Food
Industries in the Food Manufacturing subsector transform livestock and agricultural products into products for intermediate or final consumption. The industry groups are distinguished by the raw materials (generally of animal or vegetable origin) processed into food products.The food products manufactured in these establishments are typically sold to wholesalers or retailers for distribution to consumers, but establishments primarily engaged in retailing bakery and candy products made on the premises not for immediate consumption are included.
Assembly Line
Bridging The Data Divide: How Egglife Foods Unified The Plant Floor With SafetyChain And Ignition
Egglife Foods, Inc. is a great example of bridging the gap between quality and machine-level data. By partnering with SafetyChain and Inductive Automation, they’ve unified plant floor data and eliminated latency between data capture, actionable insights, and results. Egglife can connect the dots between thousands of data points across the floor, so quality checks are understood alongside machine performance.
With the introduction of advanced data processing technologies, there is a lot of interest in the “last mile” analytics — the gap in analytic output and actual changes in behavior on the plant floor. A more painful challenge for most manufacturers is the first mile and the “middle miles.” These miles involve getting the data out of the plant floor’s many closed systems and machines, and connecting it with other manufacturing subsystems (human input, machine performance, quality/compliance, etc.) to generate the appropriate context for better decision-making. Anything that doesn’t allow data in or out is a closed system to avoid; this should be table stakes.
An early constraint in the journey to a connected plant floor is leveraging as many of your existing systems as possible. When it comes to solving the “first mile” problem, Inductive Automation’s web-based supervisory control and data acquisition (SCADA) system, Ignition, is unbeatable. Ignition supports multiple frameworks and industry protocols, connects with your existing shop-floor stack, and elevates machine data for utilization in downstream systems and processes. There is no need to look further than Ignition to open up traditionally closed systems (and without breaking the bank).
For Egglife Foods, quality assurance bore the brunt of first- and middle-mile inefficiencies, with processes still heavily dependent on a mix of paper and spreadsheets. Leveraging SafetyChain and Ignition as its food and beverage manufacturing software, they turned what was once a complex and inefficient process into an automated, agile operation capable of delivering consistent, high-quality results in real-time. VP of Operations and Supply Chain Manesh Paudel emphasizes the importance of consistency: “We’re in a business where you’re rewarded for… doing the same thing day in, day out. That is exactly why SafetyChain and Ignition are so important.”
Unwrapping Hershey’s $250M manufacturing upgrade
The investment aims to digitize and automate Hershey’s processes, optimize procurement and manufacturing, and accelerate R&D and planning to boost visibility and streamline operations. Through the initiative, Hershey will be able to better integrate demand planning and bring more automation to the supply chain.
The lack of visibility prompted Hershey to unify its new business units under a single umbrella through an ERP integration using software provider SAP’s S/4 platform. “S/4 was an important foundation,” Buck said at CAGNY. “It enables us the end-to-end connectivity to better identify where there’s redundancy and take that and complexity out of our system.”
Technology is a pillar of Hershey’s current strategy, and the company appointed its first-ever chief technology officer in 2023. Deepak Bhatia came to Hershey after 12 years at Amazon, where his most recent role was VP of supply chain optimization technologies.
Visibility and real-time data also allow plant managers to proactively maintain lines, advancing the initiative’s goal to optimize manufacturing. Data analytics could reveal the best times to clean equipment so it doesn’t interfere with a production run, or when to replace a part before it breaks and causes longer-term issues.
The AAA initiative is slated for completion in 2026. From there, Hershey expects to save $300 million annually, with 30% of the savings from supply chain productivity. This year alone, Hershey expects to save $100 million, with $10 million coming from supply chain savings and the remainder from SG&A.
How AMI Attachments boosts efficiency and combats welder shortage with robot offline programming
General Mills and Brau Union Take Aim at Factory Electricity Bills
The average factory electricity bill varies across the manufacturing industry. The dairy industry hovers around 5% to 8%, and breweries cite 5% to 10% of their operating costs on energy. Factory electricity bills for meat processors can reach 15%, and the sugar industry touches 30%.
