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By Mike Pehanich, Plant Operations Editor | 07/16/2007
“A growing trend — although it’s not huge yet — is Ethernet availability,” says Heat and Control’s Jesch. “As processors want to integrate more discrete equipment into the packaging line, they want to have this capability. Not many are ready for it yet from a control standpoint. It’s being used more for data collection than interpretation so far.”
Everyone wants connectivity today, Jeter emphasizes, underscoring the importance of safety data collection to HACCP programs. “Processors need to connect to a central data point where they can prove a detection system was turned on and operating during a production run; log and document the monitoring of product during production; and log and document rejects,” he adds.
Unwanted materials such as wood, insects, certain plastics, pieces of conveyor belt remain difficult to detect with metal detectors and other detection technologies. This fact has expanded opportunities for X-ray and other types of vision systems. Experience in the positioning of systems also has added to their effectiveness.
Processors are using multiple detection systems — and often multiple detection technologies. “Metal detectors find only metal, but X-ray systems find any kind of solid contaminant,” adds Jeter. While metal detector refinement aims at detection of tinier metal particles, X-ray and other emerging technologies can single out glass, stone, bone and some other materials.
The broader detection range of X-ray systems is a big reason for their popularity in processing plants. That versatility has allowed the technology to broaden its capability not only into detection of diverse substances but into a variety of process- and production-related functions as well.
Smiths Detection, the U.K.-based security corporation, introduced its own X-ray systems eight years ago. “Today our [X-ray] systems can checkweigh as well as check for bone, stone, glass, metal, dense rubber and other contaminants,” says Terry Woolford, Smiths Detection director. “They can even count product, shape-sense and detect metal contaminants inside metal containers — all on one pass of 600 to 700 packages per minute. That’s on machines running 100 meters a minute.”
Its fifth generation image analysis software (SimulTask 4.0) was designed for ease of use and customized control. Operators can view stored images and change image views. It also features an “auto-learn” for foreign materials detection and weight functions. The system can be set for automatic change for different shifts and batches.
A North American processor of garlic baguettes is employing a Smiths Detection system precisely because of this multi-functional capability. The process calls for the insertion of garlic butter between the slots, or layers, of the baguette.
“The unit can check to make sure there are enough slots in the bread and that there is butter in each slot,” says a company representative. “That’s in addition to finding contaminants.”
A meat producer is using yet another system for fat analysis in addition to its primary detection function. “This is big news for the industry since the lean value of meat is key in industry marketing today,” says Woolford.
Finding glass shards — particularly very small pieces — in glass jars has challenged some processors. A baby food manufacturer is employing Smiths Quad View, featuring a pair of two-beam X-ray generators, providing four beams for viewing.
The processor, one of the largest baby-food manufacturers in the world, claims the Quad View system can detect 1.5-2mm fragments of glass inside a glass container, including fragments situated in the difficult-to-view area behind the crown at the bottom of the jar. The advance may help other processors of glass-packed products.
The baby-food maker also uses the system to check fill level, cap fitting and, of course, contaminant detection.
The fluorescent sensing phenomenon has been around for decades but its application to food products is relatively new. Key Technology (www.keytechnology.com), Walla Walla, Wash., became a pioneer in food applications with its introduction of a pea-pack sorter under the Tegra label more than a decade ago. The camera-based system, which required black light or other special sources of illumination, would cause product with high chlorophyll content, such as a pea, to fluoresce. The degree of fluorescence varies with the chlorophyll content.
A vegetable processor utilizing the most sophisticated fluorescence-sensing systems available today can easily target product defects and foreign material and separate them from good product based on differences in the fluorescent properties of the object.
“We wanted to separate wood and stock from good (sunflower seed),” says one West Coast seed processor. “Some of the colors overlap, so the distinction is difficult.”
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