, we’re going to see a combination 3D sensing technology, along with AI algorithms that are specifically designed for handling distorted or unstructured products.”
Tolu is a freelance food science writer based in Spain. Reach him at [email protected].