Operators have been adding equipment sensors and “quick-win” automation tools to produce more actionable data, while management is going big with evaluations of energy management systems. “Advances in instrumentation by various manufacturers have significantly enhanced data collection and analysis,” says Tim Barthel, executive vice president at Cybertrol Engineering. “Modern systems now offer far more data than what was realized from an analog signal just four years ago.”
Freshwater consumption per peeler is reduced to 0.5 to 2 gal./thousand (GPM) during regular operation. The recycled water is drained and flushed periodically. Moreover, the OEM also offers an option via its system starch separator for its line of Lamina Hydrocutting equipment. According to Vanmark, traditional potato processing includes 2% of water being bled out and is continuously replaced with clean water. The supplier’s system starch separator creates a cyclone in the line that pushes the starchiest water to the pipe’s edge and removes the water. This new feature reduces water consumption for the “bleeding process” while providing the right level of cleaning.
Recently, General Mills worked with ThinkIQ and used its machine learning algorithms to forecast a savings of $480,000 annually with the food and beverage giant’s energy bills. ThinkIQ’s software as a service (SaaS) platform identifies and forecasts “blind spots” within manufacturing sites by implementing an informational model to capture data, visualize plant applications and promote machine learning.
Robot-packed meals are coming to the frozen-food aisle
Chef Robotics, a San Francisco–based startup, has launched a system of AI-powered robotic arms that can be quickly programmed with a recipe to dole out accurate portions of everything from tikka masala to pesto tortellini. After experiments with leading brands, including Amy’s Kitchen, the company says its robots have proved their worth and are being rolled out at scale to more production facilities. They are also being offered to new customers in the US and Canada.
Rather than selling the machines outright, Chef uses a service model, where customers pay a yearly fee that covers maintenance and training. Amy’s currently uses eight systems (each with two robotic arms) spread across two of its plants. One of these systems can now do the work of two to four workers depending on which ingredients are being packed, Griego says. The robots also reduce waste, since they can pack more consistent portions than their human counterparts. One-arm systems typically cost less than $135,000 per year, according to Chef CEO Rajat Bhageria.
AI is touching your food—maybe most of it—by solving the food industry’s unique supply-chain challenges
Using AI to get your products from point A to point B is a growing solution to logistical hurdles, but in no other industry does it feel as nuanced as the food supply chain. That supply chain includes everything from natural agricultural and weather-related challenges to grow ingredients to inventory management and product shelf life: The end consumer needs that item to stay fresh long enough to cook it and eat it, be it at home or at a food service establishment.
Erik Nieves, cofounder and CEO of Plus One Robotics, explains, he has seen AI greatly reduce the time-to-shelf for several products. Part of that is with robotics, like his, that automate packaging systems in warehouses with the help of machine learning and 3D computer vision. The robots can hang out longer in a cold freezer to package temperature-controlled goods and also handle more manual labor than a human, even with a forklift. They are getting pretty good, he says, at detecting different types of fruit and adjusting their gripper strength to avoid bruising a ripe pear.
By analyzing historical sales data, AI is giving food distributors more insight into what is selling when—and informing its purchase orders accordingly. A 2022 study by the World Wildlife Fund found that AI software offered a 14.8% reduction in food waste per grocery store.
The (silent) killer application of 3D printing is packaging your food
Despite numerous efforts and great expectations in futuristic segments such as alternative meat, chocolate and pasta, food 3D printing has not fully delivered on its initial promises. However, the food industry is also one of the biggest (and quietest) implementation areas for 3D printing. Many 3D printer manufacturers have tried to yell it out to the world that 3D printing can revolutionize the food and beverage industries, but many case studies went unnoticed. Unlike direct 3D printing of food products, the additive manufacturing of food and beverage packaging machinery parts is not as appetizing to the wider public as 3D printed chocolate or a pasta dish but it may be one of the killer applications that drive AM adoption.
