Tag Archives: artificial intelligence

Pratibha Pillalamarri

Quick-Win Strategies To Propel Digital Transformation in Food Production Safety

By Pratibha Pillalamarri
No Comments
Pratibha Pillalamarri

The world’s population now exceeds 8 billion people. For the food industry, this means more than just additional mouths to feed; it also means changing consumer tastes, higher demand for more product variety, and the need to balance product safety and sustainability, along with profitability.

In a rapidly changing environment, digital solutions help companies make informed business decisions quickly. The missing component is rarely a lack of data itself. To stay competitive, and appropriately balance safety, sustainability, and profitability amid a growing population, companies need to reap the full benefit of their existing operational and process data to gain valuable insights and efficiencies. Data analytics and digital tools empower companies to collect, centralize, and extract actionable data-driven insights generated throughout the entire manufacturing lifecycle. While digital transformation can sometimes be overwhelming, there are specific steps you can take to realize important benefits, quickly.

Breaking Data Silos To Boost Efficiency

Food and beverage manufacturers generate large amounts of data during the process of turning raw materials into finished products, including information about equipment run time, product quality, and energy consumption.

Despite the need to share and analyze this data collaboratively, industrial data is often stored in separate systems, managed by different teams, and at times governed by inconsistent processes. These data silos impede collaboration, diminish quality control and safety measures, and ultimately hurt the bottom line. In a highly regulated industry, simple missteps can negatively impact brand reputation in addition to causing compliance violations and regulatory penalties.

Subscribe to the Food Safety Tech weekly newsletter to stay up to date on the latest news and information on food safety and quality.

Consider a food manufacturer that produces packaged goods. An unplanned stoppage in production can lead to safety incidents, product contamination and losses, and energy wastage. Connecting manufacturing data across functions and generating contextual insights will result in proactive planning and maintenance scheduling.

A manufacturer with disconnected inventory management and production planning systems cannot accurately forecast product demand or adjust its production schedules. This results in missed insights and excess inventory or stockouts that lead to increased costs, and/or missed sales opportunities. In both scenarios, a robust data and digitalization strategy could reduce process disruptions or deviations, product waste and recalls, and revenue loss.

Four Steps to Get More out of Your Data

Robust data analytics and management tools can provide value across the organization. The following strategies will help ensure digital initiatives deliver maximum value nearly right away throughout the entire manufacturing cycle. These quick successes help the pave the way for long-term digital integration.

Start with small initiatives. It is usually most effective to start small when it comes to digital initiatives. Pick a single site or production line, identify an urgent pain point to solve, and develop a focused approach to applying analytics. This strategy ensures a targeted investment of resources and time, as well as the opportunity to test and refine strategies.

After initial project success, it is often helpful to step back and evaluate what worked, what did not work, and review best practices for deploying the technology at scale.

Set clear goals and metrics. Setting clear, measurable goals and metrics allows you to monitor progress. For example, a company might want to work toward reducing equipment downtime by 20% within the next six months. In addition, it’s often helpful to have a champion in the organization who will push for innovation, track progress, and serve as a motivator across the company.

Build data-driven operations. Comprehensive data-driven solutions have embedded domain expertise to make employees’ jobs easier by freeing them up for high value work. The key is to invest the time, energy, and resources in training employees effectively.

When deploying AI and other data-driven technology, focus on high-impact areas for quick wins. Centralized data management systems can seamlessly connect sensors, IoT devices, legacy systems, or other interfaces in production processes, allowing engineers and managers to focus on problem solving versus data collection and analysis.

For instance, AI-powered process analytics software can analyze process data, monitor variables that are likely to produce an off-spec product, automatically alert the team when a problem needs to be addressed, and prescribe changes to address the issue. Likewise, predictive maintenance solutions can use this data to detect equipment failures early and accurately, thereby reducing downtime events. These solutions also have built-in prescriptive capabilities to guide and empower maintenance personnel to address equipment issues in a timely manner.

Leverage data to identify areas for future innovation. Beyond solving today’s production pain points, data analytics can transform manufacturing for the future by helping companies respond to changing consumer preferences and needs, including the increase in health-conscious consumers and the global rise in food allergies. By analyzing this kind of data, the industry can identify areas where innovation is needed. And, as new products are developed, existing solutions can be leveraged to increase flexibility and efficiency in production lines for data-driven growth.

By unlocking the true value of data, companies can generate insights with their digital transformation strategies that optimize production, reduce waste, and improve profitability while ensuring consumer safety.

Olga Pawluczyk, P&P Optica

Ask the Expert: Olga Pawluczyk Discusses Hyperspectral Imaging

No Comments
Olga Pawluczyk, P&P Optica

Can you explain, in simple terms, what hyperspectral imaging is?

Olga Pawluczyk: Hyperspectral imaging is a form of spectroscopy, which is the science of how wavelengths of light (or really, electromagnetic spectrum) interact with substances. As different wavelengths are absorbed by atomic and molecular bonds, we can measure that interaction and determine the chemistry of the substance under investigation. Essentially, your eyes and brain form a simple 3 color spectrometer: since you see grass as green, you can guess that it contains chlorophyll. Now, hyperspectral images include full 2D spatial information (like a regular camera image) but split the light into hundreds of continuous colors (or wavelengths). Compare this to the three colors (red, green, blue) used by cameras like the one in your cell-phone. Hyperspectral imaging allows much greater precision than other types of spectroscopy.

Why is hyperspectral imaging so effective for finding foreign (FM) materials in food products?

