Using the Weibull distribution to model harvesting machine productivity
1988
Hawkins, K.E. | Hotvedt, J.E. | Cao, Q.V. | Jackson, B.D.
The feasibility of using the Weibull probability distribution to represent machine productivity distributions in harvesting system simulation models was assessed. Parameters of the Weibull probability density function were derived from maximum likelihood techniques using time study data, and from moment estimation techniques using time study data summary statistics (mean, variance, minimum value, and number of observations). Weibull parameters were found to be obtainable from productivity equations by moment estimation techniques if the minimum dependent value, the mean of the independent value(s), the number of observations, and other information are reported. The use of Weibull distributions for harvesting machine productivity distributions was evaluated in a thinning operation comprised of two Finnish-made Makeri harvesters and a Franklin 132 forwarder, and in a clearcutting operation consisting of a Hydro-Ax 311 feller and two Clark C-666 grapple skidders. Two methods of evaluation were used for determining if the Weibull probability distribution was feasible for characterizing productivity distributions. The simplest evaluation was to compare a generated Weibull distribution with a frequency distribution of the actual data. In the second comparison, the results of harvesting system simulations using actual time study data were compared to the results of harvesting system simulations employing Weibull distributions derived from the actual data. Results of the study imply that Weibull parameters (or distributions) estimated from maximum likelihood and moment estimation techniques are good substitutes for actual machine productivity distributions in harvesting system simulations.
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