Investment in the latest inline inspection technologies enables food manufacturers to not only improve contamination detection and product quality, but also production efficiency – as Bell Food Group recently discovered.
Bell is one of the major processors of meat and convenience products in Europe. Increased customer requirements and demands in terms of quality assurance and production capacity gave the company the push to rethink the configuration of their production line for burger patties. Bell decided to dismantle their existing line, carry out a hall conversion and replace individual production line components as part of modernisation measures.
They chose a new X39 x-ray inspection solution from Mettler-Toledo to support the improvements in their quality regime. The purchase decision was made after Bell had experienced the X39 in real time at two comparable sites in Ireland and Germany.
Along with metallic contaminants, the X39 can detect various additional foreign bodies that are commonly found in meat, including bone and cartilage, stones, high-density plastic or glass. The system also provides a whole range of other options for checking the patties for product errors and visual defects: such as patties joined together, holes, dents and product flakes.
Ueli Schönenberger, in charge of patty production at Bell, explains: “We used to remove patties that were broken or had holes in them from the belt by hand, or separate them manually before packaging. Thanks to the X39, the line manager now defines the tolerance limits for visual defects and the system will reject patties which don’t meet the standards.”
The X39 inspection system currently casts a strict x-ray eye over in excess of a million patties a week – most of these being three standard products, which vary in terms of size, form and weight.
Depending on the variant of burger patty that Bell are producing the x-ray system will inspect between three and six lanes. If a visual defect is detected, the relevant patty is rejected using multi-lane air nozzles. This significantly reduces the volume of patties rejected in comparison to simpler x-ray system variants that reject the entire batch from production. Bell can even differentiate between individual rejections by product error.
Says Ueli Schönenberger. “Thanks to the X39, we can first define and save the tolerance parameters for individual reasons for rejection. Then we can get an extremely detailed picture of how many patties were rejected as the result of foreign bodies, such as bone and cartilage, or as the result of visual defects. An image of each individual rejected patty is saved in the image library so that we can analyse exactly where and how the problems occurred. In my opinion, the combination of all these capabilities is far more than other providers can offer.”
Once the patties enter the x-ray system its integrated control laser checks if the patties have been separated properly: otherwise these patties are rejected and prepared for rework. This minimises product loss for the customer without losing out on any of the benefits of the product integrity check solution.
Application of data
The majority of product settings and tolerance limits for each patty variant have been validated within just over half a year and saved in the X39. Employees now simply select a product from the product library in order to run the inspection process, based on the pre-approved product data. While employees can carry out calibrations and rectify simple defects, line managers have further access options that enable them to carry out additional settings changes on the x-ray system.
Ueli Schönenberger concludes: “The x-ray technology provides us with enormous benefits in terms of quality assurance. We inspect the patties not only to check for foreign bodies, but also to ensure that the patties have no visual defects. This simplifies packaging and the customer receives a perfect-looking burger.”
In future, it will be possible to archive all data collected by the X39 within a network and evaluate it. This makes it easier for Bell to pass on quality indicators to customers. In turn, the customers can then analyze the figures for their own quality optimisation processes.