Mid Sweden University

In 1963, Forgacs showed that at least two quality variables are needed in order to characterize the quality of mechanical pulps. Later, Strand came to asimilar conclusion by introducing two independent common factors through the use of factor analysis. Both Forgacs and Strand showed that handsheet properties can be predicted from these two factors. This paper shows how STORA, on the basis of Strand’s approach, examines the two independent common factors directly, instead of examining a large amount of conventional measured pulp and handsheet properties. The factors are called F1, fibrebonding, and F2, long fibre influence. The independent factors are controlled to a great extent by independent process parameters; F1 correlates more strongly to specific energy than does freeness while F2 is mainly controlled by conditions in the defibration stage. In order to produce a uniform pulp quality, F1 and F2 should be kept inside a specified quality window. Since July 1995 a quality window in terms of F1 and F2 has been used at STORA Kvarnsveden TMP plant and thus has given a more stable pulp quality. The quality window gives a rapid overview of the status of the quality. Another advantage of applying F1 and F2 is that not only refiners, but also screens and cleaners can be evaluated in terms of the same quality variables. New parameters for evaluation of screens and cleaners are suggested. By examining all process stages from chip refiner, screen room to final pulp we can get a quality map in terms of F1 and F2. From this map it is quite obvious how the pulp quality is influenced by chip refiner stage and rejects refining. The F1/F2-map can simplify the work to find reasons for producing off-spec pulp and also mee tone big challenge: to produce a product of more uniform quality. To attain more uniform quality we have to think and speak daily in terms of factors like F1 and F2.

As a vital component in the strive towards improved energy efficiency in the operation of TMP refining processes, this work highlights the importance of well- designed procedures when collecting and analysing pulp properties with respect to process conditions. Process data and pulp from a CD82 chip refiner have been used to show that tensile index has strong covariance with fibre residence time calculated by the extended entropy model. A combination of theoretical and practical analysis methods has shown that, in order to assure representative, reliable results, pulp sampling procedures should comprise composite pulp samples collected during a sampling period of about three minutes. In addition, at least four subsequently collected composite pulp samples should be included in the analysis to effectively dampen effects from fast process variations as well as from slow process drift. An in-depth study on tensile index measurements clarifies that 40-60 strips should be used in the case we studied regardless if machine made paper or handsheets are considered.

Currently, the pulp and paper industry mainly uses average values of   mechanical pulp properties to characterize fibers, while printing paper   grammages keep decreasing, making every fiber more important for   strength, surface, and structure properties. Because fibers are   inhomogeneous, average values of the whole pulp may not be enough for   proper fiber characterization. This paper reports results from the   development of a method to measure the distribution of fiber bonding   ability in mechanical pulps.   Fibers from two commercial TMPs were fractionated into five   hydrocyclone streams, using a four-stage hydrocyclone system. The fiber   bonding ability of Bauer McNett fractions R16, P16/R30 and P30/R50   collected from each stream was analyzed. Five different methods of   evaluating fiber bonding ability all showed that fibers were separated   in the hydrocyclones according to their bonding ability.   Long fiber handsheets of the highest bonding fibers had up to 2.5 times   higher tensile strength for the P16/1330 fraction than handsheets from   the lowest bonding fibers. We also found that both the degree of   fibrillation and collapse resistance index (CRI) of the fibers obtained   from optical measurements are sufficient to predict quite accurately   the tensile strength of handsheets made from fiber fractions. Further,   we propose how to describe the distribution in fiber bonding ability   for mechanical pulps, by combining some of these five different   methods. A method to calculate fracture toughness of long fiber   handsheets based on acoustic emission is also illustrated.   A more rapid way to characterize fibers in mechanical pulps with   respect to their bonding ability distribution needs to be developed in   the future. It appears that it is time to move on from characterizing   pulp suspensions and handsheet properties using conventional approaches   based on average values.

This study discusses how fiber dimensions affect the tensile index and density of long fiber laboratory sheets. Five commercial mechanical pulps (three TMP grades, one SGW and one CTMP) were fractionated into five streams in a hydrocyclone pilot plant. Fiber dimensions and fibrillation were analyzed of the P16/R30 and P30/R50 fractions and compared to the sheet properties. For comparison, samples were also analyzed by SEM cross-sectional image analysis and in a MorFi Lab optical analyzer. Fibrillation index showed a high positive influence on long fiber tensile index and density, whereas fiber wall thickness, fiber width, and collapse resistance index a negative. Fiber width showed the vaguest correlation to long fiber tensile index and density of the analyzed fiber properties, but this increased when combined with fiber wall thickness into collapse resistance index, CRI. The correlations between fiber properties and sheet properties were on different levels for the different mechanical pulping processes, but a combination of collapse resistance index and fibrillation index into the novel factor BIN, Bonding ability INfluence, gave one linear relation of high correlation to long fiber tensile index for all pulps, except the SGW P30/R50 fraction, which showed the same linear correlation on a slightly lower level. BIN should be a useful tool in characterizing mechanical pulp fibers.

Particles in mechanical pulp show a wide variety but are commonly described using averages and/or collective properties. The authors suggest using distributions of a common bonding factor, BIND (Bonding INDicator), for each particle. The BIND-distribution is based on factor analysis of particle diameter, wall thickness, and external fibrillation of several mechanical pulps measured in an optical analyser. A characteristic BIND-distribution is set in the primary refiner, depending on both wood and process conditions, and remains almost intact along the process. Double-disc refiners gave flatter distributions and lower amounts of fibres with extreme values than single-disc refiners. More refining increased the differences between fibres with low and high BIND. Hence, it is more difficult to develop fibres with lower BIND. Examples are given of how BIND-distributions may be used to assess energy efficiency, fractionation efficiency, and influence of raw material. Mill scale operations were studied for printing-grade thermomechanical pulp (TMP), and board-grade chemi-thermomechanical pulp (CTMP), both from spruce.

The purpose of this study was to investigate the applicability of different ways of calculating the average fibre length based on length measurements of individual particles of mechanical pulps. We have found that the commonly used average length-weighted fibre length, which is based on the assumption that coarseness is constant for all particles, as well as the arithmetic average, may lead to erroneous conclusions in real life as well as in simulations when used as a measure of the amount of long fibres. The average length-length-weighted fibre length or a weighting close to that, which to a larger extent suppresses the influence of shorter particles, is a relevant parameter of the "length" factor, i. e. amount of long fibres. Our findings are based on three studies: refining of different assortments of wood raw material in a mill; data from LC refining in mill of TMP, including Bauer McNett fractionation; mixing of pulps with different fibre length distributions. If the acceptable average fibre length for different products can be lowered, the possibility of reducing the specific energy input in refining will increase. Therefore, we need a reliable and appropriate way to assess the "length" factor.