Productivity and Costs of Mechanized Skidding operations at Sao Hill Forest Plantation, Tanzania

Abstract

Due to global advancement of technology in forest operations, utilization of advanced machineries such as grapple skidder (GS) in timber harvesting has been increasing in the last decades. However, in order to understand their contribution in sustainable harvesting operations, it is important to understand their performance under different operating environment. Therefore, this study aimed to quantify productivity and cost of mechanised skidding operations at Sao Hill Forest plantation (SHFP). Six variables; diameter at a breast height (dbh), tree height, skidding distance, slope, costs, and cycle time (determined using detailed continuous time study) were collected in 120 GS observations.GS productivity and costs were estimated using productive machine hour (PMH) and delays inclusion approach. Regression models were developed using a generalized linear model (GLM) approach. GS productivity under PMH was 2.6% higher than the one including delay time, while skidding costs was 2.1% higher in the approach including delays. This study revealed significant variations (p-value <0.05) in productivity and cost on various terrain classes. At 0 m – 50 m distance, an average delays free GS productivity was 85.5 m³/h, with costs amounting to 1.7 USD/m³. On the distance exceeding 150 m, productivity dropped to 20.1 m³/h, and costs increased to 12.7 USD/m³. Likewise, in 0.0% - 10.0% slope range, average delays free GS productivity and costs was 100 m³/h and 1.5 USD/m³ respectively, while at 20.1% - 30.0% slope range, productivity dropped to 32.6 m³/h and costs raised to 3.9 USD/m³. Skidding distance, slope, and volume per trip were robust predictors of the GS productivity and costs, yielding pseudo-R² values of 58.1% and 64.3%, respectively. Therefore, this study developed statistical models useful for predicting GS productivity and costs, however, their applications are recommended to be within the ranges of the variables used to develop the models.

Keywords:

• cycle time
• delay time
• grapple skidder
• terrain variables
• work element

Acknowledgments

We acknowledge the project titled “Higher Education for Economic Transformation (HEET)”, under Sokoine University of Agriculture and Tanzania Forest Fund (TaFF), for providing financial support during data collection.

Author Contributions

Conceptualization: Gilberth Prosper Temba, Ernest William Mauya, George Ansigar Migunga.

Data analysis: Gilberth Prosper Temba.

Methodology: Gilberth Prosper Temba, Ernest William Mauya.

Supervision: Ernest William Mauya, George Ansigar Migunga.

Writing – original draft: Gilberth Prosper Temba.

Writing – review and editing: Gilberth Prosper Temba, Ernest William Mauya, George Ansigar Migunga.

Additional information

Funding

Sokoine University of Agriculture 10.13039/501100023918 and Tanzania Forest Fund.