Technical-economic analysis of the felling of Eucalyptus species with feller-buncher: A stochastic approach

• Autor(a) principal: Pereira, Gilberto [UNESP]
• Data de Publicação: 2020
• Outros Autores: Fenner, Paulo Torres [UNESP], Batistela, Gislaine Cristina [UNESP], Simões, Danilo [UNESP]
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.18671/SCIFOR.V48N126.14; http://hdl.handle.net/11449/206709
• topic: Cost assessment; Monte Carlo; Productivity; Timber harvesting; Uncertainty

In mechanized harvesting operations for wood, the Monte Carlo method allows the probability of occurrence of the technical-economical parameters, with descriptions of the uncertainties and, consequently, the optimization of harvesting systems. This study used the stochastic approach applied for felling forests planted with Eucalyptus species performed by a self-propelled machine having a felling head, with a feller-buncher disk, in two spacings between trees, through the Monte Carlo simulation method for the analysis of the technical-economic parameters. Historical data on monetary values were considered, as well as the volume of felled timber and actual production time, considering variables under uncertainty conditions, which were adjusted by probability distributions. The Monte Carlo simulation method was applied to mathematical models in order to incorporate stochastic solutions. The results reached the conclusion that the monetary values demanded for spare part replacements for the self-propelled machine presented the highest degree of association with the programmed hourly cost; there was a strong negative nonlinear relationship between the monetary values required for the acquisition of lubricating oils and greases and the programmed hourly cost of the self-propelled machine, showing that the higher the investment in lubrication, the lower the programmed hourly cost of this machine; the average value of the production cost for felling Eucalyptus species is explained by 46% of the productivity variance per hour of the self-propelled machine.