Pawluczyk: Using hyperspectral imaging, a system can see full images of objects and chemical signatures of different materials within those images. That’s what makes this technology so much better than other forms of vision or spectroscopy for distinguishing materials such as clear plastics, rubber and bone that are often hard to see on the line. Not only do we see the chemistry, but can also distinguish very small objects that differ in their chemistry from their surroundings. We can do this on line, at line speeds. PPO’s hyperspectral imaging system has been developed specifically for food processing, with rigorous testing and unique spectrometer design that allows us to see a lot of chemical information, while still enabling producers to run their lines at full speeds.Combining this with our powerful artificial intelligence (AI) engine makes our system uniquely effective at line speed, meaning contaminants can be identified and removed immediately.

What are the advantages of hyperspectral imaging over other types of detection systems?

Pawluczyk: In addition to being highly effective at finding FM, an important advantage of hyperspectral imaging is that it also enables us to see the composition of food products. Since food is chemistry, we can use hyperspectral imaging to assess different chemical properties of food products. For example, our testing has shown that spinach grown in different parts of the same field will have slightly different chemistry. Hyperspectral imaging can see those differences, so we can identify many different quality issues such as woody breast in chicken, fat/lean ratios, freshness and moisture content.

How can food processors use this information on composition and quality?

Pawluczyk: PPO’s Smart Imaging System uses an AI engine to collect and process the data from our imaging system; It ‘learns’ over time and gets even better at detection of FM or quality issues. It also means that PPO’s system can spot trends in your production. For example, using PPO’s technology, one of our clients was able to identify and correct an issue with their de-boning process, which helped them reduce customer charge-backs by 40%.

How confident can processors be that the system will catch the FM and quality issues they care about?

Pawluczyk: Part of PPO’s installation process with a new client is a very thorough testing process. Our team of experts works closely with our client to configure each system to the precise conditions of the plant and the products that are being processed. Using AI, our Smart Imaging System gathers and stores all this information, so it learns over time and is continuously improving.

What makes PPO’s Smart Imaging System different from other visual inspection systems on the market?

Pawluczyk: PPO’s is the only hyperspectral imaging system that is operating on the line in multiple plants across North America. It is being used in a variety of poultry and pork processing facilities and has proven to be highly effective in finding a wide range of foreign materials.

Ultimately, we think happy clients are the greatest proof that our system is working. We’re seeing repeat orders starting to come in from existing clients as they reap the cost benefits of improved detection in their plants.

Learn how food processors can leverage hyperspectral imaging on P&P Optica.

Content sponsored by P&P Optica.

Olga Pawluczyk, P&P OpticaAbout Olga Pawluczyk
President, CEO and Co-Founder
P&P Optica

Olga Pawluczyk is the co-founder and CEO of P&P Optica (PPO), based in Waterloo, Ontario, part of Canada’s largest and fastest growing tech community. Pawluczyk is an expert in medical imaging, with a technical background in systems engineering and deep knowledge of the science of spectroscopy. Under the leadership of Pawluczyk and her co-founder, her father Romek Pawluczyk, PPO launched in 2004 as a research company focused on developing high-end spectrometers. The company has evolved over the past eight years to focus on building solutions to the issues of safety and quality in the food processing industry. Pawluczyk is driven by the opportunity to combine emerging technologies to significantly improve the nutritional quality, safety, and sustainability of our food.

As a leader, Pawluczyk focuses on providing an engaging working environment to like-minded people who are excited to explore new challenges as part of the PPO team. Outside of PPO, She is active in the local tech community in Waterloo Region; is an avid reader who loves to discuss pretty much any topic over coffee (or wine); and enjoys spending time walking and biking.

Emily Newton, Revolutionized Magazine
FST Soapbox

Packaging Automation Can Be an Essential Tool for Food Manufacturers

By Emily Newton
No Comments
Emily Newton, Revolutionized Magazine

Food and beverage manufacturers face various challenges—including a labor shortage, rising demand and ongoing supply chain disruptions. Food packaging automation can be an essential tool for these businesses, as the technology can improve manufacturing productivity without hiring additional workers.

As demand continues to rise over the next few years, and as the labor shortage continues, packaging automation will likely become more important. This is why manufacturers are turning to the technology and how innovations in Industry 4.0 solutions may reshape food manufacturing this decade.

Food and Beverage Manufacturers Are Doing More With Less

Food manufacturers face the same market challenges that most companies are navigating right now. Even two years after the beginning of the COVID-19 pandemic, the supply chain remains unstable, demand is volatile and job openings continue to outstrip available workers.

Consumer expectations are also changing. A growing segment of American shoppers expects businesses to deliver items faster than ever, putting greater pressure on manufacturers to accelerate production and logistics operations.

These trends aren’t likely to reverse anytime soon, even as the pandemic eases and vaccines become available globally. Some experts predict that the labor shortage may be on track to last for years, and the lack of essential raw materials or components may similarly drag on well into the future. This means hunkering down and attempting to weather current market conditions will not be an effective strategy. Instead, businesses will have to experiment with new ways to improve productivity, reduce operating costs and accelerate delivery times.

Automation may become an essential strategy, especially for food and beverage manufacturing tasks that have traditionally been time-consuming and challenging to automate.

How Food Packaging Automation Helps Manufacturers Stay Competitive

Manufacturers that need to increase factory throughput may struggle to bring on additional labor necessary to improve production. Instead, solutions that help them increase productivity without hiring—like packaging automation—may help companies meet existing demand.

Packaging automation tools allow manufacturers to automate various tasks that are tedious, dull, time-consuming and potentially dangerous.

Industry 4.0 technology also allows packaging solutions to automate work that previously required human labor. For example, AI-powered automation systems can use machine vision—algorithms that enable machines to “see” objects — for quality control and manufacturing purposes. These systems may be able to automatically package items or visually inspect them for defects, allowing businesses to improve quality control processes without the dedication of additional labor.