The benefits of using 3D printing to make food & beverage industry machinery work better are self-evident. For one, food processing machines are highly complex mechanical assemblies that can have well over 2,000 components, many of which have to be stored in inventory and, as a result, cannot be modified easily once they are in production. Many of these parts are complex. Or complexity can be added to a part in order to simplify the machine’s work. This can be done with both metal and polymers, using various different processes and even a wide range of differently priced machines, from professional-level Formlabs and Ultimakers to industrial-level metal PBF and metal binder jetting systems.
Opening a window to the food industry’s future: the world’s first factory growing food out of thin air launches
Factory 01, Solar Foods’ first commercial-scale production facility of Solein®, starts production in Vantaa, Finland. It marks the beginning of the commercialisation of the novel protein and showcases what the future of food production could look like. Solein® is the revolutionary protein grown out of a tiny but mighty micro-organism with CO2 and electricity by the Finnish foodtech company Solar Foods.
Beyond the major step the facility represents for the company’s business, it is also a historic first of its kind for cellular agriculture. Factory 01’s bioreactor grows the same amount of Solein protein per day as a 300-cow dairy farm would produce milk protein – and does this all while being entirely decoupled from the demands and environmental stresses of traditional agriculture. Vainikka likens its significance to food production to the impact quantum computing will have on information processing.
The Scoop on Keeping an Ice Cream Factory Cool
Borkowski maintains and updates equipment at the innovation center’s pilot plant at Colworth Science Park in Sharnbrook, England. The company’s food scientists and engineers use this small-scale factory to experiment with new ice cream formulations and novel production methods. Much of Borkowski’s work involves improving the environmental impact of ice cream production by cutting waste and reducing the amount of energy needed to keep products frozen.
In 2022, he was temporarily transferred to one of Unilever’s ice cream factories in Hellendoorn, Netherlands, to uncover inefficiencies in the production process. He built a system that collected and collated operational data from all the factory’s machines to identify the causes of stoppages and waste. It wasn’t easy. Some of the machines were older and no longer supported by their manufacturers. Also, they ran legacy code written in Dutch—a language Borkowski doesn’t speak.
While working in production can sometimes be stressful, “There’s a deep pride in knowing the machines that we’ve programmed make something that people buy and enjoy,” Borkowski says.
Streamlining Meat Processing: The Power of Data-Driven Daily Fabrication Plans
Data-driven decision-making is essential for any production manager aiming for the most optimized production. Real-time data feeds into your decisions, enabling you to match output with the current demand, avoiding overstocking and cutting down on waste. But it’s not just about the now—this data also helps managers look ahead, forecasting what customers want next and staying one step ahead. By using data to predict and prepare for the future, operations managers can increase the utilization of animals, demand satisfaction levels, and revenue.
Völur’s AI solution uses data-driven insights and machine learning to provide production managers with optimized production plans to ensure the right raw materials are used in value-added or processed products.
Blueberries MEGA FACTORY: Processing Thousands of Blueberries with AI
Product inspection of coffee beans
High Speed Dual View X-ray Inspection of Cans
JBT Corporation Confirms Non-Binding Proposal to Acquire Marel
JBT Corporation (NYSE: JBT), (“JBT” or the “Company”) a leading global technology solutions provider to high-value segments of the food & beverage industry, issued the following statement. JBT confirmed that it has submitted a non-binding initial proposal to the board of directors of Marel hf. (“Marel”), whose shares are listed on Nasdaq Iceland and Euronext Amsterdam, in respect of a potential voluntary takeover offer for the entire share capital of Marel in accordance with Chapters X and XII of the Icelandic Takeovers Act no. 108/2007. JBT has received an irrevocable undertaking and entered into exclusivity with respect to the shares owned by Eyrir Invest hf., which holds 24.7% of the shares in Marel. This announcement follows Marel’s disclosure that it had received a potential offer to acquire all shares in the company.
