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Journal articles
Paper surface makeup process observed by ultrasound, TAPPI JOURNAL, October 2000, Vol. 83(10)
Paper surface makeup process observed by ultrasound, TAPPI JOURNAL, October 2000, Vol. 83(10)
Magazine articles
People development in research and technology organizations, TAPPI JOURNAL, October 2000, Vol. 83(10)
People development in research and technology organizations, TAPPI JOURNAL, October 2000, Vol. 83(10)
Journal articles
Agile manufacturing: enabling optimal value chain management through new production technology, TAPPI JOURNAL, December 2000, Vol. 83(12)
Agile manufacturing: enabling optimal value chain management through new production technology, TAPPI JOURNAL, December 2000, Vol. 83(12)
Journal articles
Application of polyallylamine as a dry strength agent for paper, TAPPI JOURNAL, December 2000, Vol. 83(12)
Application of polyallylamine as a dry strength agent for paper, TAPPI JOURNAL, December 2000, Vol. 83(12)
Journal articles
Effect of the paper structure and composition on the surface sizing pick-up, TAPPI JOURNAL, December 2000, Vol. 83(12)
Effect of the paper structure and composition on the surface sizing pick-up, TAPPI JOURNAL, December 2000, Vol. 83(12)
Journal articles
Great northern paper revitalizes millinocket mill, TAPPI JOURNAL, December 2000, Vol. 83(12)
Great northern paper revitalizes millinocket mill, TAPPI JOURNAL, December 2000, Vol. 83(12)
Journal articles
The business of research: strategies for the future, TAPPI JOURNAL, December 2000, Vol. 83(12)
The business of research: strategies for the future, TAPPI JOURNAL, December 2000, Vol. 83(12)
Journal articles
The forest products industry: a sustainable industry, TAPPI JOURNAL, December 2000, Vol. 83(12)
The forest products industry: a sustainable industry, TAPPI JOURNAL, December 2000, Vol. 83(12)
Journal articles
89APR177
MD microstriations in paper: a two-sided shrinkage phenomenon?, TAPPI JOURNAL April 1989
Journal articles
Magazine articles
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.