Terra-mechanical and statistical analyses of four-wheel grapple skidder performance data
Studies of skidder productivity typically involve a range of conditions that support specific study objectives related to harvest system, terrain, forest attribute, or other aspects of the harvest. Skidder production models often fit the data well because cycle time and productivity are strongly related to load size and skid distance. Changes in skidder design over time have increased load capacity, potential machine speed, and operator comfort. Since the harvest system often limits the observed range in speed and load size, the tradeoffs between those factors have not been a primary focus of production studies. We analyzed 33 studies with 77 estimates of skidder productivity using a typical regression approach and an approach based on the Wismer and Luth terra-mechanical (TM) relationships. The regression approach resulted in a good fit of productivity but poorer fits of cycle and element times. Nonlinear models developed with the TM approach also fit but had larger values for mean square error (MSE) than the linear regressions. The use of 14 additional studies with 33 estimates as validation data produced a lower mean square prediction error (MSPE) for nonlinear TM models when compared to the linear regression models. The TM approach allowed for the tradeoff between speed and load size to be modeled explicitly. We developed a spreadsheet production model to demonstrate the effect of choices made by harvest planners, logging managers, and operators on specific production goals.