應用統計迴歸分析探討木漿纖維素黏膠液的固形物含量及其最適紡絲溫度、黏度

本研究以三級胺氮氧化物共溶劑水溶液溶解木漿纖維素，主要製備四種木漿纖維素固形物含量多寡不同濃度的紡絲黏膠液，探討紡絲製程不同濃度最適的溫度、黏度相關性及其紡絲的穩定性，利用Minitab軟體迴歸分析，找出依變數對自變數之間的迴歸方程式，即紡絲黏膠液黏度與溫度高低及固形物含量之關係式為Ŷ_(紡絲黏膠液黏度)=-1,171,445 + 348,626 × 固形物含量-26,709 × 溫度，最佳迴歸模式R^2 = 99.06%，自變數對依變數預測能力佳，黏膠液的溫度與固形物含量均對黏度有顯著的影響，是一組相當有用的預測變數，此一線性回歸模式非常顯著，即以統計迴歸分析木漿纖維素黏膠液固形物含量及溫度來預測黏度相當準確。

關鍵字

木漿纖維素；紡絲黏膠液；溫度黏度；迴歸分析

並列摘要

In this study, a tertiary amine nitrogen oxide co-solvent solution to dissolve wood pulp cellulose, mainly prepares four types of spinning viscose with different concentrations of wood pulp cellulose solid content, and explores the optimum temperature and viscosity for different concentrations in the spinning process. Correlation and spinning stability, using Minitab software regression analysis to find the regression equation between the dependent variable and the independent variable, that is, the relationship between the viscosity of the spinning viscose and the temperature and solid content is Ŷ_(Viscosity of spinning viscose) = -1,171,445 + 348,626 × solid content - 26,709 × temperature. The best regression model R^2 = 99.06%, the independent variable predicts the dependent variable well, the temperature and solid content of the viscose liquid. The content has a significant effect on the viscosity and is a set of very useful predictive variables. This linear regression model is very significant, that is, it is quite accurate to predict the viscosity by statistical regression analysis of the solid content and temperature of the wood pulp cellulose viscose liquid.

並列關鍵字

cellulose ； spinning dope ； temperature viscosity ； regression analysis

參考文獻

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