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Journal articles
Production of a pure lignin product, part 1: Distribution and removal of inorganics in Eucalyptus globulus kraft lignin, TAPPI JOURNAL March 2014
Production of a pure lignin product, part 1: Distribution and removal of inorganics in Eucalyptus globulus kraft lignin, TAPPI JOURNAL March 2014
Journal articles
Fast evaluation of spatial coating layer formation using ultraviolet scanner imaging
Fast evaluation of spatial coating layer formation using ultraviolet scanner imaging
Journal articles
Review of currently available technology for the conversion of woody biomass o value-added products 15MAR160
Review of currently available technology for the conversion of woody biomass to value-added products, TAPPI JOURNAL March 2015
Journal articles
Commissioning Brownstock Washing Controls for an Evaporator
Commissioning Brownstock Washing Controls for an Evaporator Limited Mill, TAPPI JOURNAL July 2016
Journal articles
Research pathways and outreach to drive cellulosic nanomater
Research pathways and outreach to drive cellulosic nanomaterials development, TAPPI JOURNAL June 2016
Journal articles
Acoustic analysis of recovery boiler dissolving tank operati
Acoustic analysis of recovery boiler dissolving tank operation and smelt shattering efficiency, TAPPI JOURNAL September 2016
Journal articles
Magazine articles
Editorial: Professional Networking in the Nonwovens and Technical Textiles Sector
Editorial: Professional Networking in the Nonwovens and Technical Textiles Sector
Journal articles
Magazine articles
Improved deinking and stickies removal
Improved deinking and stickies removal, TAPPI JOURNAL November 2017
Journal articles
Magazine articles
Monitoring the free lime content in lime mud using zeta potential, TAPPI JOURANL April 2018
Monitoring the free lime content in lime mud using zeta potential, TAPPI JOURANL April 2018
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.