Overall Forest Machinery Efficiency Indicator (OFME) in forest harvesting management

被引:0
|
作者
Silva, Arthur Araujo [1 ]
Machado, Carlos Cardoso [1 ]
Gomes, Raiane Ribeiro Machado [1 ]
Schettini, Bruno Leao Said [1 ]
Minette, Luciano Jose [1 ]
Nunes, Italo Lima [1 ]
Villanova, Paulo Henrique [1 ]
机构
[1] Univ Fed Vicosa UFV, Vicosa, MG, Brazil
来源
SCIENTIA FORESTALIS | 2022年 / 50卷
关键词
Performance; Harvester; Simulation;
D O I
10.18671/scifor.v50.43
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Performance indicators are tools capable of exposing measurable characteristics and generating forest operations relevant information, being considered pillars for agile and assertive decision making by managers. Productivity (P), fuel consumption (FC), operational efficiency (OE) and operation quality or final product (OQ) need to be better studied in the forestry sector. The aim of the study was to evaluate the Overall Forest Machinery Efficiency (OFME) indicator implementation in the management of forest stand harvesting data using harvesters. Data were collected during forest harvesting in commercial eucalypt stands located in Bahia and Espirito Santo states, Brazil. The OFME indicator was expressed as a percentage, calculated by: OFME = ((3*P)+(3*FC)+(3*OE)+(1*OQ))/10. The machines' performance was evaluated with a stochastic model of dynamic simulation of systems in nine scenarios, proposing improvements in relation to the average individual volume, fuel consumption, mechanical or operational stops and operation quality. The analyses were performed using the PowerSim Studio 9 software. TheOFME of fleet 05 was higher than the target (93%), with 93.45%. This is due to the greater productivity, operational efficiency and quality of operation of this fleet. The OFME indicator proved to be useful in the forest stand harvesting management with adequate and easy to understand information from a data variety. The harvester overall efficiency varies with the individual forest average volume as shown in the calculations and proven by the stochastic simulation model developed.
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页数:9
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