Food packaging automation can also help make food and beverage products more consistent and safer for workers and consumers. Quality control processes are often tedious or repetitive. Throughout a shift, workers assigned to these tasks tend to slow down and make mistakes, potentially allowing defective or dangerous products to move further along the production line.

Automated packaging systems are remarkably consistent when well-maintained. They can run for hours at a time without the same risks that may come with human workers assigned to tedious or repetitive tasks.

Some internet grocery retailers are also using a combination of AI and RFID to improve package branding and drive sales. RFID allows businesses to embed unique identifiers into the packaging of every product they sell, making it possible to collect deeper information about consumer demands and purchasing habits.

Other AI systems use IoT devices that gather real-time data on equipment operations to streamline or automate maintenance checks. For example, a predictive maintenance approach uses AI forecasting algorithms and IoT data to monitor machines and predict when they will need maintenance. The approach is similar to preventive maintenance but is more effective at keeping machines online. In practice, the forecasting power of a predictive maintenance algorithm can reduce downtime and maintenance costs.

Similar AI technology can also be used in the packaging design process. An AI algorithm trained on a library of packaging data may be used to create new packaging—helping businesses identify novel options when it comes to shape or material choice.

Other Advantages of Packaging Automation

Reducing the cost of packaging can also allow manufacturers to spend more money on higher-quality food wrapping—which can, in turn, improve customer satisfaction and drive revenue. For example, many manufacturers have begun to offer eco-friendly packaging materials that can be customized with branding elements. These packaging materials will attract customers who want to buy products from eco-friendly brands. They will also help manufacturers build deeper client relationships while growing additional company awareness.

Over time, these decisions can help a business transform its packaging into a branding tool. This will require an additional up-front investment, but the improvements will pay for themselves over time.
Packaging Automation Can Help Food and Beverage Manufacturers Adapt

Cutting-edge industry technology has made packaging solutions more effective than ever. The right equipment allows food and beverage manufacturers to automate various packaging, design and maintenance tasks—making individual facilities and businesswide processes much more efficient.

Emily Newton, Revolutionized Magazine
FST Soapbox

Using Artificial Intelligence May Add More Transparency to the Food Supply Chain

By Emily Newton
No Comments
Emily Newton, Revolutionized Magazine

Food industry professionals know how supply chain transparency plays a major role in keeping everything running smoothly. Brand representatives want confirmation that their agricultural partners can fill upcoming orders. If things go wrong and people get sick from what they eat, better visibility is vital in addressing and curbing such issues.

Artificial intelligence (AI) is a critical part of better food supply chain awareness among all applicable parties. This article briefly discusses some interesting examples.

Applying AI to Crop Management

Even the most experienced agricultural professionals know farming is far from an exact science. Everything from pests to droughts can negatively impact a growing season, even if a farmer does anything they can to influence production in their favor.

However, AI can help predict yields, enabling farmers to maintain transparency and set accurate expectations for parties further down the supply chain. That’s especially important in the increasingly popular farm-to-table movement, which shortens how far produce travels and may entail using it on the same day someone picks it.

One newly developed machine-learning tool relies on computer vision and ultra-scale images taken from the air to categorize lettuce crops. More specifically, it captures details about the size, quality, and quantity of the heads. Combining that with GPS allows more efficient harvesting.

Tracing Foodborne Illness

CDC Statistics indicate foodborne illnesses sicken one in six people every year in the United States. FSMA contains rules and actions for food processing facilities to prevent such instances, but outbreaks still happen. AI could be yet another useful mitigation measure.

Researchers at the University of Georgia determined that, since the 1960s, approximately a quarter of Salmonella outbreaks have been from the Typhimurium variation. They trained a machine-learning algorithm on more than 1,300 Typhimurium genomes with known origins. The model eventually achieved 83% accuracy in predicting certain animal sources that would have the Typhimurium genome. It showed the most accuracy with poultry and swine.

Reducing Food Waste

Waste is a tremendous problem for the food supply chain. In the United States, data shows that upwards of 40% of packaged consumables get discarded once they reach the use-by date. That happens whether or not the products are actually unsafe to eat.

However, better visibility into this issue has a positive impact on food distribution. For example, some restaurants give people discounted meals rather than throwing them away. In other cases, grocery stores partner with charities, helping people in need have enough to eat.

Scientists in Singapore have also created an electronic “nose” that uses AI to sniff out meat freshness. More specifically, it reacts to the gases produced during decay. When the team tested the system on chicken, fish and beef, it showed 98.5% accuracy in its task. Using AI in this manner could bring transparency that cuts food waste while assuring someone that a food product is still safe to eat despite the appearance of it being expired based on Best Before’ labeling.

Removing Guesswork From Dynamic Processes

People are particularly interested in how AI often detects signs that humans miss. Thus, it can often solve problems that previously proved challenging. For example, even the most conscientious farmers can’t watch all their animals every moment of the day and night, but AI could provide greater visibility. That’s valuable since animal health can directly impact the success of entire farming operations.

One European Union-funded AI project took into account how animal health is a primary factor in milk production. The tool compared cows’ behaviors to baseline levels and characteristics of the animals at the most successful farms. It then provided users with practical insights for improvement. Europe has at least 274 million dairy cows, and their milk makes up 11%-14% of Europeans’ dietary fat requirements. Those statistics show why keeping herds producing as expected is critical.

