Assessing chipper productivity and operator effects in forest biomass operations.

The present research focuses on the productivity of energy wood chipping operations at several sites in Italy. The aim was to assess the productivity and specifically the effect attributed to the operator in the chipping of wood biomass. The research included 172 trials involving 67 operators across the country that were analysed using a mixed model approach, in order to assess productivity, and to isolate the operator effect from other potential variables. The model was constructed using different predictors aiming to explain the variability due to the machines and the raw-materials. The final model included the average piece weight of raw material chipped as well as the power of the machine. The coefficients of determination (R2) were 0.76 for the fixed part of the model, and 0.88 when the effects due to the operators were included. The operators’ performance compared to their peers was established, and it was compared to a subjective classification based on the operator’s previous experience. The results of this study can help to the planning and logistics of raw material supply for bioenergy, as well as to a more effective training of future forest operators.

[1]  Juha Laitila,et al.  Harvesting Technology and the Cost of Fuel Chips from Early Thinnings , 2008 .

[2]  P. Anttila,et al.  The realisable potential supply of woody biomass from forests in the European Union. , 2011 .

[3]  J. V. Belle,et al.  A model to estimate fossil CO2 emissions during the harvesting of forest residues for energy—with an application on the case of chipping , 2006 .

[4]  Natascia Magagnotti,et al.  Logging companies in the European mountains: an example from the Italian Alps , 2013 .

[5]  P. Snowdon,et al.  A ratio estimator for bias correction in logarithmic regressions , 1991 .

[6]  Metsäteho Oy,et al.  Productivity and Cutting Costs of Thinning Harvesters , 2004 .

[7]  Jori Uusitalo,et al.  Characteristics and Significance of a Harvester Operators’ Working Technique in Thinnings , 2004 .

[8]  N. Magagnotti,et al.  The effects of introducing modern technology on the financial, labour and energy performance of forest operations in the Italian Alps , 2011 .

[9]  A. Asikainen,et al.  Hakkuutähdehakkeen kustannustekijät ja suurimittakaavaisen hankinnan logistiikka , 2001 .

[10]  D. Röser Operational efficiency of forest energy supply chains in different operational environments , 2012 .

[11]  Natascia Magagnotti,et al.  A tool for productivity and cost forecasting of decentralised wood chipping , 2010 .

[12]  A. Asikainen,et al.  Comminution of Logging Residues with Evolution 910R chipper, MOHA chipper truck, and Morbark 1200 tub grinder , 2013 .

[13]  Raffaele Spinelli,et al.  Performance Modelling in Forest Operations Through Partial Least Square Regression , 2012 .

[14]  Frank Thomas Purfürst,et al.  Learning Curves of Harvester Operators , 2010 .

[15]  N. Magagnotti,et al.  Determining the impact of some wood characteristics on the performance of a mobile chipper , 2011 .

[16]  Bruce R. Hartsough,et al.  A survey of Italian chipping operations , 2001 .

[17]  Karl Stampfer,et al.  Regional energy wood logistics - optimizing local fuel supply. , 2009 .

[18]  Dominik Röser,et al.  Chipping operations and efficiency in different operational environments. , 2012 .

[19]  Dominik Röser,et al.  Forest chips for energy in Europe: Current procurement methods and potentials , 2013 .

[20]  Raffaele Spinelli,et al.  Productivity and Cost of Mechanized Whole-Tree Harvesting of Fast-Growing Eucalypt Stands , 2002 .

[21]  Dominik Röser,et al.  Sustainable use of forest biomass for energy : a synthesis with focus on the Baltic and Nordic region , 2008 .