How factories are deploying AI on production lines
Augury’s sensors used in PepsiCo factories have been trained on huge volumes of audio data, to be able to detect faults such as wearing on conveyor belts and bearings, while analysing machine vibrations. By also collecting information and insights into equipment health on the whole, such as identifying when a machine might fail again in future, the technology lets workers schedule maintenance in advance, and avoid having to react to machine errors as they occur.
Prof Brintrup, professor of digital manufacturing at the University of Cambridge’s Institute for Manufacturing, leads the Institute for Manufacturing’s Supply Chain AI Lab, which has developed its own predictive mechanism to identify where ingredients such as palm oil may have been used in a product, but disguised under a different name on its label. The lab’s recent research suggested that palm oil can go by 200 different names in the US - and these might not stand out to eco-conscious consumers.
Cone Ice cream Inspection using Machine Vision
Automated packaging tech helps streamline snack and bakery operations
Kellogg’s uses packaging automation to create efficient production lines with the capacity for high throughput volume. This entails using automation in areas where manual labor may struggle to keep up with rapid rates of product output. “Our automation systems handle tasks such as placing products into containers and transporting them to the end of the line, as well as filling unit loads and loading them onto trucks via forklifts. The product mostly remains untouched by human hands until it reaches the retailer,” says David Sosnoski, director of packaging engineering for salty snacks, Kellogg Co.
Robotics plays a significant role within Kellogg’s packaging automation initiatives, offering a diverse range of options, from basic and simple robots to advanced collaborative robots (cobots). “Cobots are designed to replace repetitive human tasks that do not require a larger, fully automated solution,” Sosnoski says. “They have proven valuable in filling the middle ground between tasks that are too complex for traditional automation but exceed human capabilities in certain areas.”
🧀 Next Time You Buy Parmesan, Watch Out for the Microchip
Italian producers of parmesan cheese have been fighting against imitations for years. Now, makers of Parmigiano-Reggiano, as the original parmesan cheese is officially called, are slapping the microchips on their 90-pound cheese wheels as part of an endless cat-and-mouse game between makers of authentic and fake products.
The new silicon chips, made by Chicago-based p-Chip, use blockchain technology to authenticate data that can trace the cheese as far back as the producer of the milk used. The chips have been in advanced testing on more than 100,000 Parmigiano wheels for more than a year. The consortium of producers wants to be sure the chips can stand up to Parmigiano’s aging requirement, which is a minimum of one year and can exceed three years for some varieties.
Drugmaker Merck KGaA will soon begin using the chips, which are also being tested in the automotive industry to guarantee the authenticity of car parts. The chips could eventually be used on livestock, crops or medicine stored in liquid nitrogen.
“We don’t want to be known as the company accused of tracking people,” said Eibon. “I ate one of the chips and nobody is tracking me, except my wife, and she uses a different method.”
Automation that displays flashes of creativity
More complex icing and decorating systems are replacing traditional waterfall icing operations. For example, Inline Filling Systems recently developed a swirled icing decoration on top of a fully baked cake. The system relies on servo pump fillers feeding a pair of eight-across nozzle manifolds attached to two ABB robots applying a distinctive, programmable decoration pattern over an Auto-Bake Serpentine production line.
The Deco-Bot is a self-contained robotic decorating, glazing, depositing and spraying system with a built-in conveyor and quick hookup for heated and non-heated pumps. “Cobots are not the speed demon robotics you see on a caged line. They serve a different purpose,” he explained. “They help manufacturers with the labor crisis with a small footprint while being easy to clean and set up, and they are very safe.” It’s not uncommon to see 10 to 12 cobots decorating cakes night and day on the same production line.
AI-automated meal kitting powered by Covariant
🧀 Conceptualizing the sustainable dairy plant of the future
Depending on the type of dairy processing plant — cheese, milk, butter, etc. — the Stellar Group makes specific recommendations. “In cheese factories, there’s an opportunity to recover the water and use for other purposes like hot water, potable water. This will help to reduce biochemical oxygen demand (BOD) for wastewater,” Kolla, Goode and Smallwood suggest. “Solar panels will provide as an alternative source to reduce energy costs and a combined heat and power (CHP) system, also known as cogeneration, will recover heat from the systems (cooling tower, heat exchangers) and produce an alternative energy source.”
