Tetra Laval International had one patent in big data during Q4 2023. The patent filed by Tetra Laval International SA in Q4 2023 describes a method for assessing the quality of longitudinal sealing in a roll fed packaging machine. This method involves receiving strip application image data, extracting features related to the heating effects during strip application, determining the strip application status based on these features, and transmitting the strip application status to provide a quality assessment of the longitudinal strip sealing. GlobalData’s report on Tetra Laval International gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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Tetra Laval International grant share with big data as a theme is 0% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: A method for assessing quality of a longitudinal sealing and a server (Patent ID: US20230331419A1)
The patent filed by Tetra Laval International SA describes a method for assessing the quality of longitudinal sealing in a roll fed packaging machine. The method involves using a strip applicator to apply a protective strip on the packaging material web by heating and pressing them together, while a strip application camera captures image data for quality assessment. Features related to the effects of heating are extracted from the image data to determine the strip application status, which is then transmitted to provide a quality assessment of the longitudinal strip sealing.
Additionally, the patent includes claims for further steps such as receiving the web and protective strip, forming the longitudinal strip sealing, capturing image data, and assessing the tube forming status. The method also involves applying the protective strip in a specific manner to cover the exposed intermediate layer of the packaging material. The transmitted status can indicate underheating, normal heating, or overheating, allowing for adjustments in the heating power. Furthermore, the method involves utilizing artificial intelligence models to determine the status based on extracted features from the image data, which include identifying overlapping areas, heat-affected regions, and reflective properties of the sealing.
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