Foreign materials in food was the fourth most common reason for food safety recalls in 2023, according to AIB International. The most common contaminants included wood, plastic, metal and glass, which can come from malfunctioning equipment or may have been present in the ingredients when they arrived at the manufacturing facility.
Bakers and snack makers understand the importance of guarding against these materials getting into the final products and avoiding costly recalls. But with all the systems available to help, how do they determine which is best for their facility?
“X-ray, metal detection, checkweighing and vision all play a critical role in guaranteeing the quality and safety of food products before they reach consumers,” said Eric Garr, regional sales manager, Fortress Technology. “Decisions regarding the implementation of these inspection systems should be grounded in a thorough risk analysis of the manufacturer’s processes. This approach ensures that the chosen systems effectively mitigate potential risks specific to the production environment, such as foreign object contamination or compliance issues.”
Although the technologies are commonly used as standalone systems, a combination of options tied to a data reporting system can achieve the highest performance and productivity levels, Garr added.
“Metal detectors and X-ray systems offer different but complementary ways to screen for contaminants,” he said. “The addition of vision systems can provide labeling, packaging integrity and pack fill checks, as well as ensuring pack separation as products are fed onto inspection machine conveyors.”
Choosing the best system for each facility means manufacturers must assess the largest risks to the baked foods or snacks.
“The first question you’re going to ask is looking at the environment and the product: What type of materials are going to be most prevalent that you’re going to have the largest issue or risk with?” said Kyle Hermes, vice president, TDI Packsys. “For most facilities and operations, this is going to be metals. Most of the stuff in the production line is going to be metal. Metal detectors in general are a safe bet for a lot of these facilities that are smaller or don’t have any more restrictive needs. If metal detectors aren’t an option, the second option for most people is X-ray. It’s considered the step up.”
Low-density, low-conductive materials represent some of the greatest challenges for quality assurance.
“These are things that would not qualify either for X-ray or metal detection,” Hermes said. “In these cases, you have a few options. Vision systems are usually the way to go, vision systems and optical sorters. The limitations on these are if they’re internal to the product already. If there’s nothing visible and its conductivity and density aren’t allowing us to see into the product with either of our other means, those are the ranges currently that are not detectable.”
For the items that are hardest to detect, the best defense is a good offense.
“Since low-density plastics are not easily detected, the best way to overcome this challenge is a good preventative procedure program that includes routine visual inspection of plastic wear items and plastic components that could enter the production stream if broken or damaged,” said Craig Lorei, global market manager, light industry, Eriez.
In a perfect world, bakeries would have all the systems to help guard against a wide range of foreign materials, Hermes said.
“There’s no system out there that’s perfect that’s going to cover all types of foreign material in the same product,” Hermes pointed out. “It’s going to have to be a collaboration between them. There are models that are combination systems. We offer two of them. This can provide a little space saving, and it’s a little bit more effective. We have one that’s a mix of a metal detector and a checkweigher. This can detect for over and under weights and can check for metal at the same time, but it’s operated as a single system. And then we have a combination X-ray and vision system, where both are operated with a single HMI and the same machine.”
Although having multiple systems would be ideal, it’s not practical for all operations.
“The problem with all these different systems is, No. 1, they cost money,” said Andrew McGhie, business development director, KPM vision inspection, KPM Analytics. “No. 2, they all have to be set up, maintained and operators have to be trained. As the bakers know, it is always a challenge to get and then retain capable people. With every capital equipment purchase, a baker is always balancing the total cost of the technology and the payback to the business — labor savings, improved quality, food safety and protecting their brand.”
The investment food manufacturers make can also be influenced by the level of risk, McGhie said.
“If the product bakers are producing has a higher food safety risk profile based on the ingredients, the process and the nature of the product, then they may be more likely to invest in more of these technologies,” he said. “If it’s a very low-risk product and process, bakers may be less cautious and more selective in the food safety and quality technologies they invest in. If manufacturers have very demanding foodservice or QSR customers with the highest quality standards, they don’t want to make a mistake and risk that business. Those are the assessments bakers are always making.”
In addition to identifying the type of contaminants as well as the products in each bakery and the different detection capabilities they may need, regulatory requirements must be weighed as well, said Mark Friesen, global director of marketing, Bunting Magnetics.