AI is also increasingly used in aquaculture. Until recently, fish farming professionals largely used intuition and experience to determine feeding amounts. However, that can lead to waste. One company uses artificial intelligence to sense fish and shrimp hunger levels and sends that information to smart dispensers that release food. The manufacturers say this approach causes up to a 21% reduction in feed costs. Other solutions track how much fish eat over time, helping farmers adjust their care protocols.

Fascinating Advancements in Supply Chain Transparency

These instances are only a sampling of what AI can do to support the food supply chain. Although most of them are most relevant to producers, consumers will likely reap the benefits, too. For example, some food labels already show the precise field associated with the potatoes used for a bag of chips. Once technology reaches a point where most consumers could have advanced AI apps on their phones, it could be a matter of aiming a smartphone’s camera at any food product and instantly seeing the path it took before reaching the consumer. It’s too early to know when that might happen. Nevertheless, what’s already possible with innovative technology is compelling in its own right and makes people rightfully eager to see what’s on the horizon.

Emily Newton, Revolutionized Magazine
FST Soapbox

As Demand for Frozen Food Surges, Cold Storage Facilities Must Continue to Prioritize Safety

By Emily Newton
No Comments
Emily Newton, Revolutionized Magazine

Frozen food demand has skyrocketed. Although COVID-19 was a catalyst, there are many reasons why the trend will likely continue going forward. The pandemic forced people to eat at home more, which was largely responsible for the hike in food sales, especially frozen goods. Higher availability and food quality enhancements have also contributed to the spike, prompting suppliers to upgrade and expand cold storage warehouse solutions—whether that means creating extra space or utilizing existing space more effectively.

One of the more important changes, prioritized across the industry, is food preservation and safety. It has always been crucial that frozen food reaches its destination clean, healthy and still frozen — just as it went in. However, preliminary data from the CDC’s Foodborne Diseases Active Surveillance Network reveals that foodborne illnesses are up 15%. The primary or most common form is Salmonella, but COVID-19 has consumers and food safety professionals thinking more closely about cleanliness and proper sanitation.

It has pushed a tight focus on safety overall, with new innovations looking to enhance sector controls.

Necessity Breeds Creativity

Recent events have played a role in the industry’s continued focus on safety, but so have consumer demands, as more and more people look to frozen meals, foods and items as part of their normal routines.

People love convenience. But as the pandemic hit, and people were forced to isolate and remain home more, and restaurants and stores closed as a safety precaution. What was once about convenience became even more about safety. People still wanted freedom and ease of use, but it wasn’t a necessity nor was it a priority. Safety became even more important, which is why curbside pickup, deliveries and online transactions became so popular.

What does this have to do with frozen foods? Everything. Because of the pandemic, we’ve all had to eat at home more often, which means preparing meals, snacks and other items, with minimal exposure to the outside world or even local grocery stores. Naturally, consumers turned to easily cooked and pre-prepared frozen foods and meals.

Safety is the Priority

It makes sense that more frozen foods being purchased and consumed would shift priorities in the market. In a 2021 report released by Acosta, 14% of respondents say they consume frozen food nearly all the time. About 46% say they consume frozen foods often.

During the pandemic, the share of U.S. core frozen food consumers rose to 39% in 2020, up from 35% in 2018. “Core” consumers are defined as those who either eat frozen food daily or every few days.

What’s more, 42% of households that buy frozen foods did so online, up from 23% in 2018. And online frozen food sales jumped 75% last year, with the top purchases including frozen dinners and entrees, meat, poultry and even seafood.

Instead of restricting eating habits, consumers have turned to frozen foods to spruce up their meals, create new at-home dishes, and so on. It has boosted the demand for all kinds of frozen foods. It also necessitates the need for improved quality and safety. Implementing and maintaining strict controls as to how the food is transported, handled and preserved, can prevent contamination on all fronts.

With that rise in dependence, on frozen foods specifically, it is imperative that supply chain operators are delivering goods in a safe, healthy condition. Allowing foods to thaw during the transport process can introduce more problems than just contamination, especially with COVID remaining a major influence.

Imagine how bad it would be if the world experienced a major foodborne outbreak, right now. Most scenarios can be prevented through smarter food handling and better, data-driven controls.

New methods are being implemented to chill and prepare foods earlier on in the supply process. Many cold chain providers are adopting low-temperature chillers, like a food processing chiller, for example. They can freeze prepared foods quickly to ensure they are safe, disinfected and stored appropriately. From there, it’s just a matter of keeping them cold-locked during transport, storage, delivery, and beyond. That’s precisely where some of the latest innovations come into the picture.

Cold Storage Warehouse Innovations

To keep up with the demand and ensure frozen foods and other goods stay fresh in the cold chain, the industry is seeing rampant innovation, thanks to modern technologies. Think IoT-equipped fleets and storage systems to facilitate faster time to market and better transparency. Or, machine learning and AI-driven tools that help discern bottlenecks, locate faster and more effective solutions, and so on.

At the heart of it all is data, or rather digital content and information. The smarter and more contextually driven operations are, the better efficiency is all around. The following are some of the technologies making this happen:

  • IioT. The Industrial Internet of Things (IIoT) involves connected devices that continually collect, transmit and sometimes process performance and contextual data. In the cold chain, it can be used to track goods, prevent theft or fraud, monitor processes, discover bottlenecks and more.
  • Machine Learning. An offset of artificial intelligence, machine learning and neural networks can be used to ingest and analyze massive swarms of data in ways, and at speeds, that humans never could. What’s more, the technology can empower highly advanced automation systems to take action, respond, or act based on algorithmic rulesets.
  • Electric and autonomous vehicles. Revolutionizing logistics and conventional transport, electric and fully autonomous vehicles will significantly improve fleets with better safety, stop-free trips and more.
  • Smart shelving. Imagine Amazon’s Kivo bots, or something similar, implemented within cold storage warehouses. The entire system is designed to improve inventory management, order picking, and general logistics.
  • Co-bots. Beyond delivery, ground-based drones or advanced robots can be used to transport and move heavy goods, large or bulk orders, and organize the warehouse. When outfitted with the appropriate hardware, they can reach high shelves and storage areas or move through hazardous locations, improving safety for manual workers.

