A model to predict productivity of different chipping operations

Abstract

The chipping operation is an important component of harvesting systems producing biomass and pulp chips. This paper aimed to develop a valid model to predict the productivity of chipping as part of these operations. Over a number of years more than 200 different time studies were conducted on chipping operations in Italy and Australia. Multiple regressions and backward stepwise data analysis methods were applied to develop a productivity prediction equation, considering the following variables: machine power (kW), piece size (m³), crew size, harvesting method, species, tree part, wood condition, wood lay-out, chipping type, propulsion, feeding method, point of chipping, season, location of chip discharge, country (Italy or Australia) and type of operation (biomass chip operation or pulp chip operation). The final productivity model included machine power, average piece size, location of chip discharge and type of operation as significant variables. The internal validation test was conducted using five witness samples from Italy and Australia, which confirmed the validity at α=0.05. Additional international case studies from North America, South America, and central and northern Europe were used to test the accuracy of the model, in which 15 studies confirmed the model's validity and two failed to pass the test.