Evaluation of Chipping Productivity with Five Different Mobile Chippers at Different Forest Sites by a Stochastic Model

It is important to evaluate chipping productivity that often differed according to the timing of observations and varied unexpectedly. A variation in production was the major concern of stakeholders for sustainable forest operation to establish regularly attainable production schedules on many operational levels. The aim of this study was to estimate the variance of chipping productivity by using a stochastic simulation model to achieve the objective evaluation of chipper performances. Chipping operations of five different kinds of mobile chippers, i.e. three smaller and two middle and larger ones in horse powers, were investigated. Probability distributions of material size and feeding time for chipping in a log-normal distribution were estimated. The estimates were made based on chipping operations performed 2000 or 4000 times by mechanical repetitions. Except for the largest chipper, whose observed productivity was 338 loose m/hr, all of the observed productivities, varying from 18 to 68 loose m/hr, were located within a two-sided confidential interval whose difference between both ends was 4 to 10 loose m/hr. The estimates were, generally, reliable with small variances around the median productivity values in the model. By this stochastic model, chipper productivity could be shown objectively, while the accuracy would be improved more by increasing sample size and accurate material size measurement. It was elucidated that the operations followed by chipping should encompass enough volume capacity to provide stable chipping productivity.

[1]  Antti Asikainen Chipping terminal logistics , 1998 .

[2]  Raffaele Spinelli,et al.  A model to predict productivity of different chipping operations , 2013 .

[3]  Karl Stampfer,et al.  Current state and development possibilities of wood chip supply chains in Austria , 2006 .

[4]  Raffaele Spinelli,et al.  Managing chipper knife wear to increase chip quality and reduce chipping cost , 2014 .

[5]  Alberto Assirelli,et al.  Effect of piece size and tree part on chipper performance , 2013 .

[6]  Bruce Talbot,et al.  Analysis of Two Simulated In-field Chipping and Extraction Systems in Spruce Thinnings , 2005 .

[7]  Mika Yoshida,et al.  Importance of capital cost reduction of chippers and their required productivity , 2013, Journal of Forest Research.

[8]  Antti Asikainen,et al.  Simulation of stump crushing and truck transport of chips , 2010 .

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

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

[11]  Glen Murphy,et al.  Stochastic simulation and optimization of mobile chipping and transport of forest biomass from harvest residues. , 2013 .

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

[13]  C. Gallis,et al.  Activity oriented stochastic computer simulation of forest biomass logistics in Greece , 1996 .

[14]  Rien Visser,et al.  Analyzing and estimating delays in wood chipping operations. , 2009 .

[15]  I. Samset Some observations on time and performance studies in forestry , 1990 .