Innovation Brings New Challenges

Of course, there are the general challenges facing the cold storage industry, such as how to keep foods fresh throughout the journey, proper packaging solutions, and maintaining more sanitary conditions, but there are new challenges presented by the adopted technologies.

For example, IIoT devices aren’t typically designed to be exposed to extremely frigid temperatures, which may sometimes affect the measurements and data collected. A malfunctioning device can lead to serious problems, especially when it’s the sole method for maintaining temperatures and ensuring food is properly stored.

Bringing these devices up to a sufficiently resistant level is a challenge, as is keeping them running optimally. Failing to do so could increase food contamination, the spread of foodborne illness, or worse.

Another challenge involves the expansion or development of new cold storage facilities. As warehouses and locations grow to accommodate larger inventories, the cold storage systems must become more sophisticated and powerful. What’s more, even the slightest temperature drop because of a system failure can have sweeping repercussions in such a large facility. A single refrigeration unit going down can drop temperatures across the entire warehouse.

Designing smarter spaces to keep the cold temperatures contained is one solution. Installing the supporting systems is another, which keeps things operational even when a negative scenario plays out. Automation and smart, data-driven technologies can be incredibly helpful in this area.

Finally, the bigger the cold storage solution, the higher the power draw and the more resources needed to keep things running. In turn, it’s necessary to install and implement smart technologies to reduce the carbon footprint. Cutting energy usage wherever possible becomes vital to sustainability. It can call for solutions like smart or timed lighting, smart thermostats for the refrigeration units, or upgraded systems that reduce emissions — think electric fleets and renewable energy platforms.

Backup solutions are even a part of the mix, when power outages can bring an entire operation down in seconds, and expose food to long-term risk.

Frozen Food Demand: A Steady Climb

Things may change, and there are never any guarantees, but right now it looks as though high demand for frozen food will continue, and may even grow steadily. Market conditions are partly responsible, but consumers are now more focused on quality and healthy foods, above eating out or ordering in. As the economy continues to open, people will want to get back out there and explore. But that doesn’t necessarily mean frozen food demand will decline.

Cold chain and cold storage warehouse providers must be prepared for the continued growth, which includes finding new and innovative ways to preserve, package and safely store frozen foods.

Emily Newton, Revolutionized Magazine
FST Soapbox

How Food Processors Can Use Robots to Improve Food Quality

By Emily Newton
No Comments
Emily Newton, Revolutionized Magazine

Across industries, new innovations in robotics technologies are helping to speed up day-to-day work and improve product quality. Robots can be especially effective for businesses in the food processing industry, where a growing labor shortage poses trouble for processors.

While a number of critical industry tasks were difficult to fully or partially automate in the past, new robotics technology is helping to increase the number of potential applications for robots in the industry.

Consistency, Accuracy, and Speed

Food processing robots offer a few major advantages over conventional food processing workflows. Robots can perform a task repeatedly over the course of a work day or shift, typically with minimal deviation in precision. Unlike human workers, robots don’t get tired, and their pace of work tends to stay consistent. This combination of accuracy and speed has been found to increase site throughput while ensuring packaged products are up to company standards.

Food processors that adopt robots also see major gains in item consistency—more often, packaged products contain the same amount of food, weigh the same, and are packaged in the same manner.

Automated packaging systems can sometimes be a poor fit for certain food commodities, especially for products like delicate fruits and vegetables.

Experimentation, however, often leads to custom solutions that can handle these unique challenges. After experimentation with new weighing and packaging robots in the cannabis industry, for example, processors were able to accelerate the packaging process and create more consistently packaged items.

In the food processing industry, this can come in the form of robots with soft silicon grippers and attachments, which help companies package delicate products.

Workers production line
Workers in a factory sorting food by hand, could be assisted by new robot technology. (Unsplash image)

Preventing Cross Contamination

Despite improved food safety standards, foodborne disease outbreaks remain common in the United States.

The use of robots can help control cross-contamination in food processing plants.

With any human labor force comes the risk of cross-contamination. Workers assigned to packaging foods can easily transport pathogens from product to product or from one area of the facility to another. This is especially true in sites that process raw meat products. Even when following proper site hygiene practices, it’s possible for workers to unintentionally transport pathogens and other contaminants from one workcell to another.

Because work in food processing facilities is often shoulder-to-shoulder, it’s also easy for contaminants to spread from one worker to another once a particular cell has been contaminated.

Robots that are fixed in place and handle all the aspects of a particular packaging job can help localize potential contamination, making it easier for processors to minimize cross-contamination and keep food safe.

Robots can still contribute to cross contamination if not properly cleaned, but an additional set of robots could solve this problem, too. For example, one a provider of robots for the food processing industry has developed a set of robots capable of washing down an entire workcell.

These robots, working in pairs, activate at the end of each operating cycle and use high-powered jets of water to wash down the workcell, the packaging robots used there, and themselves.

Collaborative Robotics (Cobots)

One major recent innovation in robots has a new focus on tech that is collaborative.

These new robots, unlike conventional robotics, aren’t always built to fully automate a particular task. Instead, they are built to interact and work collaboratively alongside humans where necessary.

