Comprehensive Performance Tests of the Paper Product Formation and Surface Appearance Quality Analysis and Classification System, 2021 TAPPICon Live (21TAPL)

Recently introduced new technologies for analyzing and classifying paper product formation and surface appearance are tested and the test results are presented in this paper. These new machine vision methods utilize elements of artificial intelligence (AI) for analysis and classification of paper product qualities. Methods are running online and include for example statistical feature extraction, unsupervised learning, paper product formation and surface appearance pattern extraction, modeling and recognition, supervised and unsupervised manufacturing process and paper product quality learning and exception detection.

The uniformity of the paper product formation often correlates with the paper structural properties, which are important for reaching acceptable strength and printability. Correspondingly the surface appearance needs also to be analyzed to guarantee high quality printability and adequate surface visual quality. The measurement results can be used for example for optimizing the coating processes and the usage of additives. Measurement of 100% of the product ensures required quality for the entire product area. 

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