Kolla notes that once the factory is built, it can be extremely expensive to retrofit it into a sustainable factory. However, “It’s very cost effective to design the factory from day one with a sustainable strategy,” he advises. “Leverage state and federal government energy rebate programs. Some states provide incentives based on energy used per ton of product.”
High-Speed Flow-Wrapper Loading of Cupcakes
State-Based Control Uncovers Automation Gains
For this edible oil production company, the equipment was tasked with refining two different types of oil, each with its own characteristics. A key part of the process involved dosing the oil with clay to “bleach” it. This removes the color, chlorophyl and performs other conditioning. The clay must then be filtered out. Each type of oil requires a different clay dosing rate, and in turn the filters need to be cleaned at differing intervals for best overall performance.
Before implementing control loop performance monitoring (CLPM) technology, some aspects of the company’s operations were manual and others were automatic. For example, when production began after a product changeover, operators would manually manipulate the system to achieve a steady state, and then apply tuning settings and setpoints corresponding with the product type. While this would result in product that was well within specification, it used more clay than was necessary.
State-based CLPM was initially proven for the localized part of the process where clay was first dosed and then filtered for the facility’s various products. The technology was quickly extended to make improvements in other PIDs, including control of the bleaching process’ back-end temperature loops. These successes have led to an initiative to identify similar opportunities for control improvements within this individual facility as well as across the company’s more than 100 other sites operated globally.
CLPM software is now part of the standard toolkit for the company to improve operational performance, and to then maintain and sustain that performance over time. Analytics on their own don’t fix anything. But putting useful and accessible analytics in the hands of users, through software with advanced features like state-based control, empowers plant personnel to implement continuous improvement.
Automation helps bakers make the most of ingredients
While many bakers hope and anticipate raw material costs will ease in 2023, that future is not now. Ingredient costs remain high, especially when it comes to premium ingredients such as dairy, eggs and sugar. While product loss and waste is never desirable, at these prices, waste just got unaffordable. And this isn’t limited to ingredient costs either. The price of labor itself has indulgent products like sweet goods costing more to produce these days. Manufacturers of these products are looking for ways to reduce waste and improve production efficiencies to bring these costs in line.
“Automation is the answer here,” said Hans Besems, executive product manager, AMF Tromp, an AMF Bakery Systems brand. “We can automate almost the complete process and take over where human labor is hard to find or where it is too intensive. An automated process eliminates many opportunities for finished product to fall out of spec, but it’s critical that the dough being fed to the makeup line is consistent.”
“With smart technologies and AI, AMF Tromp uses vision technology to evaluate every single product in real time, and by machine learning the Tromp machines will adapt automatically, resulting in almost no waste and perfect products repeatedly,” Mr. Besems said.
AI and the chocolate factory
“After about 72 hours of training with the digital twin (on a standard computer; about 24 hours on computer clusters in the cloud), the AI is ready to control the real machine. That’s definitely much faster than humans developing these control algorithms,” Bischoff says. Using reinforcement learning, the AI has developed a solution strategy in which all the chocolate bars on the front conveyor belts are transported on as quickly as possible and the exact speed is only controlled on the last conveyor belt - is interestingly quite different from that of a conventional control system.
The researchers led by Martin Bischoff were able to make their approach even more practical by compressing and compiling the trained control models in such a way that they run cycle-synchronously on the Siemens Simatic controllers in real time. Thomas Menzel, who is responsible for the department Digital Machines and Innovation within the business segment Production Machines, sees great potential in the methodology of letting AI learn complex control tasks independently on the digital twin: “Under the name AI Motion Trainer, this method is now helping several co-creation partners to develop application-specific optimized controls in a much shorter time. Production machines are now no longer limited to tasks for which a PLC control program has already been developed but can realize all tasks that can be learned by AI. The integration with our SIMATIC portfolio makes the use of this technology particularly industry-grade.”
