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Combustion behaviors of lignin-lean black liquor and lignin, TAPPI JOURNAL July 2015

Combustion behaviors of lignin-lean black liquor and lignin, TAPPI JOURNAL July 2015

Journal articles
Magazine articles
Open Access
Editorial: Marc Foulger: All things papermaking, TAPPI JOUR

Editorial: Marc Foulger: All things papermaking, TAPPI JOURNAL November 2015

Journal articles
Magazine articles
Open Access
Causality of manufacturing processes with significant time

Causality of manufacturing processes with significant time delays, TAPPI JOURNAL November 2015

Journal articles
Magazine articles
Open Access
Desilication of bamboo for pulp production, TAPPI JOURNAL N

Desilication of bamboo for pulp production, TAPPI JOURNAL November 2015

Journal articles
Magazine articles
Tissue Industry News, Tissue360º Fall/Winter 2016

Tissue Industry News, Tissue360º Fall/Winter 2016

Journal articles
Magazine articles
Von Drehle Starts Up First Valmet NTT Tissue Machine in the

Von Drehle Starts Up First Valmet NTT Tissue Machine in the U.S., Tissue360º Fall/Winter 2016

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Making the Most of Opportunity in Tissue?, Tissue360º Fall/W

Making the Most of Opportunity in Tissue?, Tissue360º Fall/Winter 2016

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Magazine articles
Reducing MRO Inventory Using RCM Principles, Tissue360º Fall

Reducing MRO Inventory Using RCM Principles, Tissue360º Fall/Winter 2016

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Magazine articles
Open Access
Modeling and parameter optimization of the papermaking processes by using regression tree model and full factorial design, TAPPI Journal February 2021

ABSTRACT: One of the major challenges in the pulp and paper industry is taking advantage of the large amount of data generated through its processes in order to develop models for optimization purposes, mainly in the papermaking, where the current practice for solving optimization problems is the error-proofing method. First, the multiple linear regression technique is applied to find the variables that affect the output pressure controlling the gap of the paper sheet between the rod sizer and spooner sections, which is the main cause of paper breaks. As a measure to determine the predictive capacity of the adjusted model, the coefficient of determination (R2) and s values for the output pressure were considered, while the variance inflation factor was used to identify and eliminate the collinearity problem. Considering the same amount of data available by using machine learning, the regression tree was the best model based on the root mean square error (RSME) and R2. To find the optimal operating conditions using the regression tree model as source of output pressure measurement, a full factorial design was developed. Using an alpha level of 5%, findings show that linear regression and the regression tree model found only four independent variables as significant; thus, the regression tree model demonstrated a clear advantage over the linear regression model alone by improving operating conditions and demonstrating less variability in output pressure. Furthermore, in the present work, it was demonstrated that the adjusted models with good predictive capacity can be used to design noninvasive experiments and obtain.

Journal articles
Magazine articles
Open Access
Editorial: Change, reality, and vision in the pulp and paper industry, TAPPI Journal February 2021

ABSTRACT: Change is inevitable and is a constant in our lives. Change is especially evident in this era of whirlwind, revolutionary break-throughs in communication and control technology. If nothing else, the past year has certainly made this clear.

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