Bringing automation to forest production with precision tools
Rising equipment costs, unpredictable weather, long hours and hazardous conditions make logging a high-risk industry. Not only is it difficult to attract and maintain skilled workers to forest production, but these challenges also make it difficult for firms to forecast the impacts of external factors to remain competitive.
Researchers at Auburn University in Alabama partnered with equipment manufacturers to develop smart technology that uses sensors to monitor machine performance in real time and automatically track how productive logging equipment is while it is working in the field. Tools designed to evaluate and compare crew productivity across different sites and conditions allowed a collaborating logging firm to link performance data with external factors such as weather, trucking availability and site-specific challenges.
The patterns and constraints that emerged from the data provided enhanced visibility that allowed firms to make more informed decisions, including adjusting operations in response to fluctuating markets and field conditions and forecasting future productivity with greater accuracy. By helping logging firms remain resilient even when conditions change, these tools contribute to safeguarding steady jobs and bolstering the economic health of rural regions.
Auburn University Research | Project supported by Hatch capacity funds. Photo courtesy of Auburn University Research.