This 3-D Printed Icelandic Fish-Gutting Machine Contains the Secret of a Future, Less-Globalized Economy
Tucked away in a nondescript 10,000-square-foot building there is a manufacturing facility that runs 24/7, producing parts for fish-processing machines in a way that was, even a few years ago, impossible. Elliði Hreinsson, the founder of Curio, which owns the building, says the machines he designs and makes would be difficult or in some cases impossible to produce without 3-D printing.
“In Iceland, we are a small stone in the ocean, and we cannot so easily run around to get help,” says Mr. Hreinsson. “You have to be able to do it all in-house.” His machines, which he sells to clients around the world, include more than 100 parts that he prints on seven 3-D printers made by a company called Desktop Metal. Printing the stainless-steel parts this way skips all the steps required for conventional manufacturing, from prototyping to casting or injection molding—the last of which generally happens in Asia, and can add weeks or months to the time between product design and delivery.
High tech meets agriculture in Denmark
The Danish company Nordic Harvest runs Europe’s biggest vertical farm in Denmark. Vertical farming is either the worst method of farming in terms of CO2 emissions, or it’s the best. That all depends on the type of energy used to power the farm – and on the technology used to run it. Denmark sees greenhouse production as a big part of its future. Not only can it feed its own population at less cost and in a more energy-efficient manner, but it can also export some of the technology and know-how. A project, called Greenhouse Industry 4.0, was established to bring in some of the latest technology already used in other industries and apply it to greenhouse production.
Anders Riemann, founder and director of Nordic Harvest, says in a company blog post that the only reason they haven’t moved beyond production of just lettuce, herbs and cabbage is that these are the only plants that are profitable to grow with vertical farming. It is not economically feasible to use vertical farming to grow tomatoes, for example, because it takes too much time and effort for the plant to grow leaves and stems, which cannot be sold. Only after a long period of photosynthesis can tomato plants start bearing the fruit that can be sold. It’s not only technological development that will determine what makes sense to produce in the future. A whole new ecosystem needs to develop around new methods of farming. For example, seeds will be bred so they are suitable for vertical farming.
World's Largest Pasta Production Plant a Showcase for Integrated Robotics and Sustainable Distribution
Barilla’s flagship pasta manufacturing plant in Parma, Italy boasts a 430,000 square foot distribution facility – fully automated, lights-out, 24/7/365 operation – equipped with120 laser-guided vehicles, 37 robotic systems including high-density AS/RS, palletizers, labelers and stretch wrappers, handling 320,000 tons of pasta annually. Designed, manufactured and installed by E80 Group, this distribution facility is not only an example of excellence in integrated robotics systems, but also a showpiece for energy and environmental efficiency.
To realize such an integrated-system and energy-efficient strategy at Barilla’s Parma distribution facility, E80 Group (E80) was selected to design, manufacture and install a solution. E80 is an Italian-based multinational leader specializing in creating automated solutions for companies that produce fast-moving consumer goods, particularly in the food, beverage and tissue sectors. It has been a leading manufacturer of integrated-robotics systems for distribution facilities for almost three decades, specifically laser-guided vehicles (LGVs), robotic palletizers and other end-of-line robotic systems. The company’s latest technology advances have made LGVs particularly attractive for sustainability and reduced energy usage.
How the best steam peelers can significantly reduce food waste on vegetable processing lines
When peeling vegetables, many processing lines waste huge amounts of food – and potential revenue. With modern peeling machines, however, this can be prevented, while also reducing energy costs and water consumption. Eamonn Cullen, Marketing Manager Peeling at TOMRA Food, explains how.
Food waste is financial waste, yet when processing lines peel vegetables, they often let huge amounts of raw material get thrown away. Food losses can be as high as 30% during mechanical peeling and 20% with low-tech steam peelers – and much of this lost revenue is preventable.
