Northern Hub
The ROSEWOOD4.0 North Europe Hub covers the Nordic countries, in particular Finland, Sweden, Norway (consortium partner countries), Denmark and Baltic countries. The area has large forest resources and a high-level of forest expertise. Thanks to a long-standing tradition and the high professionalisation of forest management and research, the rate of forest growth is stable and the number of harvests could be increased without compromising durability.
Advanced Virtual Aptitude and Training Application in Real Time (AVATAR)
/in Central-West Hub, Hubs, News, News & Media, Northern HubDigital operator assistance for future CTL operations
Heat waves, droughts and related bark beetle infestations deeply affect middle European forestry. In Germany, around 80 million m³ timber were harvested in 2021, which is the highest quantity since 1990. 60 % of this amount can be considered as damaged wood [1]. To face these challenges, fully mechanized harvesting systems consisting out of single grip harvesters and forwarders are commonly used due to their high productivity and work safety.
Despite the advantages of these systems, the operation of forest machinery requires lengthy training. Operators experience high cognitive strain while operating forest machines. Within the AVATAR project, a digital coaching-, assistance- and feedback system was developed to increase operational efficiency of both harvesters and forwarders and to decrease mental workload for operators, while improving job satisfaction. The project lasted from 2019 to 2022 and was processed on an international level. Participating institutions were: State Forest Service Northrhine-Westfalia, University of Göttingen, Leibniz Research Center for Working Environment and Human Factors (Germany), Skogforsk (Sweden), NIBIO, Skogkurs and OPTEA As (Norway).
To increase efficiency and reduce mental workload of forest machine operators, machine manufacturers have developed operator assistance such as rotating cabins or intelligent crane controls. Within the AVATAR project, these technologies were scientifically evaluated and integrated in the digital coach concept. In various loading scenarios, it was found that the usage of intelligent crane controls and rotating cabins together produce synergy effects which significantly reduce time consumption per loading cycle for forwarders of up to 14 % [2]. Furthermore, results revealed that the use of intelligent crane controls widens productive loading areas of forwarders – despite greater loading distance and unfavourable loading angles, the forwarder operator needs the same time for loading compared to the favourable loading areas of the reference variant without driver assistance.
All these aspects were then integrated in the digital coach for forest machine operators. A harvester John Deere 1270 G was equipped with a lidar sensor platform to detect the machine environment during work. In addition, a head-up display from OPTEA As was integrated into the operator’s cabin, on which any information could be shown to the machine operator to simplify daily work. Based on the research results of preliminary studies [2,3], the machine position was shown, the position of the surrounding trees, the position of the harvester head as well as productive and maximum working ranges on the head-up display. The evaluation of the field tests showed that such digital assistance systems can support the operator. Autonomous forestry machines are difficult to imagine in the next few years because of too many incalculable effects on productivity and efficiency of the machines. That is why it is important to develop functioning and commercially viable operator assistance systems. The research was funded within the framework of the EU-project AVATAR under the umbrella of ERA-NET Cofound ForestValue by Fachagentur Nachwachsende Rohstoffe e.V. (FNR). ForestValue has received funding from the European Union´s Horizon 2020 research and innovation programme under grant agreement No. 773324.
Article authored by Florian Hartsch and Thilo Wagner.
Contact: florian.hartsch@wald-und-holz.nrw.de; thilo.wagner@wald-und-holz.nrw.de
References
[1]: Statistisches Bundesamt (2022): Neuer Rekordwert beim Holzeinschlag 2021. Höchste Holzeinschlagsmenge seit der deutschen Wiedervereinigung trotz weniger Schadholz aufgrund von Waldschäden. Accessed online: https://www.destatis.de/DE/Presse/Pressemitteilungen/2022/04/PD22_170_41.html (29.12.2022).
[2]: Hartsch, F.; Schönauer, M.; Pohle, C.; Breinig, L.; Wagner, T.; Jaeger, D. (2023, accepted, unpublished): Effects of Boom-tip control and a Rotating Cabin on Loading Efficiency of a Forwarder: A Pilot Study. Croatian Journal of Forest Engineering.
[3]: Hartsch, F.; Schönauer, M.; Breinig, L.; Jaeger, D. Influence of Loading Distance, Loading Angle and Log Orientation on Time Consumption of Forwarder Loading Cycles: A Pilot Case Study. Forests 2022, 13, 384. https://doi.org/10.3390/f13030384