Bakers must “ensure compliance with local and international food safety regulations that may dictate specific quality control measures,” he explained.
Alexandre Goasmat, robotics and automation product manager, ABI Ltd., said customers often approach him with specific quality control needs.
“For example, they might need to measure the height of buns after proofing,” he said. “As experts in the field, we assess their requirements and specifications to recommend the most appropriate quality control systems, whether it be metal detectors, vision systems or X-rays.”
The company uses a quality control system using multiple input sources to collect comprehensive data and provide a unified analysis, Goasmat added.
Because needs can vary based on the product, raw materials used, plant location and equipment, finding the best quality assurance equipment for each operation is not always easy.
“Finding an inspection equipment provider that offers product testing can help a bakery or snack maker determine if a basic metal detector is adequate,” said Todd Grube, product manager inspection systems, Heat and Control. “Fortunately, the technology in inspection and detection equipment continues to advance, so bakers and snack makers can determine the necessary level of their quality control program, and if appropriate, utilize more sophisticated inspection equipment that detects smaller foreign objects, reduces false rejects and handles a wider range of products to ensure maximum food safety with higher productivity.”
Putting quality checks at critical control points (CCPs) along manufacturing lines can save bakeries and snack makers time and money as problems can be caught and addressed quickly.
“Placing metal detectors at different CCPs on the line can help save costs by preventing added value as the product goes through production,” said Sarrina Crowley, marketing communications manager, Mettler-Toledo. “Throat and gravity metal detectors can catch metal contaminants in incoming ingredients, conveyorized systems placed after mixing and baking where metal may have been introduced from mixers and at the end of the line at final packaging.”
She added that vision systems can ensure the correct label is on each package and that label information is accurate.
“Systems can verify alpha text such as allergen information, as well as graphical IDs,” Crowley said.
Powered by AI
Artificial intelligence (AI) has powered quality assurance systems forward over the past few years and is helping food manufacturers detect more and smaller foreign objects while maintaining throughput.
“Artificial intelligence has become a key component of quality control in the food production industry,” said Daniel Greb, head of machine vision, Schubert. “Artificial intelligence fills a gap where algorithmic approaches often fail or are limited. It can perform tasks where algorithmic approaches cannot. An algorithmic approach usually requires measurable parameters to make a qualitative assessment. However, there is often a lack of correlation between different error classes. With the help of artificial neural networks, these correlations can be trained to a particular network. This makes quality control much easier.”
Metal detection software and technology have helped speed up processes, Lorei said.
“Advancements in metal detection software and technology have enabled us to detect metals on faster conveyor belts and identify smaller metal pieces, even when buried deeper or when using larger detector openings than possible in the past,” he said.
AI is continuing to revolutionize the way the food industry inspects food, Grube said.
“AI can be used to improve order accuracy, to reduce overall waste, to enhance safety and to comply with regulatory guidelines,” he said. “Data from detectors, sensors and X-rays is analyzed to make real-time adjustments on the processing line.”
The processing power for vision systems has gone through the roof, McGhie said.
“Where we might have been measuring seven attributes on a bun when we first started in vision serving bakeries, now we can measure 40, 50 things on a bun,” he said. “The lines are getting more throughput as well so we can analyze 1,600 buns or 10,000 biscuits a minute, no problem, and we can make a decision within 2 feet if an item is good or bad. And if it’s bad, the inspection system can reject it off the line.”
For vision systems, AI has allowed companies to look at items a bit more holistically, McGhie said. For instance, traditional systems often look at bake color, width and height of products, but AI can also look at shape and overall appearance. In other applications such as pizza toppings, inspecting similarly colored toppings, such as pepperoni slices, tomatoes and tomato paste, can be distinguished and measured separately to ensure the right quantity and distribution. It’s also helping to identify foreign objects that systems could not identify earlier.
“For example, clear plastics and foreign materials similar in color to the product have always been difficult to detect on a traditional vision system,” McGhie said.
But AI-enhanced inspection systems can be taught to identify it as a foreign material.
Technology is making vision systems easier to set up and simpler to use. Additionally, the vision system can communicate with equipment along the production line. For instance, if hamburger buns are too brown as they come out of the oven, the system can turn down the temperature or make other adjustments in the oven to get them back within their set parameters.
