Intelligent measuring device evaluates opening forces of peelable packages
The new measuring device "Pack Peel Scan" was developed at the Fraunhofer Institute for process engineering and Packaging IVV, Dresden, for testing peelable packaging. Equipped with artificial intelligence, it enables the efficient measurement of Easy Opening packaging. The opening forces of thermoformed, peelable packaging can thus be recorded and checked in accordance with standards. "Pack Peel Scan" has a machine learning method that is used to predict and avoid process errors. During K Messe, the international trade fair for plastics, rubber, plastics processing and plastics manufacturing, the new measuring instrument will be demonstrated in Düsseldorf from 16 to 23 October 2019 in Hall 7, Stand 70SC01.
"Pack Peel Scan" checks the opening forces of thermoformed, peelable packaging in accordance with standards. The machine learning method also makes it possible to forecast and avoid process errors.
Fraunhofer IVV
"Pack Peel Scan" can be used as an external measuring device in the production of peelable packaging for food, medical products etc.. It detects opening forces of trays and film packaging in accordance with standards. Opening force and opening path are measured. By comparing the tear forces with the guide values for easy-to-open packaging, the device provides a statement as to whether the packaging is actually easy-to-open. The seam quality can be evaluated directly during production. With the flexible adjustment of the packaging contour and height, packages of any shape can be safely used and efficiently measured and inspected. In addition, an artificial intelligence evaluates the recorded force curves and identifies possible errors in the sealing process.
"Pack Peel Scan" enables machine learning with operator assistance system
In addition to operation as an autonomous test device, an integrated operator assistance system based on machine learning can be used for fault diagnosis. The data on specific opening force curves are also used by machine learning methods to predict process errors. This enables relevant information to be passed on to the process control system or for concrete instructions to be issued to the machine operator. The system is able to learn the causes of malfunctions in the sealing process and to work towards their prevention. Plant operators, for example, receive information on the possible cause of a seal seam that does not meet quality requirements.
The device was developed as part of a ZIM project with the company IMA Ingenieurgesellschaft für Maschinenbau und Anlagen GmbH. ZIM, the Central Innovation Programme for SMEs, is a nationwide, technology and industry open funding programme of the Federal Ministry of Economics and Energy (BMWi) to support small and medium-sized enterprises as well as cooperating research institutions.
Note: This article has been translated using a computer system without human intervention. LUMITOS offers these automatic translations to present a wider range of current news. Since this article has been translated with automatic translation, it is possible that it contains errors in vocabulary, syntax or grammar. The original article in German can be found here.
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