Digital transformation is changing how we do business across the globe, and the food industry is no exception as emerging technologies such as artificial intelligence (AI), machine learning and robotics are revolutionizing everything from food processing to service to sustainability.
“There is no doubt that technology will become a critical component of our everyday food experiences within the next five years,” says Vipin Jain, founder and CEO of Blendid, in a January 2022 Q&A with Robotics Tomorrow. “Robotics and AI will facilitate better access to healthy food, while also reducing food waste to help our planet.”
Tech Tackles Issues Too Complex for the Human Mind
Food Processing senior editor Pan Demetrakakes sees AI and machine learning capabilities able to handle detailed issues that are too complex or time-consuming for the human mind.
“AI is already being used in some food processing applications and has the potential to be used in many more, including maintenance, sanitation and logistics,” Demetrakakes writes in a February 2022 article.
In some ways, the shift to technology is replacing decisions made by “gut feeling” which are often misguided.
“Due to the difficulty in processing all of this data, often times gut feel or tribal knowledge end up being the basis for decisions. This results in great variability and therefore lack of consistency in decision-making across the organization,” Richard Phillips, director of smart manufacturing at systems integrator Polytron, told Food Processing.
Can Automation Solve the Food Service Worker Problem?
The historically tight labor market has hit the food service industry especially hard.
In November 2021, for example, 1 million of the 4.5 million American workers who quit their jobs were in the restaurant and hotel industry.
“Employees who remain in the industry are left scrambling to serve customers and fulfill to-go orders, and restaurants have been forced to close dining rooms and cut operating hours to help curb the impacts of the worker shortage. For some restaurants, the labor crunch has even led to them shutting down for good,” reported the Business Insider.
Jain told Robotics Today that food service operators are looking to technology solutions to solve this workforce staffing problem.
The key, according to Jain, is that it requires “a diverse team of skilled cross-functional leaders in technology, food, and business operations, building the right product that consumers desires, a robust go-to-market strategy, field experience to ensure the product can sustain the stress and reliability needed in commercial food service, and sustainable business model.”
Besides Blendid -- which offers contactless and autonomous robotic food kiosks with partners like smoothie maker Jamba – there are plenty of other players in the food robotics market, estimated at $1.9 billion in 2020 but expected to skyrocket to $4 billion by 2026, including:
- Sally by Chowbotics (salad-making robot)
- Celilia.ai (interactive robot bartender)
- Picnic (automatic pizza maker)
- The Mini Bakery (automated loaf maker)
- Miso Robotics (robotic kitchen for fast food chains)
- Kitchen Robotics (robotic dark kitchen)
- TrueBird (full automated micro-café)
- Smile Robotics (Plates-collecting robot)
- Solato (Gelato maker)
- Milkit (Milk on tap)
“From cocktail-making to burger-flipping, many food and beverage businesses are beginning to discover the benefits of using robots to improve their productivity. The automation revolution has begun,” says FastCausual.com.
AI Can Sort, Grade and Inspect Ingredients and Products
On the other end of food service is food processing where AI can help by setting standards and specifications, as well as alerting manufacturers as to when products go out of spec.
AI, programmed with a baseline “sort recipe” for what a product should look like, can excel at sorting, grading, and inspecting ingredients and the final products.
“The end result is always a sorter that is custom-programmed specifically for the unique processing line on which it is installed, because each installation has unique definitions of good in-spec product as well as the exact defects and the types of foreign materials and contaminants that must be eliminated,” Marco Azzaretti, Key Technology director of marketing, told Food Processing.
Benefits of using AI in this area includes:
- Higher accuracy
- Lower detection limits
- More complex physical relationships
AI’s Role in Maintenance: Prediction vs. Prevention
AI can help food processors move their maintenance from “preventive maintenance” to the next level of “predictive maintenance.”
“Predictive maintenance is a program of continuously monitoring equipment and developing a profile of its performance that indicates when it’s likely to need attention,” writes Demetrakakes.
Predictive maintenance is based on:
- AI developing a profile via continuous assessment of parameters
- Sensors attached to equipment relay real-time data, often via cloud-based apps
- The data is analyzed with a profile developed for when equipment needs replacement
AI Can Find Food Processing Problems Fast
Putting it mildly, “things happen”, and AI is great at looking at complex inputs to quickly discover why a product has gone out of spec or other issues have happened.
“AI has the capacity simply to consider more things – more potential causes – than the human mind is capable of. By noticing variations in inputs and other factors, AI can discover correlations that might go unnoticed by human observers,” writes Demetrakakes.
A company like Seebo, which makes AI software, can help companies correct losses and inefficiencies on production lines.
““The Seebo solution conducts continuous, multivariate analysis on all the data relevant to the production process - from data on the raw materials, to quality data, and even external data like the weather, temperature or humidity; literally every piece of relevant data is being analyzed 24/7,” Seebo co-founder Liran Akavia told Food Processing. “That also includes all the complex, dynamic interrelationships between the different data tags on the line.”
Other AI machine learning ventures are being developed to improve sanitation and sustainability, such as limiting water usage.
“Artificial intelligence and machine learning are some of the most powerful tools in computer science. Using them judiciously has the potential to increase efficiency in some of the most important, and challenging, applications to be found in a food plant,” concluded Demetrakakes.
