Evolution of the Human Factor in Forestry Automation: From Manually Operated Forestry Machinery to Fully Autonomous Systems

The advancement of robotics, drones, and unmanned systems has significantly transformed forestry operations, particularly through the mechanization and automation of crane systems, trucks, and other forestry machinery used for timber harvesting and transportation. This research examines the transition of forestry machinery from manual operation to full autonomy, discussing how different levels of automation will impact technological development, adoption, and societal acceptance. The shift from traditional forestry equipment, requiring skilled human operators, to semi-automated and fully autonomous systems is driven by innovations in sensors, machine learning and advanced system control. While automation enhances efficiency, safety, and sustainability, it also presents challenges related to operator adaptation, job displacement, and trust in AI-driven systems.A key human factor in this transition is the cognitive load on operators. Initially, semi-automated systems increased this burden due to complex control interfaces, but advancements in intuitive human-machine interaction have helped to mitigate these effects. Acceptance among forestry professionals depends on factors such as reliability, ease of use, and perceived safety. Resistance to fully autonomous systems remains, particularly due to concerns about loss of control, unpredictable forest environments, and the ability of AI systems to make appropriate decisions under variable conditions. However, automation also offers significant benefits, including improved efficiency, enhanced safety, and solutions to labor shortages caused by demographic shifts. Additionally, it increases the attractiveness of forestry careers for younger generations. This research assesses the current state of forestry machinery and their respective levels of automation. Using the timber value chain as a case study, it explores how increasing automation will shape the future of forest management and outlines strategies to improve acceptance among operators and society. Ultimately, the research highlights how technological advancements can align worker’s well-being with sustainable management of forest resources.

Authors

Publication Details

Journal
AHFE international
Published
2025-01-01
DOI
https://doi.org/10.54941/ahfe1006370
Citations
1
Primary Topic
Flexible and Reconfigurable Manufacturing Systems
Type
article
Field-Weighted Citation Impact
1.24
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evolution of the Human Factor in Forestry Automation: From Manually Operated Forestry Machinery to Fully Autonomous Systems

Alexander Kreis, Mario Hirz, Karl Aumeier
1 citations
AHFE international
Flexible and Reconfigurable Manufacturing Systems
1.24
article

Evolution of the Human Factor in Forestry Automation: From Manually Operated Forestry Machinery to Fully Autonomous Systems

Alexander Kreis, Mario Hirz, Karl Aumeier
article en
1 citations

Abstract

The advancement of robotics, drones, and unmanned systems has significantly transformed forestry operations, particularly through the mechanization and automation of crane systems, trucks, and other forestry machinery used for timber harvesting and transportation. This research examines the transition of forestry machinery from manual operation to full autonomy, discussing how different levels of automation will impact technological development, adoption, and societal acceptance. The shift from traditional forestry equipment, requiring skilled human operators, to semi-automated and fully autonomous systems is driven by innovations in sensors, machine learning and advanced system control. While automation enhances efficiency, safety, and sustainability, it also presents challenges related to operator adaptation, job displacement, and trust in AI-driven systems.A key human factor in this transition is the cognitive load on operators. Initially, semi-automated systems increased this burden due to complex control interfaces, but advancements in intuitive human-machine interaction have helped to mitigate these effects. Acceptance among forestry professionals depends on factors such as reliability, ease of use, and perceived safety. Resistance to fully autonomous systems remains, particularly due to concerns about loss of control, unpredictable forest environments, and the ability of AI systems to make appropriate decisions under variable conditions. However, automation also offers significant benefits, including improved efficiency, enhanced safety, and solutions to labor shortages caused by demographic shifts. Additionally, it increases the attractiveness of forestry careers for younger generations. This research assesses the current state of forestry machinery and their respective levels of automation. Using the timber value chain as a case study, it explores how increasing automation will shape the future of forest management and outlines strategies to improve acceptance among operators and society. Ultimately, the research highlights how technological advancements can align worker’s well-being with sustainable management of forest resources.

AHFE internationalVol. 179
Openalex Percentile: Top 18%
Flexible and Reconfigurable Manufacturing Systems
1.24
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.