“AI is also being used to help simplify product setup using images of good products,” McGhie explained. “This learning from these images can provide a much faster, easier setup. The 30 or so attributes that are being measured can be set up with minimal operator intervention.”
And AI can identify smaller items like low-density plastics, which have traditionally been hard to see, Hermes said.
“X-ray with AI is now able to identify small items consistently but at a miniscule scale that our other programs and software wouldn’t be able to identify,” he said. “There’s a baseline 50% improvement across the board on every material type. It has completely revolutionized what can be detected or not detected.”
Hermes said X-ray systems will always have some false rejects, but AI can improve this problem, especially when it comes to certain challenging products, like those with a small metallic piece of packaging or a product with a desiccant package or another component that could throw off an X-ray system.
“With AI, we don’t really encounter any of those issues because we can teach it, for lack of a better term, what the good product looks like, and it can become accustomed to that,” he said.
Tying various quality assurance systems together becomes easier with AI, which leads to strong food safety programs, Garr said.
“Intuitive data management and the accessibility of AI now makes integration of any of these four inspection technologies — X-ray, metal detection, checkweighing and vision — possible,” he pointed out. “When integrated into a single system, this synergistically enhances the performance of each technology.”
He added that Fortress’ system reviews, collects data and oversees the performance of multiple metal detectors, checkweighers or combination inspection machines connected to the same network.
Friesen said that AI has helped improve automatic setup and product learning of systems, simplified reporting processes, improved monitoring capabilities and facilitated simplified final product inspection.
What’s coming next
As the technology that runs various quality assurance systems advances quickly, bakers and snack makers should stay tuned in the next few years for more progress in this field.
“The future of our global food system relies on transparency, traceability and data-informed decision-making,” Garr said. “This will inevitably accelerate the adoption of digital recordkeeping technologies. AI, especially when a data center is completely integrated into a single system, takes machine-learning, rule-based algorithm technologies and makes sense of the data the machine has collected. It enhances human intelligence and adds greater scientific input, assisting the actions taken to respond to issues rather than operating independently or replacing human decision-making.”
Greb said that new sensor technologies will become established in the food production industry.
“The areas of SWIR (short wavelength infrared) and radar sensor technology are currently developing rapidly and are becoming more attractive, especially from a financial perspective,” he said. “Furthermore, neural networks will continue to establish themselves and increasingly replace traditional algorithms.”
Advances in vision are going to make detection capabilities better, McGhie said.
“Those advances are not just in AI but also improvements in the resolution and speed of cameras, improvements in processing power to analyze the images,” he added. “Other advances in vision include hyperspectral imaging, which provides increased capability to detect foreign materials and other defects we previously weren’t able to reliably detect. The price of this technology is also falling, making it more accessible.”
In the next five years, bakers and snack producers can anticipate advancements in hardware that will enable the processing of more data without requiring additional equipment, Goasmat said.
“Another evolution would be achieving full integration with all equipment on the line, enabling the system to detect defaults and automatically regulate, ensuring self-correction,” he said. “Furthermore, it remains imperative to prioritize secure data storage. Given that bakers and snack makers entrust experts with their data to ensure seamless operations, it is essential for suppliers to furnish a robust privacy framework to safeguard this information effectively.”
The next big push is going to be dual- and multi-
energy, Hermes pointed out. It’s a new approach to using X-rays in determining different types of foreign materials.
“Dual-energy utilizes two different distinct wavelengths of X-rays, and each one will pass through or get stopped by different materials in a certain unique way,” he explained. “By blasting those through at the same time, and comparing how the product stops certain wavelengths in certain ways, we’re actually able to determine the composition of it. If it has a different molecular composition, we’re able to detect it now.”
Friesen said to look for improved detection accuracy through advanced algorithms and enhanced data integration and analysis capabilities with AI. He also sees more compact and energy-efficient systems, better detection of smaller contaminants and greater automation and remote monitoring systems coming in the near future.
Bakers and snack manufacturers have many quality assurance systems to choose from. One system or many combinations exist to help them keep their products safe from foreign contaminants. They must assess their risks and products then decide which system or systems work best for their operation.
This article is an excerpt from the August 2024 issue of Baking & Snack. To read the entire feature on Quality Assurance, click here.