How Junior's Bakes 5 Million Cheesecakes During A Cream Cheese Shortage
The Advantages of a Data-Driven Culture for Food Production
Data-driven production does not look the same for every kind of product. The complexity of food and beverage processing puts it in another category that has unique needs for data management. Food processors need a solution that can interact with a range of production workflows, meet compliance and quality standards, bring operations into sync, and equip them for growth.
Data-driven decision-making is even more crucial for food and beverage manufacturers, who are operating in a complex global supply chain with thin margins and plenty of risk. According to CSIMarket, the gross profit margin for the food processing industry in 2022 currently rests at 19.2 per cent, which is lower than other industries (averaging 49.4 per cent). In such an environment, the advantages of quality, workable data for business success is difficult to understate, yielding valuable analytics to drive business agility and providing the means to build capacity in a scalable way for the future marketplace.
Shinkei Systems’ AI-guided fish harvesting is more humane and less wasteful
Fresh fish isn’t really that fresh — even straight off the boat. The way they’re caught and killed is not only inhumane but detrimental to the resulting meat. There’s a far superior alternative, but it’s time-consuming and manual — but Shinkei Systems has figured out a way to automate it, even on the deck of a moving boat and has landed $1.3 million to bring its machine to market.
Ike-jime involves piercing the brain with a sharp spike to send the fish to fish heaven, then quickly exsanguinating it, and after that destroying the spinal cord. Gruesome, yes, but all of these things prevent stress, suffering and the spreading of bacteria and destructive substances through the body. But it has to be done precisely and within a couple minutes of the fish being caught, so it doesn’t really scale. That is, unless you automate it, which is what Shinkei Systems has done. The team, led by founder Saif Khawaja, has created a mechanical means of accomplishing ike-jime on fresh-caught fish, at a rate of one every 10-15 seconds.
How King Arthur Baking Produces 100 Million Pounds of Flour per Year
A hi-tech factory supports circular mushroom production
To grow mushrooms you need a ‘substrate’ – the base material colonised by the fungi’s mycelium from which the edible mushroom flowers. But sourcing substrates is a thorn in the side of commercial exotic mushroom growers, with supply chain issues dogging the market. This is where Belgian startup Eclo comes in. Normally, mushroom substrates are made from a wood base, grains, water, and mycelium. Eclo, by contrast, has found a way to replace the grains with organic waste from breweries and industrial bakeries. Not only is this a good use of recyled material that reduces the demand for virgin grain – the novel substrate is also high-yield, benefitting growers’ bottom lines.
Cultured Meat Is So Close You Can Almost Taste It
The technology of cultured animal meats has come in a very short time. Prices have declined to the point that these products are competitive – although not on parity – with animal products. Pioneer Mosa Meat reportedly spent $280,000 to create the first cultured beef burger in 2013. Israel’s Future Meat Technologies claims to have reduced the production cost of a 4-oz. cultured (but partially plant-based) chicken breast to $7.50, and beef for less than $16 per pound.
Several companies are gearing up to make production quantities of their products. BlueNalu is completing a 40,000-sq.-ft. pilot facility in San Diego “that enables limited volumes under GMP conditions and global best practices in food safety,” a spokesperson told us. Israel’s Future Meat Technologies raised $347 million in investment back in December, the largest single fundraising to date for a company in the cultivated meat space, in part to build a U.S. plant. While Pioneer Memphis Meats, which has rebranded itself as Upside Foods, last November opened its Engineering, Production and Innovation Center (EPIC), claiming the 53,000 sq. ft. facility in Emeryville, Calif., is the most advanced cultivated meat production facility in the world.
High-tech potato-grading line ups profits for Cornish grower
Another problem caused by the older line relates to packers now wanting more specific size grading, particularly for the Gemson and Jazzy salad varieties the farm grows. They also prefer the crop to be delivered stone free, which is a challenge because of the region’s light loam soils having a relatively high small stone content. With their maincrop varieties, such as Electra, this can be addressed in the field, but it is much more difficult to remove on the harvester when using the narrow 28mm webs that are required for the salad crops.
