Search
Use the search bar or filters below to find any TAPPI product or publication.
Filters
Content Type
Publications
Level of Knowledge
Collections
Magazine articles
A guide to developing a best management practices (bmp) plan for spent liquor, part II, TAPPI JOURNAL, December 1999, Vol. 82(12)
A guide to developing a best management practices (bmp) plan for spent liquor, part II, TAPPI JOURNAL, December 1999, Vol. 82(12)
Magazine articles
Mönsterås going 100% TCF as it increases production and minimizes emissions, December 1995 Tappi Journal [95Dec49.pdf]
Monsteras going 100% tcf as it increases production and minimizes emissions, TAPPI JOURNAL, December 1995, Vol. 78(12)
Journal articles
Magazine articles
Application of ATR-IR measurements to predict the deinking efficiency of UV-cured inks, TAPPI Journal January 2022
ABSTRACT: In recent years, ultraviolet (UV)-curable ink has been developed and widely used in various printing applications. However, using UV-printed products (UV prints) in recovered paper recycling causes end-product dirt specks and quality issues. A new method was developed that can distinguish UV prints from other prints by means of attenuated total reflectance infrared (ATR-IR) spectroscopy. Application of this method could allow more efficient use of UV prints as raw materials for paper recycling.First, a mill trial was performed using UV prints alone as raw materials in a deinked pulp (DIP) process. Second, test prints were made with four types of UV inks: a conventional UV ink and three different highly-sensitive UV inks. Each print sample had four levels of four-color ink coverage patterns (100%, 75%, 50%, and 25%). Next, deinkability of all prints was evaluated by laboratory experiments. Finally, each print was measured using the ATR-IR method, and the relationship between the IR spectra and deinkability was investigated. Mill trial results showed that UV prints caused more than 20 times as many dirt specks as those printed with conventional oil-based ink. There were variations in recycling performance among UV prints taken from bales used for the mill trial. Lab tests clearly revealed that not all UV-printed products lead to dirt specks. In order to clarify the factors that affected deinkability of UV prints, the print samples were investigated by lab experiments. Key findings from lab experiments include: • The number of dirt specks larger than 250 µm in diameter increased as the ink coverage increased. • Higher ink coverage area showed stronger intensity of ATR-IR spectral bands associated with inks. These results indicate that deinkability of UV prints could be predicted by analysis of ATR-IR spectra. • Finally, the method was applied for assessment of recovered paper from commercial printing presses. It was confirmed that this method made it possible to distinguish easily deinkable UV prints from other UV prints. Based on these findings, we concluded that the ATR-IR method is applicable for inspection of incoming recovered paper.
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.
Magazine articles
Paperboard success stories, Solutions!, February 2004, Vol. 87(2) (101KB)
Paperboard success stories, Solutions!, February 2004, Vol. 87(2) (101KB)
Magazine articles
Five Steps to Excellent Communications on the Job, Solutions!, February 2006, Vol. 89(2) (159 KB)
Five Steps to Excellent Communications on the Job, Solutions!, February 2006, Vol. 89(2) (159 KB)
Magazine articles
A Retirement Tribute to Wayne H. Gross, TAPPI President, Solutions!, January 2006, Vol. 89(1) (68 KB)
A Retirement Tribute to Wayne H. Gross, TAPPI President, Solutions!, January 2006, Vol. 89(1) (68 KB)
Magazine articles
The Basics: What You Need to Know About Press Fabrics, Solutions!, January 2006, Vol. 89(1) (404 KB)
The Basics: What You Need to Know About Press Fabrics, Solutions!, January 2006, Vol. 89(1) (404 KB)
Journal articles
Magazine articles
TAPPI JOURNAL Summaries, Paper360º November/December 2017
TAPPI JOURNAL Summaries, Paper360º November/December 2017
Journal articles
Magazine articles
Effect of conductivity on paper and board machine performanc
Effect of conductivity on paper and board machine performance— a review and new experiences, TAPPI JOURNAL October 2017