Food and beverage companies are stressing natural ingredients on their labels. But there’s one artificial ingredient they need to consider as they plan ahead: artificial intelligence.
Manufacturers are finding uses for AI at nearly every stage of their operations, from designing products and packages to boosting efficiency and forecasting demand. AI also has a role to play in critical areas such as food safety and equipment maintenance.
It’s not just a matter of crunching numbers and generating spreadsheets more quickly. Today’s AI incorporates tools like optical scanning and machine learning that can tackle the physical, real-world challenges facing manufacturers. Here is a look at a few areas where AI is making a mark.
Safety and Quality Control: Bad apples are not just a cliché for food and beverage makers, who must be vigilant about finding and removing subpar ingredients and foreign materials from the production process. AI-guided machine vision can root out problems and sort incoming produce to ensure it gets where it needs to go. Some companies even use versions of AI to ensure employees are consistently donning protective masks and hairnets. Advances also are being made in electronic noses, which can be used to detect infections or pollutants.
Operations and Maintenance: Manufacturers lean on AI to calculate the variables that go into food and beverage production and to find the right recipe to keep things humming. Those variables include ingredient levels, energy usage and requirements for machine maintenance. Sensors, meanwhile, can be placed all along the production line to send up warnings about potential equipment failures or bottlenecks. The resulting data can allow timely intervention to stop any breakdowns – and speed up the hunt for root causes. Equipment cleaning is another area that can be optimized through AI, by computing exactly what’s needed to get the job done, conserving resources.
Supply Chain: Logistics in the food and beverage industry have never been more critical. But even in uncertain times, AI can help forecast consumer demand, as well as the supply of ingredients. Executives can use the data to ensure their supply chains are robust, anticipate shocks, quickly identify alternatives and efficiently manage their inventory. Technology also can provide transparency by tracking products from their sources to their end uses.
Consumer Demand: AI gives companies unprecedented insight consumer tastes. Data collected from self-serve soda fountains, for example, led Coca-Cola to develop Cherry Sprite after the company noticed consumers mixing the flavors on their own. At Kellogg, AI tools paved the way for Bear Naked Granola, which allows customers to mix and match ingredients to create their own blends. AI can even figure out new ingredient mixes, as was the case for delivery chain Dodo Pizza. It came up with new, computer-generated pizza recipes.
Packaging: Companies spend hours designing packages for new products. AI and machine learning can save time by rapidly sifting through the options and recommending the best ones. It’s the way AI figures out what you want to watch next on Netflix, but also how some pharmaceutical companies scan for potential drugs to test.
There is a lot to absorb when it comes to AI, and the possibilities can seem overwhelming. But manufacturers don’t have to reinvent their entire process. The first move is to analyze the data you’re already gathering, get some outside advice, and then decide where AI might be worth testing on a limited basis. It is a conversation we are happy to have at K2 Kinetics.
