Quality prediction by neural network for pulp and paper processes

Kim, H.C.; Shen, Xuemin; Rao, Ming; Zurcher, J.

doi:10.1109/ccece.1993.332225

Cited by 4 publications

(2 citation statements)

References 3 publications

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“…Another method was proposed by Chagaev and Zou [11] in which they introduced the pulp quality index and fiber development index based on the content ratio of fines to coarse fibers to monitor strength development during mechanical pulp refining. Efforts have been made to explore the relationship between chemical and physical properties of the pulp fiber and their inherent paper making strength properties by various researchers [12][13][14][15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Relationship between Strength Properties and Fiber Morphological Characteristics of S. officinarum

2017

IJSR

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Abstract:The impact of different pulp morphological properties on paper properties has been the subject of interest for paper makers.Relationships between the physical strength properties of S. officinarum pulp, like tensile index, tear index, burst index & double fold number, and the morphological characteristics of pulp fiber after at beating levels is developed in the present work. Multiple linear regression (MLR) and artificial neural networks (ANN) analysis are used to develop relationship models which can be useful to monitor and control quality of the paper products. The results have indicated that the MLR and ANN approaches can be successfully used to model the effects of beating on strength parameters of S. officinarum pulp.

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Section: Introductionmentioning

confidence: 99%

Relationship between Strength Properties and Fiber Morphological Characteristics of S. officinarum

2017

IJSR

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“…MLR has been used to explore possibility of correlation between morphological features and the strength parameters by various researchers [3][4][5][6][7][8][9][10][11]. Similarly possibility of application of ANN in the paper industry has also been reported in various articles [12][13][14][15][16][17][18] to use neural network based model for prediction of paper properties based on factors related to the most important refining effects, such as the fiber and pulp average length, width and fines content. However there is no systematic study reported in the literature on relationship of morphological characteristics and strength properties of paper made from the most commonly used raw materials by the industry.…”

Section: Introductionmentioning

confidence: 99%

Relationship between Strength Properties and Fiber Morphological Characteristics of E. tereticornis

2017

IJSR

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Morphology of pulp significantly affect the paper properties and many researchers have made efforts to evaluate their relationship to control the paper properties. In continuation of the studies by the authors, relationship between the physical strength properties and morphological characteristics of E. tereticornis was evaluated. In order to develop the relationship between morphological characteristics of bleached chemical pulps, the changes in fiber morphology of E. tereticornis after beating to different levels was estimated. The handsheets prepared from the pulps beaten to different levels were tested for changes in strength properties. Multiple linear regression (MLR) & artificial neural networks (ANN) analysis were used to develop relationship of strength propertieswith the morphological characteristics of the pulp fibers. Studies have revealed that all four strength properties studied (tensile index, tear index, burst index and double fold) correlate significantly with the change in the morphological characteristics on beating. The results indicate that the MLR and ANN can be successfully used as tools to reveal the relationships between strength properties with fiber morphological characteristics in E. tereticornis pulp.

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