Artificial intelligence-based machine vision technology helps them navigate factory floors safely or assist in tasks like assembly and machine tending. Safety features like force limiters and padded joints help prevent injuries that can occur while working in close proximity to conventional robots.

These features also enable them to work in tight spaces without the use of safety cages that conventional robots sometimes require. In factories and food processing plants, they can provide assistance and speed up existing workflows.

For example, an article in Asia Pacific Food Industry cites one case study from a Swedish food processor, Orkla Foods. The company integrated cobots into a production line packaging vanilla cream, freeing up the human workers who had been responsible for the task. Before the cobots were introduced, workers had to bag and manually pack the vanilla cream into cartons.

Even with cobots, human workers are still necessary for tasks that require judgment, creativity, and problem-solving skills. Cobots can take over tasks that don’t lend themselves well to automation. These tasks tend to be tedious, dull, or even dangerous due to the repetitive motions workers need to make.

Even if a task can’t be fully automated, cobots can still help improve efficiency and boost accuracy. These robots provide the most significant benefits for businesses that need flexibility and agility in production.

Cobots are often lightweight and easy to reprogram on-the-fly, allowing workers to quickly move them from task to task as needed. In many cases, an entire fleet of cobots can be repositioned and reprogrammed in half a day, allowing a business to reconfigure its robots to handle entirely new tasks without additional capital investment.

This flexibility can also make cobots a better fit for personalized products than other systems. As product specifications change, a cobot can be easily programmed and reprogrammed to handle the differences.

The use of these robots can also help prevent cross contamination, like more conventional robotics.

Sector-Specific Applications

A handful of sectors within the food processing industry can also benefit from niche robotics designed to automate certain specific tasks.

Danish robotics manufacturer Varo, for example, developed a line of cake decorating and filling robots. These robots are designed with technology that allows them to determine which cake will be decorated next, minimizing the amount of human involvement needed to operate.

While these robots won’t be useful for every manufacturer, they are a good example of how many sectors within the industry stand to benefit from robots that can automate niche tasks.
Using Food Processing Robots to Improve Product Quality and Consistency
Robots help automate tasks that are dull, dirty or dangerous. In doing so, they typically provide businesses with significant upgrades to process accuracy, speed, and consistency.

New technology—like machine vision and collaborative robotics technology—is helping to expand the use cases of robots in the food processing industry. These robots can often improve product quality more effectively than process changes alone, and may help manage a labor gap that could persist well into the future.

James Gunn-Wilkerson, CMX
Retail Food Safety Forum

The Future Is Now: AI Takes Journey from Supply Chain to Today’s Restaurant Kitchens

By James Gunn-Wilkerson
No Comments
James Gunn-Wilkerson, CMX

Futurist Ross Dawson has said that AI and automation will shape the future of work, and it also promises to transform our lives beyond the office. According to the World Economic Forum, when AI, which provides the ability to “enable devices to learn, reason and process information like humans,” is combined with Internet of Things (IoT) devices and systems, it creates AIoT. This super duo has the potential to power smart homes, smart cities, smart industries and even our smartwatches and fitness trackers, a market estimated by Gartner to be worth $87 billion by 2023. More importantly, this “interconnectedness” will change the way we interact with our devices as well as the way we will live and work in the future.

In the restaurant industry, we’re already seeing glimpses of this interconnectedness take shape, and in the past year, we’ve experienced major technological advancements that have transformed every facet of the way food establishments work. Reflecting on those advancements, I want to take a moment to share three areas of AI impact that are bubbling up in the restaurant sector in 2021.

1: AI-powered Intelligent Kitchens

From ghost kitchens to traditional kitchens, the “back of the house” continues to be a prime target for AI and automation. While great progress has been made, in many ways it seems like we’ve only scratched the surface when it comes to how far AI can take today’s restaurants. But every now and then, we hear examples of AI powering the future of our industry. For example, Nala Robotics, Inc. will be opening what it calls “the world’s first state-of-the-art intelligent restaurant” in Naperville, Illinois this year. The company says the AI-based robotic kitchen “can create dishes from any cuisine around the world, using authentic recipes from celebrated chefs”. A press release from Nala Robotics states that its flagship restaurant is taking “the first step in the food service industry with AI-powered service, addressing many of the issues affecting restaurant owners during COVID-19,” and it will “provide consumers an endless variety of cuisine without potential contamination from human contact.” This is the new frontier in intelligent kitchens, and it couldn’t have come at a better time, with the pandemic forcing restaurants to reimagine the way they do business.

2: AI-Driven Labor Shifts.

You can’t talk about AI in the restaurant industry without also having a conversation about the implications for the modern workforce. With AI in restaurant kitchens and beyond, the impact on the labor force is undeniable. By 2024, Gartner predicts “that these technologies will replace almost 69% of the manager’s workload.” But that’s not entirely a bad thing. Instead of manually filling out forms and updating records, managers can turn to AI to automate these and other tedious tasks. “By using AI…they can spend less time managing transactions and can invest more time on learning, performance management and goal setting,” Gartner adds.Managers can also use the extra time to focus more effort on the customer and employee experience. And indeed they should: In a recent Deloitte report, 60% of guests surveyed indicated that a positive experience would influence them to dine at a restaurant more frequently.

Looking at the impact of AI on labor at all levels, from the CEO to the entry-level wage earner, the shift, at its best, will be a transition to more meaningful—and less mundane—work. The evolution of humanity has taken us to the point we’re now at now, with food production and delivery processes becoming increasingly automated. This has been an evolution generations in the making. In an ideal world, everyone at every level of the organization should benefit from this new wave of technology. For example, automation can and should be used to open the door to new training and new opportunities for low-wage earners to learn new skills that elevate career paths, increase income and improve quality of life.

