The Importance of Distribution Statistics in the Characterisation of Chip Quality
Metallurgical and Materials Transactions B
This study examines the effect of wood-chip dimensions on pulp quality. Chip fractions were classified by size, and chips in each fraction were measured manually to determine precise distributions for length, width, and thickness. The classified fractions were then cooked (low-yield magnesium bisulfite), and pulp handsheets were tested. Pulp quality for small chips (R 114-in. fraction) matched or exceeded that of longer chips (R 314-in. fraction). Statistical analysis revealed that the skewness and kurtosis of the distribution in chip width had a significant effect on tensile strength, accounting for almost 50% of the variability in tensile energy absorption. Skewness in chip-width distribution also had an important effect on tear index, along with skewness in chip thickness and kurtosis in chip length. Selectivity of delignification varied with chip size distribution at the same overall yield. Changes in the skewness of chip-width distribution alone accounted for over half the variation in kappa number. Application: Statistical analysis of chip-size distributions reveals that measures of dispersion within the distribution are better predictors of pulp quality than average chip size.
(1998). The Importance of Distribution Statistics in the Characterisation of Chip Quality. Metallurgical and Materials Transactions B, 81(2), 131-142.
Available at: https://nsuworks.nova.edu/cps_facarticles/1040