Quality assurance of sausage salad with 3 different inspection solutions
Tyson invests in AI-enabled robotics firm to boost worker productivity
Automating meat factories has long been a difficult feat because it is costly and carcasses come in varying sizes so it can be hard for robots to cut and work with all types accurately. But as the coronavirus ravaged meat plants, forcing many to temporarily shutter as thousands of workers got sick, more companies accelerated their plans for automation. Meat and poultry companies also are automating certain tasks that can be repetitious or prone to injury, such as moving or loading boxes.
Soft Robotics’ SoftAI technology uses AI and 3D vision to maneuver the company’s mGrip robotic grippers with human-like hand-eye coordination. The technology allows the automation of bulk picking for fragile and irregularly shaped proteins, produce and bakery items, according to the company. Tyson Foods is an existing user of Soft Robotics’ software.
Machine learning optimizes real-time inspection of instant noodle packaging
During the production process there are various factors that can potentially lead to the seasoning sachets slipping between two noodle blocks and being cut open by the cutting machine or being packed separately in two packets side by side. Such defective products would result in consumer complaints and damage to the company’s reputation, for which reason delivery of such products to dealers should be reduced as far as possible. Since the machine type upgraded by Tianjin FengYu already produced with a very low error rate before, another aspect of quality control is critical: It must be ensured that only the defective and not the defect-free products are reliably sorted out.
Integrated intelligent technologies optimize yield and increase profits for rice millers
The digitally connected technology provides mill operators with the insights they need to correctly adjust solution settings. Over time, the intelligent system is capable of adjusting autonomously. Where millers were once left to take corrective action after an incident occurred, they can now prevent costly reprocessing steps and proactively manage the entire process. With these advances, the miller can optimize operating costs, quality and yield, all of which have a direct impact on the profit of the mill.
Analysing fruit data in the supply chain has never been more important for business efficiency
Fruit and production data can be used in ways that it has never been done before to improve a company’s efficiency and boost profits, according to global packhouse equipment and automation supplier Tomra Food.
He added that there are several different useful data types at play in a packhouse; production and traceability level data, performance level data, quality data and auditing data. This data can be used to optimise the supply chain and can be used to make decisions and directions in terms of the next big thing that needs to be done. But consumer trends will constantly change the requirements of automation.
Hygienic Thermoformer Loading
Why Meatpacking Plants Have Become Covid-19 Hot Spots
In Texas, the fastest growing Covid-19 outbreak isn’t in Dallas or Houston or San Antonio, the state’s most densely packed metro areas. It’s hundreds of miles to the north, in the dusty, windswept flatlands of Moore County, population 20,000. According to data reported Monday by the state health department, 19 out of 1,000 residents in Moore County have so far tested positive for the novel coronavirus that causes Covid-19 — 10 times higher than the infection rates in the state’s largest cities.
So what’s in Moore County that’s making people so sick? One of the nation’s largest beef processing facilities, where huge armies of employees slice, shave, and clean up to 5,000 cattle carcasses a day. Last month, Texas health officials launched an investigation into a cluster of Covid-19 cases linked to the massive meatpacking plant, which is operated by JBS USA, a subsidiary of the largest meat processing company in the world, based in São Paulo, Brazil.
3D printing in metal resulted in fewer bacteria and greater food safety
3D printing in metal was chosen as a solution and Marel quickly began to redesign the support element specifically for 3D printing, so that it took full advantage of the technology’s possibilities. The support element is in direct contact with food, so bacteria can accumulate in all cleaves, joints and openings, and these bacteria can be transferred directly to the meat. That’s why we were really excited about the possibility of 3D printing the support element in one piece, and the weight reduction was also a positive element, as the support element moves MANY times a second, says Matias Taul Hansen, Technical Designer at Marel
3D printing is a much cheaper solution than cutting out the item, and compared to laser cutting, 3D printing is also preferable, as we avoid joints where bacteria can accumulate. By 3D printing in titanium, we also achieve a lower-weight item that is cheaper to produce and that can work faster, says Kristian Rand Henriksen, consultant at the Danish Technological Institute.