3: AI and Global Supply Chain Transformation

From the farm all the way to the table, AI is now poised to transform the global supply chain. From my perspective, the biggest impact will be around driving sustainability efforts. Restaurant and grocery brands are already beginning to leverage AI to forecast their food supply needs based on customer demand, leading to less over-ordering and less food waste to support sustainability initiatives. One company in this space, FourKites, is creating what it calls “the digital supply chain of the future.” Using real-time visibility and machine learning, FourKites powers and optimizes global supply chains, making them “automated, interconnected and collaborative—spanning transportation, warehouses, stores, trucks and more.”

In addition to predictive planning, more and more brands will start to use AI to create incident risk management models to identify trends and risks in the supply chain to determine whether bad or recalled products are originating from a specific supplier, distributor, or due to an environmental variable.With all of these changes, the need for comprehensive data standards will multiply as suppliers and distributors around the world work together to bring us produce and packaged food from all corners of the globe. Data standards will be critical to traceability and the exchange of critical tracking events and key data elements, and advances in data standards will power the meta-data needed to provide better insight for food quality and regulatory compliance, crisis management, and recalls—at scale.

Research firm Forrester states that, in the end, the greatest impact resulting from an investment in robotics and other technologies that automate operational tasks is improved customer experience (CX). “Most companies believe that investment in AI, automation, and robotics for engagement will decrease operational costs. While this is true, our research shows that the revenue upside from delivering better CX could deliver a greater impact on the bottom line over time,” Forrester states.

As a business engaged in digitizing and transforming supply chain operations, our team couldn’t agree with Forrester more. But we believe it will take striking the right balance between technology and the human touch to not only drive stronger CX, but to also create a world in which AI is implemented for the greater good—a world in which people, processes, business and technology all win.

Angel Suarez, EAS Consulting Group
FST Soapbox

Regulatory Cross Cutting with Artificial Intelligence and Imported Seafood

By Angel M. Suarez
No Comments
Angel Suarez, EAS Consulting Group

Since 2019 the FDA’s crosscutting work has implemented artificial intelligence (AI) as part of the its New Era of Smarter Food Safety initiative. This new application of available data sources can strengthen the agency’s public health mission with the goal using AI to improve capabilities to quickly and efficiently identify products that may pose a threat to public health by impeding their entry into the U.S. market.

On February 8 the FDA reported the initiation of their succeeding phase for AI activity with the Imported Seafood Pilot program. Running from February 1 through July 31, 2021, the pilot will allow FDA to study and evaluate the utility of AI in support of import targeting, ultimately assisting with the implementation of an AI model to target high-risk seafood products—a critical strategy, as the United States imports nearly 94% of its seafood, according to the FDA.

Where in the past, reliance on human intervention and/or trend analysis drove scrutiny of seafood shipments such as field exams, label exams or laboratory analysis of samples, with the use of AI technologies, FDA surveillance and regulatory efforts might be improved. The use of Artificial intelligence will allow for processing large amount of data at a faster rate and accuracy giving the capability for revamping FDA regulatory compliance and facilitate importers knowledge of compliance carrying through correct activity. FDA compliance officers would also get actionable insights faster, ensuring that operations can keep up with emerging compliance requirements.

Predictive Risk-based Evaluation for Dynamic Imports Compliance (PREDICT) is the current electronic tracking system that FDA uses to evaluate risk using a database screening system. It combs through every distribution line of imported food and ranks risk based on human inputs of historical data classifying foods as higher or lower risk. Higher-risk foods get more scrutiny at ports of entry. It is worth noting that AI is not intended to replace those noticeable PREDICT trends, but rather augment them. AI will be part of a wider toolset for regulators who want to figure out how and why certain trends happen so that they can make informed decisions.

AI’s focus in this regard is to strengthen food safety through the use of machine learning and identification of complex patterns in large data sets to order to detect and predict risk. AI combined with PREDICT has the potential to be the tool that expedites the clearance of lower risk seafood shipments, and identifies those that are higher risk.

The unleashing of data through this sophisticated mechanism can expedite sample collection, review and analysis with a focus on prevention and action-oriented information.

American consumers want safe food, whether it is domestically produced or imported from abroad. FDA needs to transform its computing and technology infrastructure to close the gap between rapid advances in product and process technology solutions to ensure that advances translate into meaningful results for these consumers.

There is a lot we humans can learn from data generated by machine learning and because of that learning curve, FDA is not expecting to see a reduction of FDA import enforcement action during the pilot program. Inputs will need to be adjusted, as well as performance and targets for violative seafood shipments, and the building of smart machines capable of performing tasks that typically require human interaction, optimizing workplans, planning and logistics will be prioritized.

In the future, AI will assist FDA in making regulatory decisions about which facilities must be inspected, what foods are most likely to make people sick, and other risk prioritization factors. As times and technologies change, FDA is changing with them, but its objective remains in protecting public health. There is much promise in AI, but developing a food safety algorithm takes time. FDA’s pilot program focusing on AI’s capabilities to strengthen the safety of U.S. seafood imports is a strong next step in predictive analytics in support of FDA’s New Era of Smarter Food Safety.

Nicole Lang, igus
Retail Food Safety Forum

Robots Serve Up Safety in Restaurants

By Nicole Lang
No Comments
Nicole Lang, igus

Perhaps the top takeaway from the worldwide COVID-19 pandemic is that people the world over realize how easily viruses can spread. Even with social distancing, masks and zealous, frequent handwashing, everyone has learned contagions can cycle through the atmosphere and put a person at risk of serious, and sometimes deadly, health complications. In reality, there are no safe spaces when proper protocols are not followed.

