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A tool for productivity and cost forecasting of decentralised wood chipping

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  • Spinelli, Raffaele
  • Magagnotti, Natascia

Abstract

The growing interest in forest biomass has made chipping increasingly popular all across Europe. Many operators have equipped for the purpose, but the large variety of working conditions found in the European forests makes it difficult to correctly estimate the productivity of each specific operation, leading to uncertainty in crucial decisions, such as: operation scheduling, price setting, machinery selection and acquisition. In 2001, the Italian National Council for Research (CNR) and the University of California (UC) developed a spreadsheet freeware capable of returning reliable estimates of chipping productivity and cost, on the basis of user-defined input data. The model is still available from the CNR website and is the object of frequent downloading and inquiries. Such model contains a set of predictive equations derived from the results of 102 field trials, conducted with 30 different machines, under a range of working conditions. In order to facilitate comparison with other estimates and to achieve methodological transparency, the equations are assembled into a simple Microsoft Excel workbook, and the costs are calculated with standard costing methods currently used in Forest and Agricultural Engineering. Since then CNR has continued to work on the subject, with the goal of updating and refining the model. Such work has included 45 validation tests and a separate study on the delay (idle) time typical for different chipping operation layouts. The study was concluded in 2009 and confirms that the model developed by CNR can provide reliable estimates of chipper productivity under a range of operational conditions. Authors believe that such a model can assist European foresters in keeping ahead with the growing biomass sector, thus helping them to seize an important business opportunity.

Suggested Citation

  • Spinelli, Raffaele & Magagnotti, Natascia, 2010. "A tool for productivity and cost forecasting of decentralised wood chipping," Forest Policy and Economics, Elsevier, vol. 12(3), pages 194-198, March.
    • Handle: RePEc:eee:forpol:v:12:y:2010:i:3:p:194-198
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    References listed on IDEAS

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    1. Hartsough, Bruce R. & Abrams, Scott & Barbour, R. James & Drews, Erik S. & McIver, James D. & Moghaddas, Jason J. & Schwilk, Dylan W. & Stephens, Scott L., 2008. "The economics of alternative fuel reduction treatments in western United States dry forests: Financial and policy implications from the National Fire and Fire Surrogate Study," Forest Policy and Economics, Elsevier, vol. 10(6), pages 344-354, August.
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    3. Toupin, Dominic & LeBel, Luc & Dubeau, Denise & Imbeau, Daniel & Bouthillier, Luc, 2007. "Measuring the productivity and physical workload of brushcutters within the context of a production-based pay system," Forest Policy and Economics, Elsevier, vol. 9(8), pages 1046-1055, May.
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    1. Spinelli, Raffaele & Cavallo, Eugenio & Eliasson, Lars & Facello, Alessio & Magagnotti, Natascia, 2015. "The effect of drum design on chipper performance," Renewable Energy, Elsevier, vol. 81(C), pages 57-61.
    2. M.R. Ghaffariyan & J. Sessions & M. Brown, 2012. "Evaluating productivity, cost, chip quality and biomass recovery for a mobile chipper in Australian roadside chipping operations," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 58(12), pages 530-535.
    3. Juha Laitila & Robert Prinz & Lauri Sikanen, 2019. "Selection of a chipper technology for small-scale operations - a Finnish case," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 65(4), pages 121-133.

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