Open AccessEffects of Working Time and the Volume and Weight of Timber on Productivity of Log Loader Caterpillar Type 966 F and WL 980 C
Author(s) -
Bei Kewilaa,
Apri Tehupeiory
Publication year - 2018
Publication title -
wood research journal
Language(s) - English
Resource type - Journals
ISSN - 2774-9320
DOI - 10.51850/wrj.2015.6.1.8-13
Subject(s) - productivity , volume (thermodynamics) , linear regression , regression analysis , environmental science , felling , loader , statistics , mathematics , agricultural engineering , engineering , agroforestry , economics , mechanical engineering , physics , quantum mechanics , macroeconomics
Timber harvesting involves a series of activities to move timber from harvesting sites to the processing sites. The activities could be divided into four main components: felling, skidding, hauling and stockpiling. Loading at the landing site and unloading of cargo at the log yard are some of the major activities in timber harvesting. The overall activity is influenced by various factors such as timber volume and weight as well as working time. However, there has been lack of empirical information about what factors influenced by the productivity of timber harvesting in tropical forest in eastern Indonesia. Thus, the aim of this study was to determine the effect of timber volume and weight as well as the working time and their interaction on the productivity of Log Loader Caterpillar 966 F Type and WL 980 C which are the most commonly used equipments in tropical timber harvesting in Indonesia. The multiple linear regression analysis showed that on the loading productivity, the volume and weight of timber, the working time and interaction among them showed positive coefficient regression but others showed negative coefficient regression; while on the unloading productivity, volume, the working time, interaction between volume and weight of timber, and interaction between weight of timber and working time showed positive coefficient regression but others showed negative coefficient regression; and on loading and unloading productivity of cargo per round trip hauling, volume and weight of timber showed positive coefficient regression, but their interaction shows negative coefficient regression. Thus, these factors were taken into account in predicting the magnitude of tool productivity.