The primary culprit in transmission of norovirus, according to the CDC, is contaminated food. “The virus can easily contaminate food because it is very tiny and spreads easily,” the CDC says in a fact sheet for food workers posted on its website. “It only takes a very small amount of virus to make someone sick.”

The CDC numbers are alarming. The agency reports about 20 million people get sick from norovirus each year, most from close contact with infected people or by eating contaminated food. Norovirus is the leading cause of disease outbreaks from contaminated food in the United States, and infected food workers cause about 70% of reported norovirus outbreaks from contaminated food.

The solution to reducing the transmission of unhealthy particles could be starting to take shape through automation. While robots have been used for the past few years in food manufacturing and processing, new solutions take food handling to a new level. Robots are no longer in the back of the house in the food industry, isolated in packaging and manufacturing plants. They are now front and center. The next time you see a salad prepared for you at a favorite haunt, you may be watching a robot.

“The global pandemic has altered the way that we eat,” said Justin Rooney, of Dexai Robotics, a company that developed a food service robotic device. Reducing human contact with food via hands-free ordering and autonomous food serving capabilities has the potential to reduce the spread of pathogens and viruses, and could help keep food fresh for a longer period of time.

Painful Pandemic

Increased use of automation in the foodservice industry might be one of the salvations of the COVID-19 pandemic. In an industry searching for good news, that might be the silver lining in an otherwise gloomful crisis.

Job losses in the restaurant industry have been brutal. By the end of November, nearly 110,000 restaurants in the United States had closed. A report by the National Restaurant Association said restaurants lost three times more jobs than any other industry since the beginning of the pandemic. In December, reports said nearly 17% of U.S. restaurants had closed. Some restaurants clung to life by offering outdoor dining, but as winter set in, that option evaporated. Some governors even demanded restaurant closures as the pandemic escalated in late fall.

Restaurants have faced a chronic labor shortage for years. Despite layoffs during the pandemic, many former foodservice employees are electing to leave the industry.

Teenagers, for instance, and some older workers are staying away for health and safety reasons. Some former workers are also finding out that they can make more money on unemployment benefits than by returning to work. Restaurant chains have hiked wages, but filling positions still remains a challenge.

Automated Solutions

Restaurants began dancing with the idea of robots nearly 50 years ago. The trend started slowly, with customers ordering food directly through kiosks. As of 2011, McDonald’s installed nearly 7,000 touchscreen kiosks to handle cashiering responsibilities at restaurants throughout Europe.

As technology has advanced, so has the presence of robots in restaurants. In 2019 Seattle-based Picnic unveiled a robot that can prepare 300 pizzas in an hour. In January, Nala Robotics announced it would open the world’s first “intelligent” restaurant. The robotic kitchen can create dishes from any cuisine in the world. The kitchen, which is expected to open in April in Naperville, Illinois, will have the capability to create an endless variety of cuisine without potential contamination from human contact.

Dexai designed a new robotic unit that allows for hands-free ordering that can be placed through any device with an Internet connection. The robot also includes a new subsystem for utensils, which are stored in a food bin to keep them temperature controlled. This ensures that robot is compliant with ServSafe regulations. The company is working on improving robot system’s reliability, robustness, safety and user friendliness. The robot has two areas to hold tools, a kitchen display system, bowl passing arm, an enclosure for electronics and two refrigeration units. It has the unique ability to swap utensils to comply with food service standards and prevent contamination as a result of allergens, for example.

Why Automation

Many industries have been impacted by advancements in automation, and the foodservice industry is no different. While initially expensive, the benefits over time can provide to be worth the investment.

One of the most significant advantages, particularly important in the post-COVID era, is better quality control. Automated units can detect issues much earlier in the supply chain, and address those issues.

Automation can also help improve worker safety by executing some of the more repetitive and dangerous tasks. Robots can also boost efficiency (i.e., a robot used for making pizza that can press out dough five times faster than humans and place them into ovens) and eliminate the risk of injury. Robots are also being used to make coffee, manage orders and billing, and prepare the food. Robots can also collect data that will help foodservice owners regarding output, quantity, speed and other factors.

“Alfred’s actions are powered by artificial intelligence,” according to Rooney. “Each time Alfred performs an action, the associated data gets fed into a machine learning model. Consequently, each individual Alfred learns from the accumulated success and failures of every other Alfred that has existed.” Dexai plans to teach the robot to operate other commonly found pieces of kitchen equipment such as grills, fryers, espresso machines, ice cream cabinets and smoothie makers.

Unrelenting Trend

Automated solutions might have come along too late to save many restaurants, but the path forward is clear. While they are not yet everywhere, robots are now in play at significant number of restaurants, and there is no turning back. Any way you slice it, robots in restaurants, clearly, is an idea whose time has come.

FDA

FDA Begins Phase Two of Artificial Intelligence Imported Seafood Pilot Program

By Food Safety Tech Staff
No Comments
FDA

FDA is beginning phase two of its Artificial Intelligence Imported Seafood Pilot Program. The program, which is expected to run from February 1 through July 31, intends to improve FDA’s response in quickly and efficiently identifying potentially harmful imported seafood products.

Phase one of the pilot looked at using machine learning to find violative seafood shipments. “The pilot program will help the agency not only gain valuable experience with new powerful AI-enabled technology but also add to the tools used to determine compliance with regulatory requirements and speed up detection of public health threats,” FDA stated in a news release. “Following completion of the pilot, FDA will communicate on our findings to promote transparency and facilitate dialogue on how new and emerging technologies can be harnessed to solve complex public health challenges.”

The pilot program is part of the agency’s efforts that fall under the New Era of Smarter Food Safety.