Search
Use the search bar or filters below to find any TAPPI product or publication.
Filters
Content Type
Publications
Level of Knowledge
Committees
Collections
Journal articles
Use of enzymes for reduction in refining energy - laboratory
Use of enzymes for reduction in refining energy - laboratory studies, TAPPI JOURNAL, November 2006
Journal articles
Sizing variations of dispersed rosin sizes with fortification, hardness, pH, and temperature, TAPPI JOURNAL, April 2003, Vol. 2(4) (93KB)
Sizing variations of dispersed rosin sizes with fortification, hardness, pH, and temperature, Solutions! & TAPPI JOURNAL, April 2003, Vol. 2(4) (93KB)
Journal articles
Impact of refining intensity on energy reduction in commercial refiners: effect of primary-stage consistency, TAPPI JOURNAL, January 1997, Vol. 80(1)
Impact of refining intensity on energy reduction in commercial refiners: effect of primary-stage consistency, TAPPI JOURNAL, January 1997, Vol. 80(1)
Journal articles
Predictive advisory solutions for chemistry management, control, and optimization, TAPPI Journal March 2025
ABSTRACT: Process runnability and end-product quality in paper and board making are often connected to chemistry. Typically, monitoring of the chemistry status is based on a few laboratory measurements and a limited number of online specific chemistry-related measurements. Therefore, mill personnel do not have real-time transparency of the chemistry related phenomena, which can cause production instability, including deposition, higher chemical consumption, quality issues in the end-product and runnability problems. Machine learning techniques have been used to establish soft sensor models and to detect abnormalities. Furthermore, these soft sensors prove to be most useful when combined with expert-driven interpretation. This study is aimed at utilizing a hybrid solution comprising chemistry and physics models and machine learning models for stabilizing chemistry-related processes in paper and board production. The principal idea is to combine chemistry/physics models and machine learning models in a fashion close to white box modeling. A cornerstone in the approach is to formulate explanations of the findings from the models; that is, to explain in plain text what the findings mean and how operational changes can mitigate the identified risks. The approach has been demonstrated for several different applications, including deposit control in the wet end, both raw water treatment and usage, and wastewater treatment. This approach provides mill personnel with knowledge of identified phenomena and recommendations on how to stabilize chemistry-related processes. Instead of using close to black box machine learning models, a hybrid solution including chemistry/physics models can enhance the performance of artificial intelligence (AI) deployed systems. A successful way of gaining the trust from mill personnel is by creating a plain text explanation of the findings from the hybrid models. The correlation between the likelihood of a phenomena and disturbance and the explanations are derived and validated by application and chemistry and physics experts.
Magazine articles
Forklift emissions - some solutions, TAPPI JOURNAL, December 1993, Vol. 76(12)
Forklift emissions - some solutions, TAPPI JOURNAL, December 1993, Vol. 76(12)
Journal articles
Refining: Good practice for refining the types of fiber found in modern paper furnishes, February 1995 Tappi Journal [95Feb147.pdf]
Good practice for refining the types of fiber found in modern paper furnishes, TAPPI JOURNAL, February 1995, Vol. 78(2)
Journal articles
Predictive advisory solutions for chemistry management, control, and optimization, TAPPI Journal March 2025
ABSTRACT: Process runnability and end-product quality in paper and board making are often connected to chemistry. Typically, monitoring of the chemistry status is based on a few laboratory measurements and a limited number of online specific chemistry-related measurements. Therefore, mill personnel do not have real-time transparency of the chemistry related phenomena, which can cause production instability, including deposition, higher chemical consumption, quality issues in the end-product and runnability problems. Machine learning techniques have been used to establish soft sensor models and to detect abnormalities. Furthermore, these soft sensors prove to be most useful when combined with expert-driven interpretation. This study is aimed at utilizing a hybrid solution comprising chemistry and physics models and machine learning models for stabilizing chemistry-related processes in paper and board production. The principal idea is to combine chemistry/physics models and machine learning models in a fashion close to white box modeling. A cornerstone in the approach is to formulate explanations of the findings from the models; that is, to explain in plain text what the findings mean and how operational changes can mitigate the identified risks. The approach has been demonstrated for several different applications, including deposit control in the wet end, both raw water treatment and usage, and wastewater treatment. This approach provides mill personnel with knowledge of identified phenomena and recommendations on how to stabilize chemistry-related processes. Instead of using close to black box machine learning models, a hybrid solution including chemistry/physics models can enhance the performance of artificial intelligence (AI) deployed systems. A successful way of gaining the trust from mill personnel is by creating a plain text explanation of the findings from the hybrid models. The correlation between the likelihood of a phenomena and disturbance and the explanations are derived and validated by application and chemistry and physics experts.
Journal articles
Characterization of refined papermaking pulps using hydrodynamic parameters from filtration analysis, TAPPI JOURNAL May 2015
Characterization of refined papermaking pulps using hydrodynamic parameters from filtration analysis, TAPPI JOURNAL May 2015
Journal articles
Choosing the right refiner plate bolts: a practical guide, TAPPI JOURNAL, February 2000, Vol. 83(2)
Choosing the right refiner plate bolts: a practical guide, TAPPI JOURNAL, February 2000, Vol. 83(2)
Journal articles
Practical windows and inhibitors for grade 2 titanium use in alkaline peroxide bleach solutions, TAPPI JOURNAL, November 1995, Vol. 78(11)
Practical windows and inhibitors for grade 2 titanium use in alkaline peroxide bleach solutions, TAPPI JOURNAL, November 1995, Vol. 78(11)