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The influence of raw material characteristics on the industrial pelletizing process and pellet quality

    Publikation: Bidrag till tidskriftArtikel i vetenskaplig tidskriftPeer review

    Sammanfattning

    Industrial pelletizing of sawdust was carried out as a designed experiment in the factors: sawdust moisture content, fractions of fresh pine, stored pine and spruce. The process parameters and response variables were energy consumption, pellet flow rate, pellet bulk density, durability and moisture content. The final data consisted of twelve industrial scale runs. Because of the many response variables, data evaluation was by principal component analysis of a 12 x 9 data matrix. The two principal component model showed a clustering of samples, with a good reproducibility of the center points. It also showed a positive correlation of energy consumption, bulk density and durability all negatively correlated to flow rate and moisture content. The stored pine was more related to high durability and bulk density. The role of the spruce fraction was unclear. The design matrix, augmented with the process parameters was a 12 x 6 matrix. Partial least squares regression showed excellent results for pellet moisture content and bulk density. The model for durability was promising. A 12 x 21 data matrix of fatty- and resin acid concentrations measured by GC-MS showed the differences between fresh and stored pine very clearly. The influence of the spruce fraction was less clear. However, the influence of the fatty- and resin acids on the pelletizing process could not be confirmed, indicating that other differences between fresh and stored pine sawdust have to be investigated. This work shows that it is possible to design the pelletizing process for moderate energy consumption and high pellet quality. (C) 2008 Elsevier B.V. All rights reserved.
    OriginalspråkEngelska
    Sidor (från-till)1442-1447
    Antal sidor6
    TidskriftFuel Processing Technology
    Volym89
    Nummer12
    DOI
    StatusPublicerad - 2008

    Nyckelord

    • Industrial experimental design
    • Bulk density
    • Durability
    • Moisture content
    • Energy consumption
    • Multivariate data analysis

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