The detection of catching injuries, such as hematomas and broken wings, is a crucial criterion for assessing the quality of animal transport. Technically, this poses a challenge as visibility of the wings may be limited. To address this issue, CLK GmbH has developed the Catching Damage Control module. The catch damage control is installed in a 180° curve of the hook conveyor system.

Additionally, the module distinguishes whether a broken wing occurred during processing, i.e. during slaughter, or during the catching process. Broken wings without hematomas are attributed to the slaughtering process, while broken wings with hematomas are classified as catching injuries.

The module also enables the detection of catching injuries on the breast and thighs.

The early and precise weight measurement of individual poultry parts, such as breast fillets, thighs, wings, as well as the total weight, can be critical for production processes. With the Rendite System, another module of the ChickenCheck suite, CLK GmbH has developed a solution to accurately measure poultry parts while still on the hook, even before they are disassembled.

To achieve this, a model was developed based on a wide range of poultry breeds, enabling precise mapping of weight distribution after disassembly. The slaughtered poultry is scanned from both sides using two 3D cameras, and the captured images are merged into a comprehensive 360° representation. Using robust statistical methods and artificial intelligence, the images are analyzed in detail.

The Rendite System has proven its effectiveness in accurately determining the weight proportions of broiler chickens at the very start of the processing line in numerous locations. In addition to optimizing production control (e.g., precise adjustment of machinery) and supplier evaluation (e.g., assessing deviations in breast weight from expected yields to evaluate rearing quality), the system also provides insights into flock homogeneity. By analyzing the recorded weight proportions of each individual animal and evaluating variations within the flock, the system offers valuable information on the uniformity of weight distribution within the flock.

Preventing contamination in slaughterhouses is a key aspect of food safety. One significant risk is posed by animals with full crops. If a full crop is cut open during the slaughtering process, its contents may spill onto the carcass or the surrounding environment, leading to contamination of the meat and the production area. To minimize the risk of such contamination, early detection of full crops is essential.

The crop cetection module uses color and 3D cameras combined with a neural network to accurately measure and identify full crops. When an animal with a full crop is detected, it can be removed from the process. This prevents the cutting of the full crop and the resulting contamination of products and the environment.

The system also enables the documentation of incidents involving full crops, the identification of batch-related clusters, and the precise tracking of potential causes. This proactive approach enhances food safety while providing valuable data for operational improvements.

Consisting of a camera, a lighting unit, and a processing unit equipped with AI algorithms, the footpad control system can detect potential footpad dermatitis in broiler chickens, ducks, and turkeys and classify it into various stages. The ChickenCheck footpad control system can be calibrated to meet national animal welfare assessment requirements, such as using three or four quality levels. Based on the captured images and classifications, insights into housing conditions can be derived. Furthermore, feedback can be provided to farmers, and transparency in the slaughterhouse can be enhanced through detailed statistics and data storage.

In addition to identifying footpad dermatitis, analyzing hock joint inflammations in poultry is another critical aspect of welfare assessment. By integrating the joint control system, the ChickenCheck system can classify hock joint inflammations in up to three quality levels. Similar to the footpad control system, the joint control system enables conclusions about housing conditions and the development of improvement measures.

With the help of the DeepHyperCheck system, films, bones, and plastics can be detected in meat products (such as chicken nuggets or cold cuts) while they are conveyed on a belt. The system utilizes transmitted light, a state-of-the-art camera, and artificial intelligence. The system is compact, highly precise, and can be integrated directly onto the conveyor belt without additional effort.

Visit us on our stand A28 in hall 9.1 to get more information about the DeepHyperCheck.

The MultiCheck by CLK GmbH is an innovative camera system designed specifically for foreign object detection in multihead weighers. It combines state-of-the-art image processing technology with artificial intelligence (AI) to elevate product safety and quality in food production while minimizing product recalls.

To detect foreign objects, the system assigns defined color ranges to the product, background, and unwanted objects. It is capable of identifying plastic contaminants as small as 1mm x 1mm, with detection of foreign objects made from other materials also possible. The inspection takes place immediately before packaging, significantly reducing the risk of further contamination as the products are sealed directly after inspection.

The MultiCheck stands out for its high detection probability, even for partially concealed foreign objects. Image sequences are captured from multiple perspectives during the product’s fall through the multihead weigher. All detected foreign objects are stored in an internal database and are available as images and statistical reports for review.