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Focus on Global Tissue Key Move for Buckman, Tissue360º Spr
Focus on Global Tissue Key Move for Buckman, Tissue360º Spring/Summer 2016
Journal articles
Magazine articles
Bamboo Tissue Mill Nears Startup in China, Tissue360º Sprin
Bamboo Tissue Mill Nears Startup in China, Tissue360º Spring/Summer 2016
Journal articles
Magazine articles
2016 Edition of TAPPI Tissue360o Forum Best Yet, Tissue360º
2016 Edition of TAPPI Tissue360o Forum Best Yet, Tissue360º Spring/Summer 2016
Journal articles
Magazine articles
Recent advances in lignin-based polyurethanes, TAPPI JOURNAL
Recent advances in lignin-based polyurethanes, TAPPI JOURNAL April 2017
Journal articles
Magazine articles
Toward valorization of lignin: characterization and fast pyr
Toward valorization of lignin: characterization and fast pyrolysis of lignin recovered from hot-water extracts of electron-beam irradiated sugar maple, TAPPI JOURNAL April 2017
Journal articles
Magazine articles
Guest Editorial: The next act for nonwovens, TAPPI JOURNAL A
Guest Editorial: The next act for nonwovens, TAPPI JOURNAL August 2017
Journal articles
Magazine articles
Visual discrimination of hygiene tissue softness in the abse
Visual discrimination of hygiene tissue softness in the absence of haptic feedback, TAPPI JOURNAL August 2017
Journal articles
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Modeling the influence of forming fabric structure on vacuum
Modeling the influence of forming fabric structure on vacuum box dewatering, TAPPI JOURNAL August 2017
Journal articles
Magazine articles
Creating adaptive predictions for packaging-critical quality parameters using advanced analytics and machine learning, TAPPI Journal November 2019
ABSTRACT: Packaging manufacturers are challenged to achieve consistent strength targets and maximize pro-duction while reducing costs through smarter fiber utilization, chemical optimization, energy reduction, and more. With innovative instrumentation readily accessible, mills are collecting vast amounts of data that provide them with ever increasing visibility into their processes. Turning this visibility into actionable insight is key to successfully exceeding customer expectations and reducing costs. Predictive analytics supported by machine learning can provide real-time quality measures that remain robust and accurate in the face of changing machine conditions. These adaptive quality “soft sensors” allow for more informed, on-the-fly process changes; fast change detection; and process control optimization without requiring periodic model tuning.The use of predictive modeling in the paper industry has increased in recent years; however, little attention has been given to packaging finished quality. The use of machine learning to maintain prediction relevancy under ever-changing machine conditions is novel. In this paper, we demonstrate the process of establishing real-time, adaptive quality predictions in an industry focused on reel-to-reel quality control, and we discuss the value created through the availability and use of real-time critical quality.
Journal articles
Magazine articles
Over the Wire, Paper360º November/December 2019
Over the Wire, Paper360º November/December 2019